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The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site
Report highlights
Chapter 1 Reseach and Development
Chapter 2 Technical Performance
Chapter 3 Technical AI Ethics
Chapter 4 The Economy and Education
Chapter 5 AI Policy and Governance
Appendix

Exciting, Useful, Worrying, Futuristic: Public Perception of Artificial Intelligence in 8 Countries / 2001.00081 / ISBN:https://doi.org/10.48550/arXiv.2001.00081 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background
3 Methodology
4 Findings
5 Discussion
6 Conclusions
Acknowledgments
References
A Questionnaire - Selected Questions

Ethics of AI: A Systematic Literature Review of Principles and Challenges / 2109.07906 / ISBN:https://doi.org/10.48550/arXiv.2109.07906 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background
5 Detail results and analysis
7 Conclusions and future directions
References
9 Appendices

AI Ethics Issues in Real World: Evidence from AI Incident Database / 2206.07635 / ISBN:https://doi.org/10.48550/arXiv.2206.07635 / Published by ArXiv / on (web) Publishing site
1Introduction
2 Related Work
4 Results
5 Discussion
References

The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis / 2206.03225 / ISBN:https://doi.org/10.48550/arXiv.2206.03225 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Study Methodology
4 Evaluation of Ethical AI Principles
5 Evaluation of Ethical Principle Implementations
6 Gap Mitigation
7 Threats to Validiity
References

A Framework for Ethical AI at the United Nations / 2104.12547 / ISBN:https://doi.org/10.48550/arXiv.2104.12547 / Published by ArXiv / on (web) Publishing site
Introductionn
1. Problems with AI
2. Defining ethical AI
3. Implementing ethical AI
Conclusion

Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance / 2206.11922 / ISBN:https://doi.org/10.48550/arXiv.2206.11922 / Published by ArXiv / on (web) Publishing site
2 Related Work
3 Methodology
4 Results
5 Discussion
Acknowledgments

Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society / 2001.04335 / ISBN:https://doi.org/10.48550/arXiv.2001.04335 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 The Near-Long
3 The Problem with the Near/Long-Term Distinction
4 A Clearer Account of Research Priorities and Disagreements
Recommendations and Conclusion
References

ESR: Ethics and Society Review of Artificial Intelligence Research / 2106.11521 / ISBN:https://doi.org/10.48550/arXiv.2106.11521 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 The ESR Process
4 Deployment and Evaluation
5 Discussion
6 Conclusion
7 Acknowledgments
A Appendix: Interview Protocol
References

On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services / 2111.01306 / ISBN:https://doi.org/10.48550/arXiv.2111.01306 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 The Need forEthical AI in Finance
3 Practical Challengesof Ethical AI
4 Conclusions & Outlook
References

A primer on AI ethics via arXiv- focus 2020-2023 / Kaggle / Published by Kaggle / on (web) Publishing site
Section 1: Introduction and concept
Section 2: History and prospective
Section 3: Current trends 2020-2023
Section 4: Considerations and conclusions
Appendix A: Bibliographical references
Appendix B: Data and charts from arXiv

What does it mean to be a responsible AI practitioner: An ontology of roles and skills / 2205.03946 / ISBN:https://doi.org/10.48550/arXiv.2205.03946 / Published by ArXiv / on (web) Publishing site
2 Background
3 Methodology
4 Proposed competency framework for responsible AI practitioners
5 Discussion
6 Conclusion
Acknowledgments
References
Appendix A supplementary material

GPT detectors are biased against non-native English writers / 2304.02819 / ISBN:https://doi.org/10.48550/arXiv.2304.02819 / Published by ArXiv / on (web) Publishing site
Results
Discussion
Acknowledgements
References
Materials and Methods

Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects / 2304.08275 / ISBN:https://doi.org/10.48550/arXiv.2304.08275 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Underlying Aspects
III. Interactions between Aspects
IV. Concluding Remarks
References

QB4AIRA: A Question Bank for AI Risk Assessment / 2305.09300 / ISBN:https://doi.org/10.48550/arXiv.2305.09300 / Published by ArXiv / on (web) Publishing site
2 The Question Bank: QB4AIRA
3 Evaluation
4 Conclusion
References

A multilevel framework for AI governance / 2307.03198 / ISBN:https://doi.org/10.48550/arXiv.2307.03198 / Published by ArXiv / on (web) Publishing site
3. International and National Governance
4. Corporate Self-Governance
5. AI Literacy and Governance by Citizen
7. Propensity to Trust
8. Ethics and Trust Lenses in the Multilevel Framework
9. Virtue Ethics
References

From OECD to India: Exploring cross-cultural differences in perceived trust, responsibility and reliance of AI and human experts / 2307.15452 / ISBN:https://doi.org/10.48550/arXiv.2307.15452 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Method
3. Results
4. Discussion and conclusion
Acknowledgments
References

The Ethics of AI Value Chains / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site
2. Theory
4. Ethical Implications of AI Value Chains
5. Future Directions for Research, Practice, & Policy
6. Conclusion

Perceptions of the Fourth Industrial Revolution and Artificial Intelligence Impact on Society / 2308.02030 / ISBN:https://doi.org/10.48550/arXiv.2308.02030 / Published by ArXiv / on (web) Publishing site
Abstract
Literature Review
Results
References

Regulating AI manipulation: Applying Insights from behavioral economics and psychology to enhance the practicality of the EU AI Act / 2308.02041 / ISBN:https://doi.org/10.48550/arXiv.2308.02041 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Clarifying Terminologies of Article-5: Insights from Behavioral Economics and Psychology
4 Conclusion

From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence / 2308.02448 / ISBN:https://doi.org/10.48550/arXiv.2308.02448 / Published by ArXiv / on (web) Publishing site
Introduction
What is Generative Artificial Intelligence?
Applications in Military Versus Healthcare
Identifying Ethical Concerns and Risks
GREAT PLEA Ethical Principles for Generative AI in Healthcare
Acknowledgements
References

Ethical Considerations and Policy Implications for Large Language Models: Guiding Responsible Development and Deployment / 2308.02678 / ISBN:https://doi.org/10.48550/arXiv.2308.02678 / Published by ArXiv / on (web) Publishing site
Introduction
System-role
Image-related
Hallucination

Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AI / 2308.04448 / ISBN:https://doi.org/10.48550/arXiv.2308.04448 / Published by ArXiv / on (web) Publishing site
2 Background
3 Policy scope
4 Centralized regulation in the US context
5 Crowdsourced safety mechanism
6 The dual governance framework
7 Limitations

Normative Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions / 2208.12616 / ISBN:https://doi.org/10.48550/arXiv.2208.12616 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Methodology
3 Taxonomy of ethical principles
4 Previous operationalisation of ethical principles
5 Gaps in operationalising ethical principles
References
A Methodology

Bad, mad, and cooked: Moral responsibility for civilian harms in human-AI military teams / 2211.06326 / ISBN:https://doi.org/10.48550/arXiv.2211.06326 / Published by ArXiv / on (web) Publishing site
Introduction
Responsibility in War
Computers, Autonomy and Accountability
Moral Injury
AI Workplace Health and Safety Framework
References

The Future of ChatGPT-enabled Labor Market: A Preliminary Study / 2304.09823 / ISBN:https://doi.org/10.48550/arXiv.2304.09823 / Published by ArXiv / on (web) Publishing site
Abstract
2 Results
3 Discussion
4 Limitations

A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation / 2305.11391 / ISBN:https://doi.org/10.48550/arXiv.2305.11391 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Large Language Models
3 Vulnerabilities, Attack, and Limitations
5 Falsification and Evaluation
6 Verification
7 Runtime Monitor
8 Regulations and Ethical Use
9 Discussions
Acknowledgments
Reference

Getting pwn'd by AI: Penetration Testing with Large Language Models / 2308.00121 / ISBN:https://doi.org/10.48550/arXiv.2308.00121 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
6 Final ethical considerations
References

Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust / 2308.09979 / ISBN:https://doi.org/10.48550/arXiv.2308.09979 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Results
3 Discussion
4 Conclusions
5 Supplementary material
References

Targeted Data Augmentation for bias mitigation / 2308.11386 / ISBN:https://doi.org/10.48550/arXiv.2308.11386 / Published by ArXiv / on (web) Publishing site
2 Related works
3 Targeted data augmentation
4 Experiments
5 Conclusions
6 Acknowledgements
References

AIxArtist: A First-Person Tale of Interacting with Artificial Intelligence to Escape Creative Block / 2308.11424 / ISBN:https://doi.org/10.48550/arXiv.2308.11424 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Case study
References

Exploring the Power of Creative AI Tools and Game-Based Methodologies for Interactive Web-Based Programming / 2308.11649 / ISBN:https://doi.org/10.48550/arXiv.2308.11649 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Emergence of Creative AI Tools and Game-Based Methodologies
7 Navigating Constraints: Limitations of Creative AI and GameBased Techniques
8 Real-World Applications: Showcasing Innovative Implementations
10 Privacy Concerns in Interactive Web-Based Programming for Education
12 The Future Landscape: Creative AI Tools and Game-Based Methodologies in Education
14 Conclusion & Discussion
References

Collect, Measure, Repeat: Reliability Factors for Responsible AI Data Collection / 2308.12885 / ISBN:https://doi.org/10.48550/arXiv.2308.12885 / Published by ArXiv / on (web) Publishing site
2 Related Work on Data Excellence
3 Reliability and Reproducibility Metrics for Responsible Data Collection
4 Published Annotation Tasks and Datasets
5 Results
6 Discussion
References
A Agreement Analysis
E Replicability similarity analysis

Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph / 2308.13534 / ISBN:https://doi.org/10.48550/arXiv.2308.13534 / Published by ArXiv / on (web) Publishing site
III. Comprehensive review of state-of-the-art LLMs
V. Market analysis of LLMs and cross-industry use cases
VI. Solution architecture for privacy-aware and trustworthy conversational AI
References
Appendix A industry-wide LLM usecases

The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward / 2308.14253 / ISBN:https://doi.org/10.48550/arXiv.2308.14253 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 The evolution of artificial intelligence: from theory to general capabilities
3 Emerging dual-use risks and vulnerabilities in AI systems
4 Integrating red teaming, blue teaming, and ethics with violet teaming
6 A pathway for balanced AI innovation
7 Violet teaming to address dual-use risks of AI in biotechnology
9 The path forward
10 Supplemental & additional details
References

Artificial Intelligence in Career Counseling: A Test Case with ResumAI / 2308.14301 / ISBN:https://doi.org/10.48550/arXiv.2308.14301 / Published by ArXiv / on (web) Publishing site
2 Literature review
5 Conclusion
References

Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? / 2308.15399 / ISBN:https://doi.org/10.48550/arXiv.2308.15399 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Works
3 Theory and Method
4 Experiment
Acknowledgments
References

The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / ISBN:https://doi.org/10.48550/arXiv.2308.16538 / Published by ArXiv / on (web) Publishing site
Table of contents and index
Executive summary
1 Introduction
2 Key AI technology in financial services
3 Benefits of AI use in the finance sector
4 Threaths & potential pitfalls
5 Challenges
6 Regulation of AI and regulating through AI
7 Recommendations
References

Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / ISBN:https://doi.org/10.48550/arXiv.2309.00064 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Black box and lack of transparency
3 Bias and fairness
4 Human-centric AI
5 Ethical concerns and value alignment
6 Way forward
References

The Impact of Artificial Intelligence on the Evolution of Digital Education: A Comparative Study of OpenAI Text Generation Tools including ChatGPT, Bing Chat, Bard, and Ernie / 2309.02029 / ISBN:https://doi.org/10.48550/arXiv.2309.02029 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Related work
3. ChatGPT Training Process
4. Methods
5. Discussion
6. Conclusion
References

Pathway to Future Symbiotic Creativity / 2209.02388 / ISBN:https://doi.org/10.48550/arXiv.2209.02388 / Published by ArXiv / on (web) Publishing site
Introduction
Part 1 - 1 Generatives Systems: Mimicking Artifacts
Part 1 - 3 Artistic Systems: Mimicking Inspiration
Part 2 Art Data and Human–Machine Interaction in Art Creation
Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data
Part 2 - 2 Motion Caputer Technologies and Motion Data
Part 2 - 3 Photogrammetry / Volumetric Capture
Part 3 - 2 Machine Artist Models
Part 3 - 3 Comparison with Generative Models
Part 3 - 4 Demonstration of the Proposed Framework
Part 4 NFTs and the Future Art Economy
Part 5 Ethical AI and Machine Artist
Part 5 - 1 Authorship and Ownership of AI-generated Works of Artt
Part 5 - 3 Democratization of Art with new Technologies

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging / 2109.09658 / ISBN:https://doi.org/10.48550/arXiv.2109.09658 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Fairness - For Equitable AI in Medical Imaging
3. Universality - For Standardised AI in Medical Imaging
4. Traceability - For Transparent and Dynamic AI in Medical Imaging
5. Usability - For Effective and Beneficial AI in Medical Imaging
6. Robustness - For Reliable AI in Medical Imaging
7. Explainability - For Enhanced Understanding of AI in Medical Imaging
9. Discussion and Conclusion
References

The Cambridge Law Corpus: A Corpus for Legal AI Research / 2309.12269 / ISBN:https://doi.org/10.48550/arXiv.2309.12269 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 The Cambridge Law Corpus
3 Legal and Ethical Considerations
4 Experiments
Acknowledgements
General References
B Example XML case
C Case Outcome Task Description
Cambridge Law Corpus: Datasheet

EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval / 2310.00970 / ISBN:https://doi.org/10.48550/arXiv.2310.00970 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Dataset Construction
5 Experiments
6 Conclusions
Acknowledgments
Appendix

Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities / 2310.08565 / ISBN:https://doi.org/10.48550/arXiv.2310.08565 / Published by ArXiv / on (web) Publishing site
I. Introduction and Motivation
II. AI-Robotics Systems Architecture
III. Survey Approach & Taxonomy
IV. Attack Surfaces
V. Ethical & Legal Concerns
VI. Human-Robot Interaction (HRI) Security Studies
VII. Future Research & Discussion
Acknowledgements
References

If our aim is to build morality into an artificial agent, how might we begin to go about doing so? / 2310.08295 / ISBN:https://doi.org/10.48550/arXiv.2310.08295 / Published by ArXiv / on (web) Publishing site
Abstract
1 The Top-Down Approach Alone Might Be Insufficient
2 Emotion, Sentience and Morality
3 Proposing a Hybrid Approach
4 AI Governance Principles
6 Acknowledgments
References

Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks / 2310.07879 / ISBN:https://doi.org/10.48550/arXiv.2310.07879 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background and Related Work
3 Method
4 Taxonomy of AI Privacy Risks
5 Discussion
6 Conclusion
Acknowledgments
References

ClausewitzGPT Framework: A New Frontier in Theoretical Large Language Model Enhanced Information Operations / 2310.07099 / ISBN:https://doi.org/10.48550/arXiv.2310.07099 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Nation-State Advances in AI-driven Information Operations
Theoretical Impact of LLMs on Information Operations
Mathematical Foundations
Conclusion
References

The AI Incident Database as an Educational Tool to Raise Awareness of AI Harms: A Classroom Exploration of Efficacy, Limitations, & Future Improvements / 2310.06269 / ISBN:https://doi.org/10.48550/arXiv.2310.06269 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Research Design and Methodology
3 Analysis and Findings
4 Discussion
5 Conclusion
Acknowledgements
References
A Consent and Data Collection Processes
C In-class Activity
G Statistical Tests

A Review of the Ethics of Artificial Intelligence and its Applications in the United States / 2310.05751 / ISBN:https://doi.org/10.48550/arXiv.2310.05751 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Literature Review
3. AI Ethical Principles
4. Implementing the Practical Use of Ethical AI Applications
5. Conclusions and Recommendations
References

A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics / 2310.05694 / ISBN:https://doi.org/10.48550/arXiv.2310.05694 / Published by ArXiv / on (web) Publishing site
Abstract
I. INTRODUCTION
II. WHAT LLM S CAN DO FOR HEALTHCARE ? FROM FUNDAMENTAL TASKS TO ADVANCED APPLICATIONS
III. FROM PLM S TO LLM S FOR HEALTHCARE
IV. TRAIN AND USE LLM FOR HEALTHCARE
V. EVALUATION METHOD
VI. IMPROVING FAIRNESS , ACCOUNTABILITY, TRANSPARENCY, AND ETHICS
VII. FUTURE WORK AND CONCLUSION
ACKNOWLEDGMENTS
REFERENCES

STREAM: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models / 2310.05563 / ISBN:https://doi.org/10.48550/arXiv.2310.05563 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 STREAM: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models
3 The applications of STREAM
4 Conclusion and Future Work
References
Competing interests

Regulation and NLP (RegNLP): Taming Large Language Models / 2310.05553 / ISBN:https://doi.org/10.48550/arXiv.2310.05553 / Published by ArXiv / on (web) Publishing site
Abstract
2 Regulation: A Short Introduction
3 LLMs: Risk and Uncertainty
4 Scientific Expertise, Social Media and Regulatory Capture
5 Regulation and NLP (RegNLP): A New Field
6 Conclusion
Limitations
References

Ethics of Artificial Intelligence and Robotics in the Architecture, Engineering, and Construction Industry / 2310.05414 / ISBN:https://doi.org/10.48550/arXiv.2310.05414 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Research Methodology
4. Systematic Review and Scientometric Analysis
5. Ethical Issues of AI and Robotics in AEC Industry
6. Discussion
7. Future Research Direction
References

Commercialized Generative AI: A Critical Study of the Feasibility and Ethics of Generating Native Advertising Using Large Language Models in Conversational Web Search / 2310.04892 / ISBN:https://doi.org/10.48550/arXiv.2310.04892 / Published by ArXiv / on (web) Publishing site
Introduction
Background and Related Work
Evaluation of the Pilot Study
Ethics of GEnerating Native Ads

Compromise in Multilateral Negotiations and the Global Regulation of Artificial Intelligence / 2309.17158 / ISBN:https://doi.org/10.48550/arXiv.2309.17158 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. The practice of multilateral negotiation and the mechanisms of compromises
3. The liberal-sovereigntist multiplicity
4. Towards a compromise: drafting the normative hybridity
5. Text negotiations as normative testing
Notes
Bibliography
Annex 1. Text amendments and ambiguity

Towards A Unified Utilitarian Ethics Framework for Healthcare Artificial Intelligence / 2309.14617 / ISBN:https://doi.org/10.48550/arXiv.2309.14617 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Utilitarian Ethics
Principal Ethics in Healthcare
Method
Results and Discussion
A Unified Utilitarian Ethics Framework
Conclusion
References

Risk of AI in Healthcare: A Comprehensive Literature Review and Study Framework / 2309.14530 / ISBN:https://doi.org/10.48550/arXiv.2309.14530 / Published by ArXiv / on (web) Publishing site
Abstract
3. Clinical Risks
4. Technical Risks
5. Conclusion
References
Appendix

Autonomous Vehicles an overview on system, cyber security, risks, issues, and a way forward / 2309.14213 / ISBN:https://doi.org/10.48550/arXiv.2309.14213 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Autonomous vehicles
4. Traffic Flow prediction in Autonomous vehicles
5. Cybersecurity Risks
6. Risk management
7. Issues
8. Conclusion
9. References

The Return on Investment in AI Ethics: A Holistic Framework / 2309.13057 / ISBN:https://doi.org/10.48550/arXiv.2309.13057 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. AI Ethics
3. Return on Investment (ROI)
4. A Holistic Framework
5. Discussion
6. References

An Evaluation of GPT-4 on the ETHICS Dataset / 2309.10492 / ISBN:https://doi.org/10.48550/arXiv.2309.10492 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Datasets and Methods
3 Results
4 Discussion
References

Who to Trust, How and Why: Untangling AI Ethics Principles, Trustworthiness and Trust / 2309.10318 / ISBN:https://doi.org/10.48550/arXiv.2309.10318 / Published by ArXiv / on (web) Publishing site
Abstract
Trust
Trust and AI Ethics Principles
Trust in AI as Socio-Technical Systems
Conclusion

In Consideration of Indigenous Data Sovereignty: Data Mining as a Colonial Practice / 2309.10215 / ISBN:https://doi.org/10.48550/arXiv.2309.10215 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
4 Methodology
5 Relating Case Studies to Indigenous Data Sovereignty and CARE Principles
7 Conclusions and Recommendations
References

The Glamorisation of Unpaid Labour: AI and its Influencers / 2308.02399 / ISBN:https://doi.org/10.48550/arXiv.2308.02399 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
References

AI & Blockchain as sustainable teaching and learning tools to cope with the 4IR / 2305.01088 / ISBN:https://doi.org/10.48550/arXiv.2305.01088 / Published by ArXiv / on (web) Publishing site
2. AI and blockchain in education: An overview of the benefits and challenges
5. AI-powered assessment and evaluation
6. Blockchain-based decentralized learning networks
7. AI-powered content creation and curation
8. Case studies: AI and blockchain in education
11.References

Toward an Ethics of AI Belief / 2304.14577 / ISBN:https://doi.org/10.48550/arXiv.2304.14577 / Published by ArXiv / on (web) Publishing site
1. Introduction
3. Proposed Novel Topics in an Ethics of AI Belief
4. Nascent Extant Work that Falls Within the Ethics of AI Belief
5. Conclusion
References

Ensuring Trustworthy Medical Artificial Intelligence through Ethical and Philosophical Principles / 2304.11530 / ISBN:https://doi.org/10.48550/arXiv.2304.11530 / Published by ArXiv / on (web) Publishing site
Introduction
Ethical concerns of AI in medicine
Ethical datasets and algorithm development guidelines
Towards solving key ethical challenges in Medical AI
Ethical guidelines for medical AI model deployment
Discussion
Conclusion and future directions
Funding
References

Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineering / 2209.04963 / ISBN:https://doi.org/10.48550/arXiv.2209.04963 / Published by ArXiv / on (web) Publishing site
2 Methodology
3 Governance Patterns
4 Process Patterns
5 Product Patterns
8 Conclusion
References

The Ethics of AI Value Chains / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site
Bibliography
Appendix A: Integrated Inventory of Ethical Concerns, Value Chains Actors, Resourcing Activities, & Sampled Sources

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare / 2309.12325 / ISBN:https://doi.org/10.48550/arXiv.2309.12325 / Published by ArXiv / on (web) Publishing site
INTRODUCTION
METHODS
FUTURE-AI GUIDELINE
DISCUSSION
ACKNOWLEDGMENTS
FUNDING

Language Agents for Detecting Implicit Stereotypes in Text-to-Image Models at Scale / 2310.11778 / ISBN:https://doi.org/10.48550/arXiv.2310.11778 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Agent Design
3 Agent Benchmark
4 Agent Performance
Appendix A Data Details

Specific versus General Principles for Constitutional AI / 2310.13798 / ISBN:https://doi.org/10.48550/arXiv.2310.13798 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 AI feedback on specific problematic AI traits
3 Generalization from a Simple Good for Humanity Principle
4 Reinforcement Learning with Good-for-Humanity Preference Models
5 Related Work
6 Discussion
7 Contribution Statement
C General Prompts for GfH Preference Modeling
G Over-Training on Good for Humanity
H Samples
I Responses on Prompts from PALMS, LaMDA, and InstructGPT

The Self 2.0: How AI-Enhanced Self-Clones Transform Self-Perception and Improve Presentation Skills / 2310.15112 / ISBN:https://doi.org/10.48550/arXiv.2310.15112 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Method
4 Findings
5 Discussion
Acknowledgments
References

Systematic AI Approach for AGI: Addressing Alignment, Energy, and AGI Grand Challenges / 2310.15274 / ISBN:https://doi.org/10.48550/arXiv.2310.15274 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Trifecta of AI Challenges
3 Systematic AI Approach for AGI
4 Systematic AI for Energy Wall
5 System Design for AI Alignment
6 System Insights from the Brain
7 Conclusions
References

AI Alignment and Social Choice: Fundamental Limitations and Policy Implications / 2310.16048 / ISBN:https://doi.org/10.48550/arXiv.2310.16048 / Published by ArXiv / on (web) Publishing site
3 Arrow-Sen Impossibility Theorems for RLHF
4 Implications for AI Governance and Policy
5 Conclusion
References

A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges / 2310.16360 / ISBN:https://doi.org/10.48550/arXiv.2310.16360 / Published by ArXiv / on (web) Publishing site
I. Introduction
IV. Artificial Intelligence Embedded UAV
VI. Review Summary
VII. Conclusion
References
Authors Bios

Unpacking the Ethical Value Alignment in Big Models / 2310.17551 / ISBN:https://doi.org/10.48550/arXiv.2310.17551 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Risks and Ethical Issues of Big Model
3 Investigating the Ethical Values of Large Language Models
4 Equilibrium Alignment: A Prospective Paradigm for Ethical Value Alignmen
References

Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
5 The Epistemic Condition
6 Degree of Responsibility

AI for Open Science: A Multi-Agent Perspective for Ethically Translating Data to Knowledge / 2310.18852 / ISBN:https://doi.org/10.48550/arXiv.2310.18852 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background and Related Work
3 A Formal Language of AI for Open Science
4 Optimizing an Openness Metric in AI for Science
5 Why Openness in AI for Science
6 Conclusion and Future Work
Acknowledgements
References

Artificial Intelligence Ethics Education in Cybersecurity: Challenges and Opportunities: a focus group report / 2311.00903 / ISBN:https://doi.org/10.48550/arXiv.2311.00903 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
AI Ethics in Cybersecurity
Educational Challenges of Teaching AI Ethics in Cybersecurity and Core Ethical Principles
Technical Issues
Learning Challenges
AI tool-specific educational concerns
Broader educational preparedness for work in AI Cybersecurity
Communication skills in cybersecurity and ethics
Conclusion
References

Human participants in AI research: Ethics and transparency in practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Contextual Concerns: Why AI Research Needs its Own Guidelines
III. Ethical Principles for AI Research with Human Participants
IV. Principles in Practice: Guidelines for AI Research with Human Participants
V. Conclusion
Acknowledgments
References
Appendix A Evaluating Current Practices for Human-Participants Research
Appendix B Placing Research Ethics for Human Participans in Historical Context
Appendix C Defining the Scope of Research Participation in AI Research

LLMs grasp morality in concept / 2311.02294 / ISBN:https://doi.org/10.48550/arXiv.2311.02294 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 A General Theory of Meaning
4 The Moral Model
A Supplementary Material
References

Educating for AI Cybersecurity Work and Research: Ethics, Systems Thinking, and Communication Requirements / 2311.04326 / ISBN:https://doi.org/10.48550/arXiv.2311.04326 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Literature Review
Research questions
Conclusions
References

Towards Effective Paraphrasing for Information Disguise / 2311.05018 / ISBN:https://doi.org/10.1007/978-3-031-28238-6_22 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
3 Methodology
4 Evaluation
References

Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness Metrics / 2311.05227 / ISBN:https://doi.org/10.48550/arXiv.2311.05227 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Overview of Kantian Deontology
3 Measuring Fairness Metrics
4 Deontological AI Alignment
5 Aligning with Deontological Principles: Use Cases
6 Conclusion

Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing / 2304.02017 / ISBN:https://doi.org/10.48550/arXiv.2304.02017 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Overview of ChatGPT and its capabilities
3 Transformers and pre-trained language models
4 Applications of ChatGPT in real-world scenarios
5 Advantages of ChatGPT in natural language processing
6 Limitations and potential challenges
7 Ethical considerations when using ChatGPT
11 Conclusion
References

Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies / 2304.07683 / ISBN:https://doi.org/10.48550/arXiv.2304.07683 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Sources of bias in AI
III. Impacts of bias in AI
IV. Mitigation strategies for bias in AI
V. Fairness in AI
VI. Mitigation strategies for fairness in AI
References

Towards ethical multimodal systems / 2304.13765 / ISBN:https://doi.org/10.48550/arXiv.2304.13765 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
3 Crafting an Ethical Dataset
4 A Multimodal Ethics Classifier
5 Conclusions
Acknowledgments and Disclosure of Funding

A Brief History of Prompt: Leveraging Language Models. (Through Advanced Prompting) / 2310.04438 / ISBN:https://doi.org/10.48550/arXiv.2310.04438 / Published by ArXiv / on (web) Publishing site
Abstract
VI. 2015: birth of the transformer
VII. The second wave in 2017: rise of RL
X. 2020-2021: the rise of LLMS
References

Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agents / 2310.15065 / ISBN:https://doi.org/10.48550/arXiv.2310.15065 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related work
4 Findings
5 Discussion
References

She had Cobalt Blue Eyes: Prompt Testing to Create Aligned and Sustainable Language Models / 2310.18333 / ISBN:https://doi.org/10.48550/arXiv.2310.18333 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Works
3 ReFLeCT: Robust, Fair, and Safe LLM Construction Test Suite
4 Empirical Evaluation and Outcomes
5 Conclusion
References

Safety, Trust, and Ethics Considerations for Human-AI Teaming in Aerospace Control / 2311.08943 / ISBN:https://doi.org/10.48550/arXiv.2311.08943 / Published by ArXiv / on (web) Publishing site
III. Safety
IV. Trust
V. Ethics
References

How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Methodology
4 Experiments
References

Prudent Silence or Foolish Babble? Examining Large Language Models' Responses to the Unknown / 2311.09731 / ISBN:https://doi.org/10.48550/arXiv.2311.09731 / Published by ArXiv / on (web) Publishing site
2 UnknownBench: Evaluating LLMs on the Unknown
References
E Prompt Templates
F NEC Question Generation Template

Revolutionizing Customer Interactions: Insights and Challenges in Deploying ChatGPT and Generative Chatbots for FAQs / 2311.09976 / ISBN:https://doi.org/10.48550/arXiv.2311.09976 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Chatbots Background and Scope of Research
3. Chatbot approaches overview: Taxonomy of existing methods
4. ChatGPT
5. Applications
6. Open chanllenges
7. Future Research Directions
8. Conclusion
References

Practical Cybersecurity Ethics: Mapping CyBOK to Ethical Concerns / 2311.10165 / ISBN:https://doi.org/10.48550/arXiv.2311.10165 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background
3 Methodology
4 Findings
5 Discussion
7 Conclusion
References
A Ethics of the cyber security profession: interview guide

First, Do No Harm: Algorithms, AI, and Digital Product Liability Managing Algorithmic Harms Though Liability Law and Market Incentives / 2311.10861 / ISBN:https://doi.org/10.48550/arXiv.2311.10861 / Published by ArXiv / on (web) Publishing site
Bloustein Local and the Center for Urban Policy Research
Executive Summary
Preface
Introduction
The Problem
Why Liability Law?
Harms, Risk, and Liability Practices
Conclusion
Appendix A - What is an Algorithmic Harm? And a Bibliography
Appendix B – Common AI Harms as Described by EPIC10
Appendix C - List of General Harms Created by Digital Products Provided by Claude.AI
Appendix E - A Sampling of References Addressing Liability and Digital Products

Case Repositories: Towards Case-Based Reasoning for AI Alignment / 2311.10934 / ISBN:https://doi.org/10.48550/arXiv.2311.10934 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Proposed Process
3 Related Work and Discussion
Acknowledgments and Disclosure of Funding

Responsible AI Considerations in Text Summarization Research: A Review of Current Practices / 2311.11103 / ISBN:https://doi.org/10.48550/arXiv.2311.11103 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background & Related Work
4 Findings
5 Discussion and Recommendations
6 Conclusion
Acknowledgements
References

Assessing AI Impact Assessments: A Classroom Study / 2311.11193 / ISBN:https://doi.org/10.48550/arXiv.2311.11193 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
3 Study Design
4 Findings
5 Discussion
Acknowledgments and Disclosure of Funding
References
A Overview of AIIA Instruments
C Extended Results

GPT in Data Science: A Practical Exploration of Model Selection / 2311.11516 / ISBN:https://doi.org/10.48550/arXiv.2311.11516 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Background
III. Approach: capturing and representing heuristics behind GPT's decision-making process
IV. Comparative results
V. Conclusion and future work
VI. Future work
Acknowledgment
References

Responsible AI Research Needs Impact Statements Too / 2311.11776 / ISBN:https://doi.org/10.48550/arXiv.2311.11776 / Published by ArXiv / on (web) Publishing site
Requiring adverse impact statements for RAI research is long overdue
Suggestions for More Meaningful Engagement with the Impact of RAI Research
Concluding Reflections

Large Language Models in Education: Vision and Opportunities / 2311.13160 / ISBN:https://doi.org/10.48550/arXiv.2311.13160 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Education and LLMS
III. Key technologies for EDULLMS
IV. LLM-empowered education
V. Key points in LLMSEDU
VI. Challenges and future directions
VII. Conclusion
Acknowledgment
References

The Rise of Creative Machines: Exploring the Impact of Generative AI / 2311.13262 / ISBN:https://doi.org/10.48550/arXiv.2311.13262 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Extent and impact of generative AI
IV. Risks of generative AI
V. Additional thoughts
References

Towards Auditing Large Language Models: Improving Text-based Stereotype Detection / 2311.14126 / ISBN:https://doi.org/10.48550/arXiv.2311.14126 / Published by ArXiv / on (web) Publishing site
Abstract
3 Methodology
4 Results and Discussion
Acknowledgements
References

Ethical Implications of ChatGPT in Higher Education: A Scoping Review / 2311.14378 / ISBN:https://doi.org/10.48550/arXiv.2311.14378 / Published by ArXiv / on (web) Publishing site
Research Method
Results
Conclusion
References

Potential Societal Biases of ChatGPT in Higher Education: A Scoping Review / 2311.14381 / ISBN:https://doi.org/10.48550/arXiv.2311.14381 / Published by ArXiv / on (web) Publishing site
Abstract
INTRODUCTION
OVERVIEW OF SOCIETAL BIASES IN GAI MODELS
ANALYTICAL FRAMEWORK
DISCUSSION
CONCLUSION

RAISE -- Radiology AI Safety, an End-to-end lifecycle approach / 2311.14570 / ISBN:https://doi.org/10.48550/arXiv.2311.14570 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Pre-Deployment phase
3. Production deployment monitoring phase
4. Post-market surveillance phase
Funding/Disclosures
Bibliography

Ethics and Responsible AI Deployment / 2311.14705 / ISBN:https://doi.org/10.48550/arXiv.2311.14705 / Published by ArXiv / on (web) Publishing site
Abstract
2. Case Study of the Bletchley Summit
4. Addressing bias, transparency, and accountability
5. Ethical AI design principles and guidelines
6. The role of AI in decision-making: ethical implications and potential consequences
7. Establishing responsible AI governance and oversight
8. AI in sensitive domains: healthcare, finance, criminal justice, defence, and human resources
9. Discussion on engaging stakeholders: fostering dialogue and collaboration between developers, users, and affected communities.
10. Conclusion
11. References

From deepfake to deep useful: risks and opportunities through a systematic literature review / 2311.15809 / ISBN:https://doi.org/10.48550/arXiv.2311.15809 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Material and methods
5. Conclusion
References

Generative AI and US Intellectual Property Law / 2311.16023 / ISBN:https://doi.org/10.48550/arXiv.2311.16023 / Published by ArXiv / on (web) Publishing site
II. US Patent law
III. US Copyright law
V. Potential harms and mitigation
References

Survey on AI Ethics: A Socio-technical Perspective / 2311.17228 / ISBN:https://doi.org/10.48550/arXiv.2311.17228 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Privacy and data protection
3 Transparency and explainability
4 Fairness and equity
5 Responsiblity, accountability, and regulations
6 Environmental impact
Acknowledgments
References

Deepfakes, Misinformation, and Disinformation in the Era of Frontier AI, Generative AI, and Large AI Models / 2311.17394 / ISBN:https://doi.org/10.48550/arXiv.2311.17394 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Background
III. The rise of large AI models
IV. Societal implications
VI. Cross-platform strategies
VIII. Proposed integrated defense framework
X. Conclusion
Acknowledgement
References

Privacy and Copyright Protection in Generative AI: A Lifecycle Perspective / 2311.18252 / ISBN:https://doi.org/10.48550/arXiv.2311.18252 / Published by ArXiv / on (web) Publishing site
2 Legal Basis of Privacy and Copyright Concerns over Generative AI
3 Mapping Challenges throughout the Data Lifecycle

From Lab to Field: Real-World Evaluation of an AI-Driven Smart Video Solution to Enhance Community Safety / 2312.02078 / ISBN:https://doi.org/10.48550/arXiv.2312.02078 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Related works
Software system features
Community Engagement
System Evaluation and Results
Conclusion
References

Understanding Teacher Perspectives and Experiences after Deployment of AI Literacy Curriculum in Middle-school Classrooms / 2312.04839 / ISBN:https://doi.org/10.48550/arXiv.2312.04839 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Methodology
3 Results
4 Conclusions
Acknowledgements

Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines / 2312.05235 / ISBN:https://doi.org/10.48550/arXiv.2312.05235 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Research questions
4. Method
5. Results
6. Discussion
7. Conclusion
Declarations

Contra generative AI detection in higher education assessments / 2312.05241 / ISBN:https://doi.org/10.48550/arXiv.2312.05241 / Published by ArXiv / on (web) Publishing site
2. The pitfalls in detecting generative AI output
3. Detectors are not useful
4. Teach critical usage of AI
References

Intelligence Primer / 2008.07324 / ISBN:https://doi.org/10.48550/arXiv.2008.07324 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Human intelligence
3 Reasoning
4 Bias, prejudice, and individuality
5 System design of intelligence
6 Measuring intelligence
8 Consciousness
9 Augmenting human intelligence
10 Exceeding human intelligence
11 Control of intelligence
12 Large language models and Generative AI

RE-centric Recommendations for the Development of Trustworthy(er) Autonomous Systems / 2306.01774 / ISBN:https://doi.org/10.48550/arXiv.2306.01774 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related work
3 Methodology
4 Results & analysis
5 Discussion
6 Conclusion & future work
7 Acknowledgement
References

Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site
III. Ethics: a primer
IV. Guidelines for promoting ethical responsibility
V. Implications whit future directions

Control Risk for Potential Misuse of Artificial Intelligence in Science / 2312.06632 / ISBN:https://doi.org/10.48550/arXiv.2312.06632 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Risks of Misuse for Artificial Intelligence in Science
3 Control the Risks of AI Models in Science
4 Call for Responsible AI for Science
5 Discussion
6 Related Works
References
Appendix A Assessing the Risks of AI Misuse in Scientific Research
Appendix B Details of Risks Demonstration in Chemical Science
Appendix D Details of Benchmark Results

Disentangling Perceptions of Offensiveness: Cultural and Moral Correlates / 2312.06861 / ISBN:https://doi.org/10.48550/arXiv.2312.06861 / Published by ArXiv / on (web) Publishing site
Abstract
...
Data Collection
Study 1: Geo-cultural Differences in Offensiveness
Study 2: Moral Foundations of Offensiveness
Study 3: Implications for Responsible AI
General Discussion
Geo-Cultural Factors
Moral Factors
References
A Appendix

The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment / 2312.07086 / ISBN:https://doi.org/10.48550/arXiv.2312.07086 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Literature
Problematizing The View Of GenAI Content As Academic Misconduct
The AI Assessment Scale
Conclusion
References

Culturally Responsive Artificial Intelligence -- Problems, Challenges and Solutions / 2312.08467 / ISBN:https://doi.org/10.48550/arXiv.2312.08467 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
The concept of multiculturalism and its importance
Culturally responsive AI – current landscape
Recommendations
References

Investigating Responsible AI for Scientific Research: An Empirical Study / 2312.09561 / ISBN:https://doi.org/10.48550/arXiv.2312.09561 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Background and motivation
III. Research methodology
IV. Results
V. Discussion
References
Appendix A – Survey Questionnaire
Appendix B – Interview Questionnaire

Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health / 2312.11803 / ISBN:https://doi.org/10.48550/arXiv.2312.11803 / Published by ArXiv / on (web) Publishing site
Abstract
1 Objective
2 Background and significance
3 Materials and methods
4 Results
5 Discussion
7 Acknowledgements
References
A Extended Survey Results
B Extended Guiding Principles
C Full survey questions

Beyond Fairness: Alternative Moral Dimensions for Assessing Algorithms and Designing Systems / 2312.12559 / ISBN:https://doi.org/10.48550/arXiv.2312.12559 / Published by ArXiv / on (web) Publishing site
Abstract
2 The Reign of Algorithmic Fairness
3 Taking a Step Forward
4 Limitations
5 Conclusion
References

Learning Human-like Representations to Enable Learning Human Values / 2312.14106 / ISBN:https://doi.org/10.48550/arXiv.2312.14106 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Problem Formulation
4 Learning Human Morality Judgments
5 Representational Alignment Supports Learning Multiple Human Values
6 Discussion
Acknowledgments and Disclosure of Funding
References

Improving Task Instructions for Data Annotators: How Clear Rules and Higher Pay Increase Performance in Data Annotation in the AI Economy / 2312.14565 / ISBN:https://doi.org/10.48550/arXiv.2312.14565 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Theoretical background and hypotheses
III. Method
IV. Results
V. Discussion
VI. Conclusion
References

Culturally-Attuned Moral Machines: Implicit Learning of Human Value Systems by AI through Inverse Reinforcement Learning / 2312.17479 / ISBN:https://doi.org/10.48550/arXiv.2312.17479 / Published by ArXiv / on (web) Publishing site
Introduction
Experimental Study
Results
Discussion
Acknowledgments
References

Autonomous Threat Hunting: A Future Paradigm for AI-Driven Threat Intelligence / 2401.00286 / ISBN:https://doi.org/10.48550/arXiv.2401.00286 / Published by ArXiv / on (web) Publishing site
1. Introduction
3. Autonomous threat hunting: conceptual framework
4. State-of-the-art AI techniques in autonomous threat hunting
5. Challenges in autonomous threat hunting
7. Evaluation metrics and performance benchmarks
8. Future directions and emerging trends
References

Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. LLMs in cognitive and behavioral psychology
3. LLMs in clinical and counseling psychology
4. LLMs in educational and developmental psychology
5. LLMs in social and cultural psychology
6. LLMs as research tools in psychology
7. Challenges and future directions
8. Conclusion
Acknowledgments

Synthetic Data in AI: Challenges, Applications, and Ethical Implications / 2401.01629 / ISBN:https://doi.org/10.48550/arXiv.2401.01629 / Published by ArXiv / on (web) Publishing site
1. Introduction
3. The usage of synthetic data
References

MULTI-CASE: A Transformer-based Ethics-aware Multimodal Investigative Intelligence Framework / 2401.01955 / ISBN:https://doi.org/10.48550/arXiv.2401.01955 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Related work
III. Methodology: model development
IV. System design
V. Evaluation
VI. Discussion and future work
VII. Conclusion
Acnkowledgments
References

AI Ethics Principles in Practice: Perspectives of Designers and Developers / 2112.07467 / ISBN:https://doi.org/10.48550/arXiv.2112.07467 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Related work
III. Methods
IV. Results
V. Discussion and suggestions
VI. Support mechanisms
VII. Conclusion
References

Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models / 2310.19917 / ISBN:https://doi.org/10.48550/arXiv.2310.19917 / Published by ArXiv / on (web) Publishing site
Abstract
Background and significance
Materials and methods
Results
Discussion
Funding

Resolving Ethics Trade-offs in Implementing Responsible AI / 2401.08103 / ISBN:https://doi.org/10.48550/arXiv.2401.08103 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Approaches for Resolving Trade-offs
III. Discussion and Recommendations
References

Towards Responsible AI in Banking: Addressing Bias for Fair Decision-Making / 2401.08691 / ISBN:https://doi.org/10.48550/arXiv.2401.08691 / Published by ArXiv / on (web) Publishing site
Abstract
Contents / List of figures / List of tables / Acronyms
1 Introduction
I Understanding bias - 2 Bias and moral framework in AI-based decision making
3 Bias on demand: a framework for generating synthetic data with bias
4 Fairness metrics landscape in machine learning
II Mitigating bias - 5 Fairness mitigation
6 FFTree: a flexible tree to mitigate multiple fairness criteria
III Accounting for bias - 7 Addressing fairness in the banking sector
8 Fairview: an evaluative AI support for addressing fairness
9 Towards fairness through time
IV Conclusions
Bibliography

Business and ethical concerns in domestic Conversational Generative AI-empowered multi-robot systems / 2401.09473 / ISBN:https://doi.org/10.48550/arXiv.2401.09473 / Published by ArXiv / on (web) Publishing site
Abstract
2 Background
4 Results
6 Conclusion
References

FAIR Enough How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training? / 2401.11033 / ISBN:https://doi.org/10.48550/arXiv.2401.11033 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 FAIR Data Principles: Theoretical Background and Significance
3 Data Management Challenges in Large Language Models
4 Framework for FAIR Data Principles Integration in LLM Development
References
Appendices

Enabling Global Image Data Sharing in the Life Sciences / 2401.13023 / ISBN:https://doi.org/10.48550/arXiv.2401.13023 / Published by ArXiv / on (web) Publishing site
Abstract
1. Motivation for White Paper
2. Background
3. Use cases representing different image data types and their challenges and status for sharing
4. Towards global image data sharing
Towards Global Image Data Sharing: A to-do list for various stakeholders
References

Beyond principlism: Practical strategies for ethical AI use in research practices / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site
1 The “Triple-Too” problem of AI ethics
2 A shift to user-centered realism in scientific contexts
3 Five specific goals and action-guiding strategies for ethical AI use in research practices
4 Concluding remarks
References

A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations / 2401.17486 / ISBN:https://doi.org/10.48550/arXiv.2401.17486 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related work
3 Methods
4 RAI tool evaluation practices
5 Towards evaluation of RAI tool effectiveness
6 Limitations
7 Conclusion
Acknowledgments
References
A List of RAI tools, with their primary publication
B RAI tools listed by target stage of AI development
C List of publications, with their associated RAI tools
D Summary of themes and codes

Detecting Multimedia Generated by Large AI Models: A Survey / 2402.00045 / ISBN:https://doi.org/10.48550/arXiv.2402.00045 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Detection
4 Tools
5 Discussion
References

Responsible developments and networking research: a reflection beyond a paper ethical statement / 2402.00442 / ISBN:https://doi.org/10.48550/arXiv.2402.00442 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Networking research today
3 Beyond technical dimensions
4 Sense of engagement and responsibility
5 Possible next steps
6 Concluding remarks
References

Generative Artificial Intelligence in Higher Education: Evidence from an Analysis of Institutional Policies and Guidelines / 2402.01659 / ISBN:https://doi.org/10.48550/arXiv.2402.01659 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Related literature
3. Research study
4. Findings
5. Discussion
6. Conclusions, limitations, and future work
References

Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cubeà / 2402.01760 / ISBN:https://doi.org/10.48550/arXiv.2402.01760 / Published by ArXiv / on (web) Publishing site
2. Literature review
3. Methodology
4. Discussion
6. Acknowledgements
References
B. An Example Dialog With Sentiment Analysis

Commercial AI, Conflict, and Moral Responsibility: A theoretical analysis and practical approach to the moral responsibilities associated with dual-use AI technology / 2402.01762 / ISBN:https://doi.org/10.48550/arXiv.2402.01762 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Establishing the novel aspect of AI as a crossover technology
3 Moral and ethical obligations when developing crossover AI technology
4 Recommendations to address threats posed by crossover AI technology
References

(A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice / 2402.01864 / ISBN:https://doi.org/10.48550/arXiv.2402.01864 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related work and our approach
3 Methods: case-based expert deliberation
4 Results
5 Discussion
7 Acknowledgement
References
A Provided AI response strategies and examples
B Workshop participant information

POLARIS: A framework to guide the development of Trustworthy AI systems / 2402.05340 / ISBN:https://doi.org/10.48550/arXiv.2402.05340 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background
3 State of the practice
4 The POLARIS framework
5 POLARIS framework application
7 Conclusion
Acknowledgments
References

Face Recognition: to Deploy or not to Deploy? A Framework for Assessing the Proportional Use of Face Recognition Systems in Real-World Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Background
3. Intervention models from other fields
4. Proposed framework
5. The framework in practice
6. Compliance with International Regulations
7. Conclusions and future work

Ethics in AI through the Practitioner's View: A Grounded Theory Literature Review / 2206.09514 / ISBN:https://doi.org/10.48550/arXiv.2206.09514 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
3 Review Methodology
5 Findings
6 Discussion and Recommendations
A List of Included Studies
C Glossary of Terms
References
Authors

Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist / 2311.02107 / ISBN:https://doi.org/10.48550/arXiv.2311.02107 / Published by ArXiv / on (web) Publishing site
Introduction
Methods
Results
Discussion
Declaration of interests
Acknowledgement
Reference
Appendix

How do machines learn? Evaluating the AIcon2abs method / 2401.07386 / ISBN:https://doi.org/10.48550/arXiv.2401.07386 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Research methodology and text structure
3. AIcon2abs Instructional Unit
4. Results
5. Conclusion
Conflict of interest statement
References

I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench / 2401.17882 / ISBN:https://doi.org/10.48550/arXiv.2401.17882 / Published by ArXiv / on (web) Publishing site
2 Related Work
3 Awareness in LLMs
5 Experiments
References
B Experimental Settings & Results

Mapping the Ethics of Generative AI: A Comprehensive Scoping Review / 2402.08323 / ISBN:https://doi.org/10.48550/arXiv.2402.08323 / Published by ArXiv / on (web) Publishing site
2 Methods
3 Results
4 Discussion
5 Limitations
6 Conclusion
References
Acknowledgements
Appendix C

Taking Training Seriously: Human Guidance and Management-Based Regulation of Artificial Intelligence / 2402.08466 / ISBN:https://doi.org/10.48550/arXiv.2402.08466 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Emerging Management-based AI Regulation
3 Management-based Regulation and Human-Guided Training
4 Techniques of Human-Guided Training
5 Advantages of Human-Guided Training
6 Limitations
References

User Modeling and User Profiling: A Comprehensive Survey / 2402.09660 / ISBN:https://doi.org/10.48550/arXiv.2402.09660 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Analysis of the Terminology
3 Paradigm Shifts and New Trends
4 Current Taxonomy
5 Discussion and Future Research Directions
References

Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence / 2402.09880 / ISBN:https://doi.org/10.48550/arXiv.2402.09880 / Published by ArXiv / on (web) Publishing site
Abstract
II. Background and Related Work
III. Unified Evaluation Framework For LLM Benchmarks
IV. Technological Aspects
V. Processual Elements
VI. Human Dynamics
References

Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications / 2402.12216 / ISBN:https://doi.org/10.48550/arXiv.2402.12216 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 The AIGC Copyright Dilemma: A What-if Analysis
4 Case Study Under the Copyleft
5 Public Perception: A Survey Method
6 Implications and Recommendations
References

Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation / 2402.12590 / ISBN:https://doi.org/10.48550/arXiv.2402.12590 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Emergence of Free-Formed AI Collectives
3. Enhanced Performance of Free-Formed AI Collectives
4. Robustness of Free-Formed AI Collectives Against Risks
5. Open Challenges for Free-Formed AI Collectives
6. Conclusion
References
A. Cocktail Simulation

What if LLMs Have Different World Views: Simulating Alien Civilizations with LLM-based Agents / 2402.13184 / ISBN:https://doi.org/10.48550/arXiv.2402.13184 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 CosmoAgent Simulation Setting
4 CosmoAgent Architecture
7 Results
8 Conclusion
A CosmoAgent Prompt
B Secretary Agent Prompt
References

The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review / 2402.13635 / ISBN:https://doi.org/10.48550/arXiv.2402.13635 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
METRIC-framework for medical training data
Discussion
Methods
References

The European Commitment to Human-Centered Technology: The Integral Role of HCI in the EU AI Act's Success / 2402.14728 / ISBN:https://doi.org/10.48550/arXiv.2402.14728 / Published by ArXiv / on (web) Publishing site
1 The increasing importance of AI
2 The EU AI Act
3 There is no reliable AI regulation without a sound theory of human-AI interaction
4 There is no trustworthy AI without HCI
6 Conclusion: Navigating the future of AI and HCI within the EU AI Act framework
References

Multi-stakeholder Perspective on Responsible Artificial Intelligence and Acceptability in Education / 2402.15027 / ISBN:https://doi.org/10.48550/arXiv.2402.15027 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
3 Materials and Methods
4 Analysis
5 Results
6 Discussion
References
Appendix 1 Scenarios
Appendix 2 Modified psychometric scales

Autonomous Vehicles: Evolution of Artificial Intelligence and Learning Algorithms / 2402.17690 / ISBN:https://doi.org/10.48550/arXiv.2402.17690 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
III. Ethical Considerations and Bias in AI-Driven Software Development for Autonomous Vehicles
IV. AI’S Role in the Emerging Trend of Internet of Things (IOT) Ecosystem for Autonomous Vehicles
V. Review of Existing Research and Use Cases
VI. AI and Learning Algorithms Statistics for Autonomous Vehicles
VII. Conclusion
References
Authors

Envisioning the Applications and Implications of Generative AI for News Media / 2402.18835 / ISBN:https://doi.org/10.48550/arXiv.2402.18835 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 The Suitability of Generative AI for Newsroom Tasks
3 Conclusion
References

FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics / 2402.19071 / ISBN:https://doi.org/10.48550/arXiv.2402.19071 / Published by ArXiv / on (web) Publishing site
Abstract
2. Background
3. Methods
4. Results
5. Discussion
6. Conclusion
References

Guidelines for Integrating Value Sensitive Design in Responsible AI Toolkits / 2403.00145 / ISBN:https://doi.org/10.48550/arXiv.2403.00145 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background and Related Work
3 Methodology
4 Results
5 Discussion
6 Conclusion
Acknowledgments
References
A Survey Questions
B Toolkits Considered for Inclusion

Implications of Regulations on the Use of AI and Generative AI for Human-Centered Responsible Artificial Intelligence / 2403.00148 / ISBN:https://doi.org/10.48550/arXiv.2403.00148 / Published by ArXiv / on (web) Publishing site
1 Motivation & Background
4 Expected Ooutcomes & Next Steps
References

The Minimum Information about CLinical Artificial Intelligence Checklist for Generative Modeling Research (MI-CLAIM-GEN) / 2403.02558 / ISBN:https://doi.org/10.48550/arXiv.2403.02558 / Published by ArXiv / on (web) Publishing site
Abstract
Part 1. Study design
Part 2. A new train-test split for prompt development and few-shot learning
Part 3. Updates to baseline selection
Part 4. Model evaluation
Part 5. Interpretability of generative models
Part 6. End-to-end pipeline replication
Conclusions
Table 1. Updated MI-CLAIM checklist for generative AI clinical studies.
References

Towards an AI-Enhanced Cyber Threat Intelligence Processing Pipeline / 2403.03265 / ISBN:https://doi.org/10.48550/arXiv.2403.03265 / Published by ArXiv / on (web) Publishing site
Abstract
II. Background & Literature Review
III. The AI-Enhanced CTI Processing Pipeline
IV. Challenges and Considerations

A Survey on Human-AI Teaming with Large Pre-Trained Models / 2403.04931 / ISBN:https://doi.org/10.48550/arXiv.2403.04931 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 AI Model Improvements with Human-AI Teaming
3 Effective Human-AI Joint Systems
4 Safe, Secure and Trustworthy AI
5 Applications
References

Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines / 2312.05235 / ISBN:https://doi.org/10.48550/arXiv.2312.05235 / Published by ArXiv / on (web) Publishing site
References

Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness Metrics / 2311.05227 / ISBN:https://doi.org/10.48550/arXiv.2311.05227 / Published by ArXiv / on (web) Publishing site
References

Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance / 2206.11922 / ISBN:https://doi.org/10.48550/arXiv.2206.11922 / Published by ArXiv / on (web) Publishing site
References

How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site
B Baseline Setup
D More Results

Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site
References

AGI Artificial General Intelligence for Education / 2304.12479 / ISBN:https://doi.org/10.48550/arXiv.2304.12479 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. What is AGI
3. The Potentials of AGI in Transforming Future Education
4. Ethical Issues and Concerns
5. Discussion
6. Conclusion
References

Moral Sparks in Social Media Narratives / 2310.19268 / ISBN:https://doi.org/10.48550/arXiv.2310.19268 / Published by ArXiv / on (web) Publishing site
1. Introduction
5. Results
6. Discussion and Conclusion

Responsible Artificial Intelligence: A Structured Literature Review / 2403.06910 / ISBN:https://doi.org/10.48550/arXiv.2403.06910 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Research Methodology
3. Analysis
4. Discussion
6. Conclusion
References

Legally Binding but Unfair? Towards Assessing Fairness of Privacy Policies / 2403.08115 / ISBN:https://doi.org/10.48550/arXiv.2403.08115 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Problem Statement
4 Informational Fairness
6 Ethics and Morality
7 Use Cases and Applications
8 Conclusion
References

Towards a Privacy and Security-Aware Framework for Ethical AI: Guiding the Development and Assessment of AI Systems / 2403.08624 / ISBN:https://doi.org/10.48550/arXiv.2403.08624 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Research Methodology
4 Results of the Systematic Literature Review
5 Towards Privacy- and Security-Aware Framework for Ethical AI
References

Review of Generative AI Methods in Cybersecurity / 2403.08701 / ISBN:https://doi.org/10.48550/arXiv.2403.08701 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
3 Cyber Offense
4 Cyber Defence
5 Implications of Generative AI in Social, Legal, and Ethical Domains
6 Discussion
References

Evaluation Ethics of LLMs in Legal Domain / 2403.11152 / ISBN:https://doi.org/10.48550/arXiv.2403.11152 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Method
4 Experiment
5 Conclusion & Future Work
8 Broad Impact
References

Trust in AI: Progress, Challenges, and Future Directions / 2403.14680 / ISBN:https://doi.org/10.48550/arXiv.2403.14680 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Methodology
3. Findings
4. Discussion
5. Concluding Remarks and Future Directions
Reference

AI Ethics: A Bibliometric Analysis, Critical Issues, and Key Gaps / 2403.14681 / ISBN:https://doi.org/10.48550/arXiv.2403.14681 / Published by ArXiv / on (web) Publishing site
Method
Results
AI Ethics Development Phases Based on Keyword Analysis
Key AI Ethics Issues
Key Gaps
Limitations and Conclusion
Funding
References
Authors bios

Safeguarding Marketing Research: The Generation, Identification, and Mitigation of AI-Fabricated Disinformation / 2403.14706 / ISBN:https://doi.org/10.48550/arXiv.2403.14706 / Published by ArXiv / on (web) Publishing site
Introduction
Methodology
Results
Conclusion
Web Appendix A: Analysis of the Disinformation Manipulations

The Journey to Trustworthy AI- Part 1 Pursuit of Pragmatic Frameworks / 2403.15457 / ISBN:https://doi.org/10.48550/arXiv.2403.15457 / Published by ArXiv / on (web) Publishing site
Abstract
2 Trustworthy AI Too Many Definitions or Lack Thereof?
3 Complexities and Challenges
4 AI Regulation: Current Global Landscape
5 Risk
6 Bias and Fairness
7 Explainable AI as an Enabler of Trustworthy AI
8 Implementation Framework
9 A Few Suggestions for a Viable Path Forward
10 Summary and Next Steps
A Appendix
References

Analyzing Potential Solutions Involving Regulation to Escape Some of AI's Ethical Concerns / 2403.15507 / ISBN:https://doi.org/10.48550/arXiv.2403.15507 / Published by ArXiv / on (web) Publishing site
Introduction
Various AI Ethical Concerns
A Possible Solution to These Concerns With Government Regulation
Feasibility of Government Regulation
References

The Pursuit of Fairness in Artificial Intelligence Models A Survey / 2403.17333 / ISBN:https://doi.org/10.48550/arXiv.2403.17333 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Conceptualizing Fairness and Bias in ML
4 Practical cases of unfairness in real-world setting
5 Ways to mitigate bias and promote Fairness
6 How Users can be affected by unfair ML Systems
7 Challenges and Limitations
Acknowledgments
References

Domain-Specific Evaluation Strategies for AI in Journalism / 2403.17911 / ISBN:https://doi.org/10.48550/arXiv.2403.17911 / Published by ArXiv / on (web) Publishing site
1 Motivation
2 Existing AI Evaluation Approaches
3 Blueprints for AI Evaluation in Journalism
References

Power and Play Investigating License to Critique in Teams AI Ethics Discussions / 2403.19049 / ISBN:https://doi.org/10.48550/arXiv.2403.19049 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction and Related Work
2 Methods
3 RQ1: What Factors Influence Members’ “Licens to Critique” when Discussing AI Ethics with their Team?
4 RQ2: How Do AI Ethics Discussions Unfold while Playing a Game Oriented toward Speculative Critique?
5 Discussion
6 Conclusion
7 Acknowledgments
References

Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness / 2403.20089 / ISBN:https://doi.org/10.48550/arXiv.2403.20089 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Non-discrimination law vs. algorithmic fairness
4 Practical challenges for compliance
References

AI Act and Large Language Models (LLMs): When critical issues and privacy impact require human and ethical oversight / 2404.00600 / ISBN:https://doi.org/10.48550/arXiv.2404.00600 / Published by ArXiv / on (web) Publishing site
5. Human Oversight
6. Large Language Models (LLMs) - Introduction
9. References

Exploring the Nexus of Large Language Models and Legal Systems: A Short Survey / 2404.00990 / ISBN:https://doi.org/10.48550/arXiv.2404.00990 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Applications of Large Language Models in Legal Tasks
3 Fine-Tuned Large Language Models in Various Countries and Regions
References

A Review of Multi-Modal Large Language and Vision Models / 2404.01322 / ISBN:https://doi.org/10.48550/arXiv.2404.01322 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 What is a Language Model?
3 Proprietary vs. Open Source LLMs
4 Specific Large Language Models
5 Vision Models and Multi-Modal Large Language Models
7 Model Evaluation and Benchmarking
8 Conclusions
References

Balancing Progress and Responsibility: A Synthesis of Sustainability Trade-Offs of AI-Based Systems / 2404.03995 / ISBN:https://doi.org/10.48550/arXiv.2404.03995 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Background and Related Work
III. Study Design
IV. Results
VII. Conclusion
References

Designing for Human-Agent Alignment: Understanding what humans want from their agents / 2404.04289 / ISBN:https://doi.org/10.1145/3613905.3650948 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
3 Method
4 Findings
5 Discussion
7 Conclusion
References

Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage / 2404.06077 / ISBN:https://doi.org/10.48550/arXiv.2404.06077 / Published by ArXiv / on (web) Publishing site
I. Introduction
III. Proposed Design: IBIS
IV. Detailed Construction
References

Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Language Model Agents / 2404.06750 / ISBN:https://arxiv.org/abs/2404.06750 / Published by ArXiv / on (web) Publishing site
A Primer
Rebooting Machine Ethics
Language Model Agents in Society
References

Safeguarding Marketing Research: The Generation, Identification, and Mitigation of AI-Fabricated Disinformation / 2403.14706 / ISBN:https://doi.org/10.48550/arXiv.2403.14706 / Published by ArXiv / on (web) Publishing site
Bibliography

The Pursuit of Fairness in Artificial Intelligence Models A Survey / 2403.17333 / ISBN:https://doi.org/10.48550/arXiv.2403.17333 / Published by ArXiv / on (web) Publishing site
A Appendices

A Critical Survey on Fairness Benefits of Explainable AI / 2310.13007 / ISBN:https://doi.org/10.1145/3630106.3658990 / Published by ArXiv / on (web) Publishing site
Abstract
3 Methodology
4 Critical Survey
5 Three Patterns of Critique
6 Conclusion and Outlook
Acknowledgments
References
B References for Archetypal Claims

AI Alignment: A Comprehensive Survey / 2310.19852 / ISBN:https://doi.org/10.48550/arXiv.2310.19852 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Learning from Feedback
3 Learning under Distribution Shift
4 Assurance
5 Governance
6 Conclusion
References

Regulating AI-Based Remote Biometric Identification. Investigating the Public Demand for Bans, Audits, and Public Database Registrations / 2401.13605 / ISBN:https://doi.org/10.48550/arXiv.2401.13605 / Published by ArXiv / on (web) Publishing site
Abstract
3 Remote Biometric Identification and the AI Act
4 Public Opinion on AI Governance
5 Research Questions
6 Results
7 Discussion
8 Conclusion
Conflicts of Interest
References
Appendix

Generative Ghosts: Anticipating Benefits and Risks of AI Afterlives / 2402.01662 / ISBN:https://doi.org/10.48550/arXiv.2402.01662 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Generative Ghosts: A Design Space
4 Benefits and Risks of Generative Ghost
5 Discussion
References

Epistemic Power in AI Ethics Labor: Legitimizing Located Complaints / 2402.08171 / ISBN:https://doi.org/10.1145/3630106.3658973 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Automated Model Cards: Legitimacy via Quantified Objectivity
4 Grey Skin as Technofix: Failures to Lodge Located Complaints
5 Alternative AI Ethics: Space for Embodied Complaints
6 Conclusions: Towards Humble Technical Practices
Acknowledgments
References

On the role of ethics and sustainability in business innovation / 2404.07678 / ISBN:https://doi.org/10.48550/arXiv.2404.07678 / Published by ArXiv / on (web) Publishing site
Ethical considera5ons
Sustainability considera5ons
Recommenda5ons
Conclusion

PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Models / 2404.08699 / ISBN:https://doi.org/10.48550/arXiv.2404.08699 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background and Related Work
5 Conclusion
References
B Instruction Generation Prompts
C GPT Scoring Prompt

Detecting AI Generated Text Based on NLP and Machine Learning Approaches / 2404.10032 / ISBN:https://doi.org/10.48550/arXiv.2404.10032 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Literature Review
III. Proposed Methodology
IV. Results and Discussion
V. Conclusion
References

Debunking Robot Rights Metaphysically, Ethically, and Legally / 2404.10072 / ISBN:https://doi.org/10.48550/arXiv.2404.10072 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
3 The Robots at Issue
4 The Machines Like us Argument: Mistaking the Map for the Territory
5 Embodied Enactive (Post-Cartesian) Perspectives on Cognition
6 Posthumanism
7 The Legal Perspective
8 The Troubling Implications of Legal Rationales for Robot Rights
9 The Enduring Irresponsibility of AI Rights Talk
Notes

Characterizing and modeling harms from interactions with design patterns in AI interfaces / 2404.11370 / ISBN:https://doi.org/10.48550/arXiv.2404.11370 / Published by ArXiv / on (web) Publishing site
3 Scoping Review of Design Patterns, Affordances, and Harms in AI Interfaces
4 DECAI: Design-Enhanced Control of AI Systems
5 Case Studies
6 Discussion
References

Taxonomy to Regulation: A (Geo)Political Taxonomy for AI Risks and Regulatory Measures in the EU AI Act / 2404.11476 / ISBN:https://doi.org/10.48550/arXiv.2404.11476 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 EU Public Policy Analysis
3 A Geo-Political AI Risk Taxonomy
4 European Union Artificial Intelligence Act
5 Conclusion
References

Just Like Me: The Role of Opinions and Personal Experiences in The Perception of Explanations in Subjective Decision-Making / 2404.12558 / ISBN:https://doi.org/10.48550/arXiv.2404.12558 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Method
3 Results
4 Discussin and Implications
5 Limitations
6 Conclusion & Future Work
References

Large Language Model Supply Chain: A Research Agenda / 2404.12736 / ISBN:https://doi.org/10.48550/arXiv.2404.12736 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Definition of LLM Supply Chain
3 LLM Infrastructure
4 LLM Lifecycle
5 Downstream Ecosystem
6 Conclusion
References

The Necessity of AI Audit Standards Boards / 2404.13060 / ISBN:https://doi.org/10.48550/arXiv.2404.13060 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Audit the process, not just the product
3 3 Governance for safety
4 4 Auditing standards body, not standard audits
5 Conclusion
References

Modeling Emotions and Ethics with Large Language Models / 2404.13071 / ISBN:https://doi.org/10.48550/arXiv.2404.13071 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Qualifying and Quantifying Emotions
3 Case Study #1: Linguistic Features of Emotion
4 Qualifying and Quantifying Ethics
5 Concluding Remarks
References

From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap / 2404.13131 / ISBN:https://doi.org/10.1145/3630106.3658951 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Disentangling Replicability of Model Performance Claiim and Replicability of Social Claim
3 How Claim Replicability Helps Bridge the Responsiblity Gap
4 Claim Replicability's Practical Implication
References

A Practical Multilevel Governance Framework for Autonomous and Intelligent Systems / 2404.13719 / ISBN:https://doi.org/10.48550/arXiv.2404.13719 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Comprehensive Governance of Emerging Technologies
III. A Practical Multilevel Governance Framework for AIs
IV. Application of the Framework for the Development of AIs
References

Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis / 2404.13861 / ISBN:https://doi.org/10.48550/arXiv.2404.13861 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Volitional Agency: an Alternative Approach
4 Alternatives to AI as Agent
References

Designing Safe and Engaging AI Experiences for Children: Towards the Definition of Best Practices in UI/UX Design / 2404.14218 / ISBN:https://doi.org/10.48550/arXiv.2404.14218 / Published by ArXiv / on (web) Publishing site
2 Towards Ethical and Engaging AI Interfaces for Children: a Comprehensive Framework
4 Metrics for Assessing Trustworthiness, Reliability, and Safety in Human-AI Interaction
6 Acknowledgement
References

AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance / 2404.14660 / ISBN:https://doi.org/10.48550/arXiv.2404.14660 / Published by ArXiv / on (web) Publishing site
Abstract
1 Technical assessments require an AI expert to complete — and we don’t have enough experts
2 Procurement Loopholes Exist
3 Substantive and Procedural Transparency are Necessary for Deploying Effective and Ethical AI systems
4 Building Towards Better Governance of Government AI

Who Followed the Blueprint? Analyzing the Responses of U.S. Federal Agencies to the Blueprint for an AI Bill of Rights / 2404.19076 / ISBN:https://doi.org/10.48550/arXiv.2404.19076 / Published by ArXiv / on (web) Publishing site
Introduction
Findings
Conclusion
Acknowledgments
References

Fairness in AI: challenges in bridging the gap between algorithms and law / 2404.19371 / ISBN:https://doi.org/10.48550/arXiv.2404.19371 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Discrimination in Law
III. Prevalent Algorithmic Fairness Definitions
IV. Criteria for the Selection of Fairness Methods
V. Discussion
References

War Elephants: Rethinking Combat AI and Human Oversight / 2404.19573 / ISBN:https://doi.org/10.48550/arXiv.2404.19573 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background
3 Lessons from History: War Elephants
4 Discussion
5 Conclusions
References

Not a Swiss Army Knife: Academics' Perceptions of Trade-Offs Around Generative Artificial Intelligence Use / 2405.00995 / ISBN:https://doi.org/10.48550/arXiv.2405.00995 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Method
4 Findings
5 Discussion
6 Limitations and Future Research
7 Conclusion
References

Towards an Ethical and Inclusive Implementation of Artificial Intelligence in Organizations: A Multidimensional Framework / 2405.01697 / ISBN:https://doi.org/10.48550/arXiv.2405.01697 / Published by ArXiv / on (web) Publishing site
Abstract
1 Technocriticism and Key Actors in the Age of AI
2 How can organizations participate
3 Four Pillars for Implementing an Ethical Framework in Organizations
4 Conclusions

A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law / 2405.01769 / ISBN:https://doi.org/10.48550/arXiv.2405.01769 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Surveys
3 Finance
4 Medicine and Healthcare
5 Law
6 Ethics
7 Conclusion

AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research / 2405.01859 / ISBN:https://doi.org/10.48550/arXiv.2405.01859 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Current State of AWS
3. AWS Proliferation and Threats to Academic Research
4. Policy Recommendations
References

Responsible AI: Portraits with Intelligent Bibliometrics / 2405.02846 / ISBN:https://doi.org/10.48550/arXiv.2405.02846 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
III. Data and Methodology
IV. Bibliometric Portraits of Responsible AI
V. Discussion and Conclusions
Acknowledgment
References
Authors

Exploring the Potential of the Large Language Models (LLMs) in Identifying Misleading News Headlines / 2405.03153 / ISBN:https://doi.org/10.48550/arXiv.2405.03153 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
5 Discussion
References

Organizing a Society of Language Models: Structures and Mechanisms for Enhanced Collective Intelligence / 2405.03825 / ISBN:https://doi.org/10.48550/arXiv.2405.03825 / Published by ArXiv / on (web) Publishing site
4 Interaction Mechanisms
6 Unified Legal Framework
References

A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI / 2405.04333 / ISBN:https://doi.org/10.48550/arXiv.2405.04333 / Published by ArXiv / on (web) Publishing site
Acknowledgements
Glossary of Terms
Executive Summary
1. Introduction
2. Methodology
3. A Spectrum of Scenarios of Open Data for Generative AI
4. Open Data Requirements And Diagnostic
5. Recommendations for Advancing Open Data in Generative AI
Appendix

Guiding the Way: A Comprehensive Examination of AI Guidelines in Global Media / 2405.04706 / ISBN:https://doi.org/10.48550/arXiv.2405.04706 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Theoretical Framework
3 Data and Methods
4 Results
5 Discussion and conclusions
References

Trustworthy AI-Generative Content in Intelligent 6G Network: Adversarial, Privacy, and Fairness / 2405.05930 / ISBN:https://doi.org/10.48550/arXiv.2405.05930 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Trustworthy AIGC in 6G Network
III. Adversarial of AIGC Models in 6G Network
V. Fairness of AIGC in 6G Network
VIII. Conclusion
References

RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical Roles / 2307.15158 / ISBN:https://doi.org/10.48550/arXiv.2307.15158 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Author Positionality Statement
4 Method for Generating Responsible AI Guidelines
5 Evaluation of the 22 Responsible AI Guidelines
6 Discussion
7 Conclusion
References
B Mapping Guidelines with EU AI Act Articles

Redefining Qualitative Analysis in the AI Era: Utilizing ChatGPT for Efficient Thematic Analysis / 2309.10771 / ISBN:https://doi.org/10.48550/arXiv.2309.10771 / on (web) Publishing site
Abstract
2 Related Work
3 Methods
4 Users’ Experiences and Challenges with ChatGPT
5 Analyses of the Design Process
6 User’s Attitude on ChatGPT’s Qualitative Analysis Assistance: from no to yes
7 Discussion
8 Limitations and Future Work
References

XXAI: Towards eXplicitly eXplainable Artificial Intelligence / 2401.03093 / ISBN:https://doi.org/10.48550/arXiv.2401.03093 / Published by ArXiv / on (web) Publishing site
1. Introduction
3. Overcoming the barriers to widespread use of symbolic AI
4. Discussion of the problems of symbolic AI and ways to overcome them
References

Should agentic conversational AI change how we think about ethics? Characterising an interactional ethics centred on respect / 2401.09082 / ISBN:https://doi.org/10.48550/arXiv.2401.09082 / Published by ArXiv / on (web) Publishing site
Evaluating a system as a social actor
Social-interactional harms
Design implications for LLM agents
Informing existing HCI approaches
References

Unsocial Intelligence: an Investigation of the Assumptions of AGI Discourse / 2401.13142 / ISBN:https://doi.org/10.48550/arXiv.2401.13142 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Between Human Intelligence and Technology: AGI’s Dual Value-Laden Pedigrees
3 The Motley Choices of AGI Discourse
4 Towards Contextualized, Politically Legitimate, and Social Intelligence
5 Conclusion: Politically Legitimate Intelligence
References

Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators / 2402.01708 / ISBN:https://doi.org/10.48550/arXiv.2402.01708 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
4 Research Approach
6 Taxonomy of Harms
7 Discussion
8 Conclusion
References
A Appendix

Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback / 2404.10271 / ISBN:https://doi.org/10.48550/arXiv.2404.10271 / Published by ArXiv / on (web) Publishing site
1. Introduction
4. Who Provides the Human Feedback?
5. What Is the Format of Human Feedback?
7. Which Traditional Social-Choice-Theoretic Concepts Are Most Relevant?
10. Conclusion
Impact Statement
Acknowledgements
References

A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs) / 2405.03066 / ISBN:https://doi.org/10.48550/arXiv.2405.03066 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Materials
3 Results
4 Discussion
References

Integrating Emotional and Linguistic Models for Ethical Compliance in Large Language Models / 2405.07076 / ISBN:https://doi.org/10.48550/arXiv.2405.07076 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Quantitative Models of Emotions, Behaviors, and Ethics
4 Pilot Studies
References
Appendix S: Multiple Adversarial LLMs
Appendix D: Complex Emotions

Using ChatGPT for Thematic Analysis / 2405.08828 / ISBN:https://doi.org/10.48550/arXiv.2405.08828 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Coding in Thematic Analysis: Manual vs GPT-driven Approaches
3 Pilot-testing: UN Policy Documents Thematic Analysis Supported by GPT
4 Validation Using Topic Modeling
5 Discussion and Limitations
6 OpenAI Updates on Policies and Model Capabilities: Implications for Thematic Analysis
7 Conclusion
8 Acknowledgments
9 Appendix
References

When AI Eats Itself: On the Caveats of Data Pollution in the Era of Generative AI / 2405.09597 / ISBN:https://doi.org/10.48550/arXiv.2405.09597 / Published by ArXiv / on (web) Publishing site
2 RQ1: What Happens When AI Eats Itself ?
3 RQ2: What Technical Strategies Can Be Employed to Mitigate the Negative Consequences of AI Autophagy?
4 RQ3: Which Regulatory Strategies Can Be Employed to Address These Negative Consequences?
6 Ethical Disclaimer and Acknowledgements
7 Acknowledgements

Cyber Risks of Machine Translation Critical Errors : Arabic Mental Health Tweets as a Case Study / 2405.11668 / ISBN:https://doi.org/10.48550/arXiv.2405.11668 / Published by ArXiv / on (web) Publishing site
2.MT Critical Errors
3. Data Compiling and Annotation
5.Quality Metrics Performance
6. Conclusion
7. Bibliographical References

The Narrow Depth and Breadth of Corporate Responsible AI Research / 2405.12193 / ISBN:https://doi.org/10.48550/arXiv.2405.12193 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Literature on Industry’s Engagement in Responsible AI Research
3 Motivations for Industry to Engage in Responsible AI Research
4 The Narrow Depth of Industry’s Responsible AI Research
5 The Narrow Breadth of Industry’s Responsible AI Research
6 Limited Adoption of Responsible AI Research in Commercialization: Patent Citation Analysis
7 Discussion
References
S1 Additional Analyses on Engagement Analysis
S2 Additional Analyses on Linguistic Analysis

Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems / 2405.13191 / ISBN:https://doi.org/10.48550/arXiv.2405.13191 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 The Audit Procedure
4 Conducting the Pilots
References
C The Risk Assessment Database

A Comprehensive Overview of Large Language Models (LLMs) for Cyber Defences: Opportunities and Directions / 2405.14487 / ISBN:https://doi.org/10.48550/arXiv.2405.14487 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Threat Intelligence
III. Vulnerability Assessment
IV. Network Security
VI. Awareness
VII. Cyber Security Operations Automation
IX. Challenges and Open Problems
References

Towards Clinical AI Fairness: Filling Gaps in the Puzzle / 2405.17921 / ISBN:https://doi.org/10.48550/arXiv.2405.17921 / Published by ArXiv / on (web) Publishing site
Abstract
Main
Results
Methods in clinical AI fairness research
Discussion
Methods
Acknowledgments
Reference
Additional material

The ethical situation of DALL-E 2 / 2405.19176 / ISBN:https://doi.org/10.48550/arXiv.2405.19176 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Understanding what can DALL-E 2 actually do
3 Current and potential future use of it
4 Following the RRI, (Responsible research innovation) principles
5 Technology and society, a complex relationship
6 Technological mediation
7 Conclusion

The Future of Child Development in the AI Era. Cross-Disciplinary Perspectives Between AI and Child Development Experts / 2405.19275 / ISBN:https://doi.org/10.48550/arXiv.2405.19275 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Anticipated AI Use for Children
3. Discussion
4. Conclusion
Bibliography
Appendix 1: Experts Consulted & Acknowledgements

Using Large Language Models for Humanitarian Frontline Negotiation: Opportunities and Considerations / 2405.20195 / ISBN:https://doi.org/10.48550/arXiv.2405.20195 / Published by ArXiv / on (web) Publishing site
Abstract
2. Related Work
5. Interview Results: Opportunities and Concerns of Using LLMs in the Frontline
6. Discussion
References
A. Appendix

The AI Alignment Paradox / 2405.20806 / ISBN:https://doi.org/10.48550/arXiv.2405.20806 / Published by ArXiv / on (web) Publishing site
Paper
Acknowledgments

Responsible AI for Earth Observation / 2405.20868 / ISBN:https://doi.org/10.48550/arXiv.2405.20868 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Mitigating (Unfair) Bias
3 Secure AI in EO: Focusing on Defense Mechanisms, Uncertainty Modeling and Explainability
4 Geo-Privacy and Privacy-preserving Measures
5 Maintaining Scientific Excellence, Open Data, and Guiding AI Usage Based on Ethical Principles in EO
6 AI&EO for Social Good
7 Responsible AI Integration in Business Innovation and Sustainability
8 Conclusions, Remarks and Future Directions
References

Gender Bias Detection in Court Decisions: A Brazilian Case Study / 2406.00393 / ISBN:https://doi.org/10.48550/arXiv.2406.00393 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Framework
4 Discussion
5 Final Remarks
Ethics Statement
Acknowledgments
References
A DVC Dataset: Domestic Violence Cases
C Biases

Transforming Computer Security and Public Trust Through the Exploration of Fine-Tuning Large Language Models / 2406.00628 / ISBN:https://doi.org/10.48550/arXiv.2406.00628 / Published by ArXiv / on (web) Publishing site
2 Background, Foundational Studies, and Discussion:
3 Experimental Design, Overview, and Discussion
4 Comparative Analysis of Pre-Trained Models.
5 Discussion and further research

How Ethical Should AI Be? How AI Alignment Shapes the Risk Preferences of LLMs / 2406.01168 / ISBN:https://doi.org/10.48550/arXiv.2406.01168 / Published by ArXiv / on (web) Publishing site
Introduction
I. Description of Method/Empirical Design
II. Risk Characteristics of LLMs
III. Impact of Alignment on LLMs’ Risk Preferences
IV. Impact of Alignments on Corporate Investment Forecasts
V. Robustness: Transcript Readability and Investment Score Predictability
VI. Conclusions
References
Figures and tables

Evaluating AI fairness in credit scoring with the BRIO tool / 2406.03292 / ISBN:https://doi.org/10.48550/arXiv.2406.03292 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Preliminary Analysis
3 ML model construction
5 Risk assessment in BRIO
7 Revenue analysis
8 Conclusions
References

Promoting Fairness and Diversity in Speech Datasets for Mental Health and Neurological Disorders Research / 2406.04116 / ISBN:https://doi.org/10.48550/arXiv.2406.04116 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. A Case Study on DAIC-WoZ Depression Research
3. Related Work
4. Desiderata
5. Methodology
6. Discussion
7. Conclusions
Acknowledgments
References

MoralBench: Moral Evaluation of LLMs / 2406.04428 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Benchmark and Method
4 Experiments
References
Appendix

Can Prompt Modifiers Control Bias? A Comparative Analysis of Text-to-Image Generative Models / 2406.05602 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Related Work
5. Results
6. Discussion
7. Conclusion
References
Can Prompt Modifiers Control Bias? A Comparative Analysis of Text-to-Image Generative Models

Deception Analysis with Artificial Intelligence: An Interdisciplinary Perspective / 2406.05724 / ISBN:https://doi.org/10.48550/arXiv.2406.05724 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Theories and Components of Deception
3 Reductionism & Previous Research in Deceptive AI
4 DAMAS: A MAS Framework for Deception Analysis
5 Conclusion
References

The Impact of AI on Academic Research and Publishing / 2406.06009 / Published by ArXiv / on (web) Publishing site
Introduction
Ethics of AI for Writing Papers
AI in Editorial Processes
Conclusion
References

An Empirical Design Justice Approach to Identifying Ethical Considerations in the Intersection of Large Language Models and Social Robotics / 2406.06400 / ISBN:https://doi.org/10.48550/arXiv.2406.06400 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Theoretical Background
3 Methodology
4 Findings
5 Discussion
Statements and Declarations
References
Appendix A: Interview questions

The Ethics of Interaction: Mitigating Security Threats in LLMs / 2401.12273 / ISBN:https://doi.org/10.48550/arXiv.2401.12273 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Why Ethics Matter in LLM Attacks?
5 Preemptive Ethical Measures
6 Ethical Response to LLM Attacks

Global AI Governance in Healthcare: A Cross-Jurisdictional Regulatory Analysis / 2406.08695 / ISBN:https://doi.org/10.48550/arXiv.2406.08695 / Published by ArXiv / on (web) Publishing site
1 Introduction
4 Global Regulatory Landscape of AI
5 Generative AI: The New Frontier
References
A Supplemental Tables

Fair by design: A sociotechnical approach to justifying the fairness of AI-enabled systems across the lifecycle / 2406.09029 / ISBN:https://doi.org/10.48550/arXiv.2406.09029 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Fairness and AI
3 Assuring fairness across the AI lifecycle
4 Assuring AI fairness in healthcare
References

Some things never change: how far generative AI can really change software engineering practice / 2406.09725 / ISBN:https://doi.org/10.48550/arXiv.2406.09725 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background and related work
3 Methodology
4 Results
5 Limitations
6 Conclusions and future work
ACKNOWLEDGMENTS
REFERENCES

Federated Learning driven Large Language Models for Swarm Intelligence: A Survey / 2406.09831 / ISBN:https://doi.org/10.48550/arXiv.2406.09831 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Foundations and Integration of SI and LLM
III. Federated LLMs for Smarm Intelligence
IV. Learned Lessons and Open Challenges
References

Applications of Generative AI in Healthcare: algorithmic, ethical, legal and societal considerations / 2406.10632 / ISBN:https://doi.org/10.48550/arXiv.2406.10632 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Selection of application
III. Analysis
References
Aappendix A Societal aspects
Appendix B Legal aspects
Appendix C Algorithmic / technical aspects

Justice in Healthcare Artificial Intelligence in Africa / 2406.10653 / ISBN:https://doi.org/10.48550/arXiv.2406.10653 / Published by ArXiv / on (web) Publishing site
Introduction
3. Ensuring Equitable Access to AI Technologies
4. Prioritizing the Common Good Over Corporate Greed
5. Promoting Global Solidarity
7. Addressing Bias and Enforcing Fairness
Conclusion
References

Conversational Agents as Catalysts for Critical Thinking: Challenging Design Fixation in Group Design / 2406.11125 / ISBN:https://doi.org/10.48550/arXiv.2406.11125 / Published by ArXiv / on (web) Publishing site
Abstract
1 INTRODUCTION
2 BEYOND RECOMMENDATIONS: ENHANCING CRITICAL THINKING WITH GENERATIVE AI
4 POTENTIAL SCENARIO AND APPLICATIONS OF CONVERSATIONAL AGENTS IN GROUP DESIGN PROCESS
5 BALANCING CRITICAL THINKING WITH DESIGNER SATISFACTION AND MOTIVATION
6 POTENTIAL DESIGN CONSIDERATIONS
REFERENCES

Current state of LLM Risks and AI Guardrails / 2406.12934 / ISBN:https://doi.org/10.48550/arXiv.2406.12934 / Published by ArXiv / on (web) Publishing site
Abstract
2 Large Language Model Risks
3 Strategies in Securing Large Language models
References

Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Health / 2406.13659 / ISBN:https://doi.org/10.48550/arXiv.2406.13659 / Published by ArXiv / on (web) Publishing site
Abstract
I. INTRODUCTION
II. RECENT ADVANCEMENTS IN LARGE LANGUAGE MODELS
III. CASE STUDIES : APPLICATIONS OF LLM S IN PATIENT ENGAGEMENT
IV. DISCUSSION AND F UTURE D IRECTIONS
V. CONCLUSION
ACKNOWLEDGMENTS
REFERENCES

Documenting Ethical Considerations in Open Source AI Models / 2406.18071 / ISBN:https://doi.org/10.48550/arXiv.2406.18071 / Published by ArXiv / on (web) Publishing site
1 INTRODUCTION
2 RELATED WORK
4 RESULTS
5 DISCUSSION AND IMPLICATIONS
8 ACKNOWLEDGEMENTS
REFERENCES

AI Alignment through Reinforcement Learning from Human Feedback? Contradictions and Limitations / 2406.18346 / ISBN:https://doi.org/10.48550/arXiv.2406.18346 / Published by ArXiv / on (web) Publishing site
3 Limitations of RLxF
4 The Internal Tensions and Ethical Issues in RLxF
5 Rebooting Safety and Alignment: Integrating AI Ethics and System Safety
Acknowledgements

A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics / 2406.18812 / ISBN:https://doi.org/10.48550/arXiv.2406.18812 / Published by ArXiv / on (web) Publishing site
I. INTRODUCTION AND MOTIVATION
II. BACKGROUND
III. ATTACKS ON DT-INTEGRATED AI ROBOTS
IV. DT-INTEGRATED ROBOTICS DESIGN CONSIDERATIONS AND DISCUSSION
V. CONCLUSION
ACKNOWLEDGEMENTS
REFERENCES

Staying vigilant in the Age of AI: From content generation to content authentication / 2407.00922 / ISBN:https://doi.org/10.48550/arXiv.2407.00922 / Published by ArXiv / on (web) Publishing site
Introduction
Art Practice: Human Reactions to Synthetic Fake Content
Emphasizing Reasoning Over Detection
Prospective Usage: Assessing Veracity in Everyday Content
References

SecGenAI: Enhancing Security of Cloud-based Generative AI Applications within Australian Critical Technologies of National Interest / 2407.01110 / ISBN:https://doi.org/10.48550/arXiv.2407.01110 / Published by ArXiv / on (web) Publishing site
Abstract
I. INTRODUCTION
II. UNDERSTANDING GENAI SECURITY
IV. SECGENAI FRAMEWORK REQUIREMENTS SPECIFICATIONS
V. DISCUSSIONS AND RECOMMENDATIONS
VI. CONCLUSION
VII. ACKNOWLEDGEMENTS
REFERENCES

Artificial intelligence, rationalization, and the limits of control in the public sector: the case of tax policy optimization / 2407.05336 / ISBN:https://doi.org/10.48550/arXiv.2407.05336 / Published by ArXiv / on (web) Publishing site
Abstract
2. Artificial intelligence as Weberian rationalization
3. Bureaucratization, tax policy, and equality
5. Freedom, equality, and self-determination in the iron cage
6. Conclusion

A Blueprint for Auditing Generative AI / 2407.05338 / ISBN:https://doi.org/10.48550/arXiv.2407.05338 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Why audit generative AI systems?
3 How to audit generative AI systems?
4 Governance audits
5 Model audits
6 Application audits
7 Clarifications and limitations
8 Conclusion
Bibliography

Challenges and Best Practices in Corporate AI Governance:Lessons from the Biopharmaceutical Industry / 2407.05339 / ISBN:https://doi.org/10.48550/arXiv.2407.05339 / Published by ArXiv / on (web) Publishing site
1 Introduction | The need for corporate AI governance
2 Case study | AstraZeneca’s AI governance journey
4 Discussion | Best practices and lessons learned
5 Concluding remarks | Upfront investments vs. long-term benefits
6 References
7 Conflict of Interest

Operationalising AI governance through ethics-based auditing: An industry case study / 2407.06232 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. The need to operationalise AI governance
3. AstraZeneca and AI governance
5. Methodology: An industry case study
6. Lessons learned from AstraZeneca’s 2021 AI audit
7. Limitations
8. Conclusions
REFERENCES
APPENDIX 1

Auditing of AI: Legal, Ethical and Technical Approaches / 2407.06235 / Published by ArXiv / on (web) Publishing site
Abstract
2 The evolution of auditing as a governance mechanism
3 The need to audit AI systems – a confluence of top-down and bottom-up pressures
4 Auditing of AI’s multidisciplinary foundations
5 In this topical collection
6 Concluding remarks
References

Why should we ever automate moral decision making? / 2407.07671 / ISBN:https://doi.org/10.48550/arXiv.2407.07671 / Published by ArXiv / on (web) Publishing site
2 Reasons for automated moral decision making

Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models / 2310.19917 / ISBN:https://doi.org/10.48550/arXiv.2310.19917 / Published by ArXiv / on (web) Publishing site
References

Potential Societal Biases of ChatGPT in Higher Education: A Scoping Review / 2311.14381 / ISBN:https://doi.org/10.48550/arXiv.2311.14381 / Published by ArXiv / on (web) Publishing site
REFERENCES

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare / 2309.12325 / ISBN:https://doi.org/10.48550/arXiv.2309.12325 / Published by ArXiv / on (web) Publishing site
REFERENCES:
Table 2

Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? / 2308.15399 / ISBN:https://doi.org/10.48550/arXiv.2308.15399 / Published by ArXiv / on (web) Publishing site
B Details of Instructions

PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Models / 2404.08699 / ISBN:https://doi.org/10.48550/arXiv.2404.08699 / Published by ArXiv / on (web) Publishing site
D Negative Sample Generation Prompts

Bridging the Global Divide in AI Regulation: A Proposal for a Contextual, Coherent, and Commensurable Framework / 2303.11196 / ISBN:https://doi.org/10.48550/arXiv.2303.11196 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Global Divide in AI Regulation: Horizontally. Context-Specific
III. Striking a Balance Betweeen the Two Approaches
IV. Proposing an Alternative 3C Framework

CogErgLLM: Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics / 2407.02885 / ISBN:https://doi.org/10.48550/arXiv.2407.02885 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
3 Conceptual Foundations
4 Design Framework
5 Case Studies
6 Discussion

Past, Present, and Future: A Survey of The Evolution of Affective Robotics For Well-being / 2407.02957 / ISBN:https://doi.org/10.48550/arXiv.2407.02957 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
III. Method
IV. Evolution of Affective Robots for Well-Being
V. 10 Years of Affectivbe Robotics
VI. Future Opportunities in Affective Robotivs for Well-Being
VII. Conclusion
Acknowledgment
References
Authors Bios

With Great Power Comes Great Responsibility: The Role of Software Engineers / 2407.08823 / ISBN:https://doi.org/10.48550/arXiv.2407.08823 / Published by ArXiv / on (web) Publishing site
2 Background and Related Work
3 Future Research Challenges
References

Have We Reached AGI? Comparing ChatGPT, Claude, and Gemini to Human Literacy and Education Benchmarks / 2407.09573 / ISBN:https://doi.org/10.48550/arXiv.2407.09573 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Literature Review
3 Methodology
4 Data Analysis and Results
5 Discussion
6 Conclusion
References

Generative AI for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations / 2407.11054 / ISBN:https://doi.org/10.48550/arXiv.2407.11054 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
A brief history of AI and generative AI
Applications of generative AI in literature reviews and evidence synthesis
Applications of generative AI to real-world evidence (RWE):
Applications of generative AI to health economic modeling
Limitations of generative AI in HTA applications
Policy landscape
Conclusion
Appendices
References

Thorns and Algorithms: Navigating Generative AI Challenges Inspired by Giraffes and Acacias / 2407.11360 / ISBN:https://doi.org/10.48550/arXiv.2407.11360 / Published by ArXiv / on (web) Publishing site
2 Study Methodology: Narrative Review
3 Giraffe and Acacia: Reciprocal Adaptations and Shaping
4 Generative AI and Humans: Risks and Mitigation
7 Recommendations: Fixing Gen AI’s Value Alignment
References

Prioritizing High-Consequence Biological Capabilities in Evaluations of Artificial Intelligence Models / 2407.13059 / ISBN:https://doi.org/10.48550/arXiv.2407.13059 / Published by ArXiv / on (web) Publishing site
Introduction
Proposed Approach to Determining High-Consequence Biological Capabilities of Concern
References

Report on the Conference on Ethical and Responsible Design in the National AI Institutes: A Summary of Challenges / 2407.13926 / ISBN:https://doi.org/10.48550/arXiv.2407.13926 / Published by ArXiv / on (web) Publishing site
Introduction
1. Organizing the National AI Institutes for Ethical and Responsible Design
2. Ethics Frameworks
3. AI Institutes and Society
4. Coordination between AI Institutes

Assurance of AI Systems From a Dependability Perspective / 2407.13948 / ISBN:https://doi.org/10.48550/arXiv.2407.13948 / Published by ArXiv / on (web) Publishing site
1 Introduction: Assurance for Traditional Systems
2 Assurance for Systems Extended with AI and ML
3 Assurance of AI Systems for Specific Functions
4 Assurance for General-Purpose AI
5 Assurance and Alignment for AGI
6 Summary and Conclusion
References

Open Artificial Knowledge / 2407.14371 / ISBN:https://doi.org/10.48550/arXiv.2407.14371 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Key Challenges of Artificial Data
6. Conclusion and Future Work
References
Appendices

Honest Computing: Achieving demonstrable data lineage and provenance for driving data and process-sensitive policies / 2407.14390 / ISBN:https://doi.org/10.48550/arXiv.2407.14390 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Threat Model for Honest Computing
3. Honest Computing reference specifications
4. Discussion
5. Conclusion
References

RogueGPT: dis-ethical tuning transforms ChatGPT4 into a Rogue AI in 158 Words / 2407.15009 / ISBN:https://doi.org/10.48550/arXiv.2407.15009 / Published by ArXiv / on (web) Publishing site
III. Methodology
IV. Results
V. Benchmarking with Chat GPT4 Default Interface
VI. Discussion
VII. Conclusion
References

Nudging Using Autonomous Agents: Risks and Ethical Considerations / 2407.16362 / ISBN:https://doi.org/10.48550/arXiv.2407.16362 / Published by ArXiv / on (web) Publishing site
2 Technology Mediated Nudging
4 Ethical Considerations
5 Principles for the Nudge Lifecycle
6 Conclusion
References

Mapping the individual, social, and biospheric impacts of Foundation Models / 2407.17129 / ISBN:https://doi.org/10.48550/arXiv.2407.17129 / Published by ArXiv / on (web) Publishing site
1 Introduction
4 Mapping Individual, Social, and Biospheric Impacts of Foundation Models
5 Discussion: Grappling with the Scale and Interconnectedness of Foundation Models
Acknowledgments
References
A Appendix

Navigating the United States Legislative Landscape on Voice Privacy: Existing Laws, Proposed Bills, Protection for Children, and Synthetic Data for AI / 2407.19677 / ISBN:https://doi.org/10.48550/arXiv.2407.19677 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. American Privacy Rights Act of 2024
6. Conclusion

Interactive embodied evolution for socially adept Artificial General Creatures / 2407.21357 / ISBN:https://doi.org/10.48550/arXiv.2407.21357 / Published by ArXiv / on (web) Publishing site
Expected impacts

Exploring the Role of Social Support when Integrating Generative AI into Small Business Workflows / 2407.21404 / ISBN:https://doi.org/10.48550/arXiv.2407.21404 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Methodology
4 Findings
5 Limitations
6 Discussion and Future Work
7 Conclusion
References
A Example Storyboards

Deepfake Media Forensics: State of the Art and Challenges Ahead / 2408.00388 / ISBN:https://doi.org/10.48550/arXiv.2408.00388 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Deepfake Detection
4. Passive Deepfake Authentication Methods
5. Deepfakes Detection Method on Realistic Scenarios
6. Active Authentication
VII. Conclusion

Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework / 2408.00965 / ISBN:https://doi.org/10.48550/arXiv.2408.00965 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background and Literature Review
3 Methodology
4 ESG-AI framework
5 Discussion
References

AI for All: Identifying AI incidents Related to Diversity and Inclusion / 2408.01438 / ISBN:https://doi.org/10.48550/arXiv.2408.01438 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background and Related Work
3 Methodology
4 Results
5 Discussion and Implications
6 Threats to Validity
References

Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governance / 2408.01458 / ISBN:https://doi.org/10.48550/arXiv.2408.01458 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Methods
4 Large-Scale Surveys of AI in the Literature
5 Discussion
References
B Additional Materials for Pilot Survey

Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity / 2408.04023 / ISBN:https://doi.org/10.48550/arXiv.2408.04023 / Published by ArXiv / on (web) Publishing site
2. Related Work
3. Proposed framework
5. Model Training
6. Results
7. Conclusion and Future Directions
References

AI-Driven Chatbot for Intrusion Detection in Edge Networks: Enhancing Cybersecurity with Ethical User Consent / 2408.04281 / ISBN:https://doi.org/10.48550/arXiv.2408.04281 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Related Work
III. Methodology
V. Results
References

Criticizing Ethics According to Artificial Intelligence / 2408.04609 / ISBN:https://doi.org/10.48550/arXiv.2408.04609 / Published by ArXiv / on (web) Publishing site
3 Critical Reflection on AI Risks
4 Exploring epistemic challenges
Bibliography

Interactive embodied evolution for socially adept Artificial General Creatures / 2407.21357 / ISBN:https://doi.org/10.48550/arXiv.2407.21357 / Published by ArXiv / on (web) Publishing site
References

Between Copyright and Computer Science: The Law and Ethics of Generative AI / 2403.14653 / ISBN:https://doi.org/10.48550/arXiv.2403.14653 / Published by ArXiv / on (web) Publishing site
Introduction
I. The Why and How Behind LLMs
II. The Difference Between Academic and Commercial Research
III. A Guide for Data in LLM Research
IV. The Path Ahead

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources / 2406.16746 / ISBN:https://doi.org/10.48550/arXiv.2406.16746 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Methodology & Guidelines
3 Data Sources
4 Data Preparation
5 Data Documentation and Release
6 Model Training
7 Environmental Impact
8 Model Evaluation
9 Model Release & Monitoring
References
A Contributions

Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives / 2407.14962 / ISBN:https://doi.org/10.48550/arXiv.2407.14962 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Generative AI
III. Language Modeling
IV. Challenges of Generative AI and LLMs
References
Authors

VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative Adversary / 2407.19524 / ISBN:https://doi.org/10.48550/arXiv.2407.19524 / Published by ArXiv / on (web) Publishing site
I Introduction
2 Related Works
3 Method
4 Experiment
References
Appendices

Speculations on Uncertainty and Humane Algorithms / 2408.06736 / ISBN:https://doi.org/10.48550/arXiv.2408.06736 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 The Numbers of the Future
3 Uncertainty Ex Machina
References

Visualization Atlases: Explaining and Exploring Complex Topics through Data, Visualization, and Narration / 2408.07483 / ISBN:https://doi.org/10.48550/arXiv.2408.07483 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Visualization Atlases : Examples and Collection
3 Visualization Atlas Design Patterns
4 Interviews with Visualization Atlas Creators
5 Visualization Atlases Genres
6 Key Characteristics of Visualization Atlases
7 Discussion
8 Conclusion
References

Neuro-Symbolic AI for Military Applications / 2408.09224 / ISBN:https://doi.org/10.48550/arXiv.2408.09224 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Neuro-Symbolic AI
III. Autonomy in Military Weapons Systems
IV. Military Applications of Neuro-Symbolic AI
V. Challenges and Risks
VI. Interpretability and Explainability
VII. Conclusion
References

Conference Submission and Review Policies to Foster Responsible Computing Research / 2408.09678 / ISBN:https://doi.org/10.48550/arXiv.2408.09678 / Published by ArXiv / on (web) Publishing site
Executive Summary
Introduction
Avoiding harm
Responsible disclosure of vulnerabilities
Obtaining Consent
Accurate Reporting and Reproducibility
Use of Generative AI in CS Conference Publications
Ways to Incorporate Ethics Review into Publication Review Processes
Reporting and Retraction Policies and Procedures
Conclusions
Acknowledgments
References

Don't Kill the Baby: The Case for AI in Arbitration / 2408.11608 / ISBN:https://doi.org/10.48550/arXiv.2408.11608 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
1. What is AI
2. Designating AI as an Arbitrator is Consistent with FAA
3. Practical and Strategic Benefits of Using AI in Arbitration
2. Let AI Grow Under Favorable Conditions: Avoiding Overly Moralistic Views
3. Arbitration Should Allow Flexible, Contract-Based Experimentation in a Fast- Evolving Regulatory Landscape

CIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical Researcher / 2408.11650 / ISBN:https://doi.org/10.48550/arXiv.2408.11650 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Background and Related Works
3. Methodology
4. Experiment Results
5. Discussion and Future Works
6. Conclusion

The Problems with Proxies: Making Data Work Visible through Requester Practices / 2408.11667 / ISBN:https://doi.org/10.48550/arXiv.2408.11667 / Published by ArXiv / on (web) Publishing site
Introduction
Related Work
Methods
Findings
Discussion
Limitations
Conclusion
Acknowledgments
References

Promises and challenges of generative artificial intelligence for human learning / 2408.12143 / ISBN:https://doi.org/10.48550/arXiv.2408.12143 / Published by ArXiv / on (web) Publishing site
Abstract
1 Main
2 Promises
3 Challenges
4 Needs
5 Conclusion and Future Directions
References
Acknowledgments

Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 European Union AI Act: a brief overview
5 Overall Ethical Requirements (O)
6 Fairness (F)
7 Privacy and Data Protection (P)
8 Safety and Robustness (SR)
9 Sustainability (SU)
10 Transparency and Explainability (T)
11 Truthfulness (TR)

Dataset | Mindset = Explainable AI | Interpretable AI / 2408.12420 / ISBN:https://doi.org/10.48550/arXiv.2408.12420 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Literature Review
3. Database and Experimental Setup
4. Experiment Implementation, Results and Analysis
5. Results Discussion
7. Acknowledge
References

Is Generative AI the Next Tactical Cyber Weapon For Threat Actors? Unforeseen Implications of AI Generated Cyber Attacks / 2408.12806 / ISBN:https://doi.org/10.48550/arXiv.2408.12806 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Related Work
IV. Attack Methodology
V. Conclusion
References

Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey / 2408.12880 / ISBN:https://doi.org/10.48550/arXiv.2408.12880 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Preliminaries
3 Multimodal Medical Studies
4 Contrastice Foundation Models (CFMs)
5 Multimodal LLMs (MLLMs)
6 Discussions of Current Studies
References
Appendix

Aligning XAI with EU Regulations for Smart Biomedical Devices: A Methodology for Compliance Analysis / 2408.15121 / ISBN:https://doi.org/10.48550/arXiv.2408.15121 / Published by ArXiv / on (web) Publishing site
1 Introduction
4 Background
5 Explanation Requirements and Legal Explanatory Goals
6 A Categorisation of XAI in Terms of Explanatory Goals
7 Case Studies: Closed-Loop and Semi-Closed-Loop Control
10 Conclusion
Acknowledgements
References

What Is Required for Empathic AI? It Depends, and Why That Matters for AI Developers and Users / 2408.15354 / ISBN:https://doi.org/10.48550/arXiv.2408.15354 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
“Fine cuts” of Empathy: Capabilities and Distinctions under the Empathy Umbrella
What Empathic Capabilities Do AIs Need?
Implications for AI Creators and Users
Acknowledgements
References

Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems / 2408.15550 / ISBN:https://doi.org/10.48550/arXiv.2408.15550 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Trustworthy and Responsible AI Definition
3 Governance for Human-Centric Intelligence Systems
4 Biases
5 Trustworthy and Responsible AI in Human-centric Applications
7 Guidelines and Recommendations
Acknowledgments
References

A Survey for Large Language Models in Biomedicine / 2409.00133 / ISBN:https://doi.org/10.48550/arXiv.2409.00133 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
3 LLMs in Zero-Shot Biomedical Applications
4 Adapting General LLMs to the Biomedical Field
5 Discussion
6 Conclusion
References

Digital Homunculi: Reimagining Democracy Research with Generative Agents / 2409.00826 / ISBN:https://doi.org/10.48550/arXiv.2409.00826 / Published by ArXiv / on (web) Publishing site
2. The Experimentation Bottleneck
3. How GenAI Could Make a Difference
4. Risks and Caveats
5. Annoyances or Dealbreakers?
References

The overlooked need for Ethics in Complexity Science: Why it matters / 2409.02002 / ISBN:https://doi.org/10.48550/arXiv.2409.02002 / Published by ArXiv / on (web) Publishing site
Abstract
Mapping ethical challenges in complexity science
Limited research on ethics in complexity science
Practical considerations for ethical actions in complexity science
Conclusion
Funding statement

AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities / 2409.02017 / ISBN:https://doi.org/10.48550/arXiv.2409.02017 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Background
Results
Discussion
Limitation
Ethic Statement
References

Preliminary Insights on Industry Practices for Addressing Fairness Debt / 2409.02432 / ISBN:https://doi.org/10.48550/arXiv.2409.02432 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
3 Method
4 Findings
5 Discussions
6 Conclusions
References

DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection / 2409.06072 / ISBN:https://doi.org/10.48550/arXiv.2409.06072 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
3 Data Details
4 LLM Services (Infrastructure)
6 Results
7 Limitations
References
10 Appendix

Exploring AI Futures Through Fictional News Articles / 2409.06354 / ISBN:https://doi.org/10.48550/arXiv.2409.06354 / Published by ArXiv / on (web) Publishing site
Reflections from two workshop participants
Discussion and conclusion

Face Recognition: to Deploy or not to Deploy? A Framework for Assessing the Proportional Use of Face Recognition Systems in Real-World Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
References

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources / 2406.16746 / ISBN:https://doi.org/10.48550/arXiv.2406.16746 / Published by ArXiv / on (web) Publishing site
B Cheatsheet Samples

Don't Kill the Baby: The Case for AI in Arbitration / 2408.11608 / ISBN:https://doi.org/10.48550/arXiv.2408.11608 / Published by ArXiv / on (web) Publishing site
Part IV. Future Direction and Conclusion

Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site
13 Ethical requirements at a glance
References

The overlooked need for Ethics in Complexity Science: Why it matters / 2409.02002 / ISBN:https://doi.org/10.48550/arXiv.2409.02002 / Published by ArXiv / on (web) Publishing site
Annexus

On the Creativity of Large Language Models / 2304.00008 / ISBN:https://doi.org/10.48550/arXiv.2304.00008 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
4 Easy and Hard Problems in Machine Creativity
5 Practical Implications
6 Conclusion
References

Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward / 2305.08413 / ISBN:https://doi.org/10.48550/arXiv.2305.08413 / Published by ArXiv / on (web) Publishing site
Introduction
Part I Modelling - Machine learning, computer vision and processing 1 Machine learning and computer vision for Earth observation
2 Advanced processing and computing
Part II Understanding - Physics-machine learning interplay, causality and ontologies 3 Knowledge-based AI and Earth observation
4 Explainable AI and causal inference
5 Physics-aware machine learning
Part III Communicating - Machine-user interaction, trustworthiness & ethics 6 User-centric Earth observation
7 Earth observation and society: the growing relevance of ethics
Conclusions
References

LLM generated responses to mitigate the impact of hate speech / 2311.16905 / ISBN:https://doi.org/10.48550/arXiv.2311.16905 / Published by ArXiv / on (web) Publishing site
2 Related Work
6 Experiment
7 Results
8 Discussion
9 Limitations
10 Ethical Considerations
References
C Verified Articles
E Used Prompts

Why business adoption of quantum and AI technology must be ethical / 2312.10081 / ISBN:https://doi.org/10.48550/arXiv.2312.10081 / Published by ArXiv / on (web) Publishing site
Argument from a holistic and humanistic perspective
Argument from Authority: Ethics by committee
Argument by regulatory relevance
Argument for acknowledging complexity: the case for individual ethos, regulation is not enough
Argument by analogy: The case of sustainability
Reductio ad absurdum: Argument by assuming the opposite scenario leading to unacceptable consequences
Summary and action areas
Notes
References

Views on AI aren't binary -- they're plural / 2312.14230 / ISBN:https://doi.org/10.48550/arXiv.2312.14230 / Published by ArXiv / on (web) Publishing site
Abstract
The false binary: A note on language
The false binary: Ethics’s discontents with Alignment
The complex reality: Where Ethics and Alignment (actually) differ
The complex reality: Where Ethics and Alignment (actually) are similar
The complex reality: Complication: The existential risk narrative has corporate valu
The complex reality: Complication: Good and bad ideas can be knotted together
Overcoming the dichotomy: Why should we?
Overcoming the dichotomy: How to build bridges
Conclusion
Glossary
Acknowledgements
References

Data-Centric Foundation Models in Computational Healthcare: A Survey / 2401.02458 / ISBN:https://doi.org/10.48550/arXiv.2401.02458 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Foundation Models
3 Foundation Models in Healthcare
4 Multi-Modal Data Fusion
5 Data Quantity
7 Data Privacy
8 Performance Evaluation
9 Challenges and Opportunities
References
A Healthcare Data Modalities

Ethical Artificial Intelligence Principles and Guidelines for the Governance and Utilization of Highly Advanced Large Language Models / 2401.10745 / ISBN:https://doi.org/10.48550/arXiv.2401.10745 / Published by ArXiv / on (web) Publishing site
Background
Advanced Large Language Models Governance Using AI Ethics
Considerations for Advanced Large Language Models and Policy-Making

Recent Advances in Hate Speech Moderation: Multimodality and the Role of Large Models / 2401.16727 / ISBN:https://doi.org/10.48550/arXiv.2401.16727 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Hate Speech
3 Methodology
4 Challenges
6 Conclusion
References

Integrating Generative AI in Hackathons: Opportunities, Challenges, and Educational Implications / 2401.17434 / ISBN:https://doi.org/10.48550/arXiv.2401.17434 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Methodology
3. Results
4. Discussion
5. Conclusion
References

Large language models as linguistic simulators and cognitive models in human research / 2402.04470 / ISBN:https://doi.org/10.48550/arXiv.2402.04470 / Published by ArXiv / on (web) Publishing site
Abstract
Language models as human participants
Six fallacies that misinterpret language models
Using language models to simulate roles and model cognitive processes
Concluding remarks
References

Navigating LLM Ethics: Advancements, Challenges, and Future Directions / 2406.18841 / ISBN:https://doi.org/10.48550/arXiv.2406.18841 / Published by ArXiv / on (web) Publishing site
III. Methodology
IV. Findings and Resultant Themes
V. Discussion
VI. Conclusion and Future directions
References

How Mature is Requirements Engineering for AI-based Systems? A Systematic Mapping Study on Practices, Challenges, and Future Research Directions / 2409.07192 / ISBN:https://doi.org/10.48550/arXiv.2409.07192 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Research Design
4 Results
5 Open Challenges and Future Research Directions (RQ5)
6 Discussions
7 Threats to Validity
8 Conclusion
References

Synthetic Human Memories: AI-Edited Images and Videos Can Implant False Memories and Distort Recollection / 2409.08895 / ISBN:https://doi.org/10.48550/arXiv.2409.08895 / Published by ArXiv / on (web) Publishing site
Introduction
1 Related Work
2 Methodology
3 Result of Primary Analysis
4 Results of Additional Analysis
5 Discussion
6 Conclusion
References
7 Supplementary Materials

Improving governance outcomes through AI documentation: Bridging theory and practice / 2409.08960 / ISBN:https://doi.org/10.48550/arXiv.2409.08960 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 What organizations could document about AI systems
3 Methods
4 Results
5 Limitations

ValueCompass: A Framework of Fundamental Values for Human-AI Alignment / 2409.09586 / ISBN:https://doi.org/10.48550/arXiv.2409.09586 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Designing ValueCompass: A Comprehensive Framework for Defining Fundamental Values in Alignment
4 Operationalizing ValueCompass: Methods to Measure Value Alignment of Humans and AI
5 Findings with ValueCompass: The Status Quo of Human-AI Value Alignment
6 Discussion
7 Conclusion
References

Beyond Algorithmic Fairness: A Guide to Develop and Deploy Ethical AI-Enabled Decision-Support Tools / 2409.11489 / ISBN:https://doi.org/10.48550/arXiv.2409.11489 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Ethical Considerations in AI-Enabled Optimization
3 Case Studies in AI-Enabled Optimization
4 Lessons Learned from the Case Studies
5 Conclusion
6 Acknowledgments
References
Appendix A Technical and Contextual Details for Collaborative Decentralized Cold Supply Chains
Appendix B Technical and Conceptual Details for the Power Systems Case Study

Reporting Non-Consensual Intimate Media: An Audit Study of Deepfakes / 2409.12138 / ISBN:https://doi.org/10.48550/arXiv.2409.12138 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Research
3 Method
4 Findings
5 Discussion
6 Conclusion
References
Appendices

Generative AI Carries Non-Democratic Biases and Stereotypes: Representation of Women, Black Individuals, Age Groups, and People with Disability in AI-Generated Images across Occupations / 2409.13869 / ISBN:https://doi.org/10.48550/arXiv.2409.13869 / Published by ArXiv / on (web) Publishing site
Mutual Impacts: Technology and Democracy
How Does AI See Humans in their Occupations?
Data and Results

GenAI Advertising: Risks of Personalizing Ads with LLMs / 2409.15436 / ISBN:https://doi.org/10.48550/arXiv.2409.15436 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background and Related Work
3 Chatbot Ad Engine Design
4 Effects of Ad Injection on LLM Performance
6 User Study Results
7 Discussion
References
A Appendix

XTRUST: On the Multilingual Trustworthiness of Large Language Models / 2409.15762 / ISBN:https://doi.org/10.48550/arXiv.2409.15762 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 XTRUST Construction
4 Experiments
5 Conclusion
Limitations
References
Appendices

Artificial Human Intelligence: The role of Humans in the Development of Next Generation AI / 2409.16001 / ISBN:https://doi.org/10.48550/arXiv.2409.16001 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Origins and the Path leading to AHI
4 Brain-inspired Information processing
5 Challenges and Perspectives in Human-Level AI Development
6 Final Thoughts and Discussions
References

Ethical and Scalable Automation: A Governance and Compliance Framework for Business Applications / 2409.16872 / ISBN:https://doi.org/10.48550/arXiv.2409.16872 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Literature Review
3. Methodology
4. Framework Development
5. Analysis and Discussion
7. Data Availability

Decoding Large-Language Models: A Systematic Overview of Socio-Technical Impacts, Constraints, and Emerging Questions / 2409.16974 / ISBN:https://doi.org/10.48550/arXiv.2409.16974 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Systematic Review Methodology
4 Characteristics of Publications
5 Aims & Objectives (RQ1)
6 Methodologies & Capabilities (RQ2)
7 Limitations & Considerations (RQ3)
8 Discussion

Social Media Bot Policies: Evaluating Passive and Active Enforcement / 2409.18931 / ISBN:https://doi.org/10.48550/arXiv.2409.18931 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Related Work
III. Current Platform Measures
V. Results
References

Safety challenges of AI in medicine / 2409.18968 / ISBN:https://doi.org/10.48550/arXiv.2409.18968 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Inherent problems of AI related to medicine
3 Risks of using AI in medicine
4 AI safety issues related to large language models in medicine
References

Responsible AI in Open Ecosystems: Reconciling Innovation with Risk Assessment and Disclosure / 2409.19104 / ISBN:https://doi.org/10.48550/arXiv.2409.19104 / Published by ArXiv / on (web) Publishing site
Abstract
I Introduction
2 Related Work
3 Methods
4 Results
5 Discussion
6 Conclusion
References

The Gradient of Health Data Privacy / 2410.00897 / ISBN:https://doi.org/10.48550/arXiv.2410.00897 / Published by ArXiv / on (web) Publishing site
2 Background and Related Work
4 Technical Implementation of a Privacy Gradient Model
5 Legal and Ethical Implications
6 Case Studies
7 Policy Implications and Recommendations
8 Conclusion and Future Directions
References

Enhancing transparency in AI-powered customer engagement / 2410.01809 / ISBN:https://doi.org/10.48550/arXiv.2410.01809 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Explaining AI-Powered Decision Making in Customer Engagement
Go Beyond Algorithms to Enhance Transparency

Ethical software requirements from user reviews: A systematic literature review / 2410.01833 / ISBN:https://doi.org/10.48550/arXiv.2410.01833 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Background
III. Research Methodology
IV. Results
V. Discussion
VI. Threats to Validity
VII. Conclusion
References
APPENDIX A SELECTED STUDIES
APPENDIX D ADDITIONAL INFORMATION

Clinnova Federated Learning Proof of Concept: Key Takeaways from a Cross-border Collaboration / 2410.02443 / ISBN:https://doi.org/10.48550/arXiv.2410.02443 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
III. FL System Elements
IV. Proof of Concept I
VI. Collaborative Network
VII. Evaluations and Experiments
VIII. Discussion and Conclusions

DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Life / 2410.02683 / ISBN:https://doi.org/10.48550/arXiv.2410.02683 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Value-Based Framework on Moral Dilemmas
4 Daily Dilemmas: Dataset Analysis
5 Model Preference and Steerability on Daily Dilemmas
6 Conclusion

Application of AI in Credit Risk Scoring for Small Business Loans: A case study on how AI-based random forest model improves a Delphi model outcome in the case of Azerbaijani SMEs / 2410.05330 / ISBN:https://doi.org/10.48550/arXiv.2410.05330 / Published by ArXiv / on (web) Publishing site
Introduction
Literature Review
Methodology
Discussion
Conclusion
Declarations of Interest
References
Appendix 2. Random forest Python code

AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models / 2410.07561 / ISBN:https://doi.org/10.48550/arXiv.2410.07561 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 AI Press System
5 Results
References
B Prompts for LLMs
C Prompts for Agents on Press Drafting Module
D Prompts for Agents on Press Polishing Module
F User Profile Pool Generating
G Evaluation Experiment

DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Life / 2410.02683 / ISBN:https://doi.org/10.48550/arXiv.2410.02683 / Published by ArXiv / on (web) Publishing site
Appendices

Investigating Labeler Bias in Face Annotation for Machine Learning / 2301.09902 / ISBN:https://doi.org/10.48550/arXiv.2301.09902 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
3. Method
4. Results
5. Discussion
6. Conclusion

From human-centered to social-centered artificial intelligence: Assessing ChatGPT's impact through disruptive events / 2306.00227 / ISBN:https://doi.org/10.48550/arXiv.2306.00227 / Published by ArXiv / on (web) Publishing site
The multiple levels of AI impact
The emerging social impacts of ChatGPT
Discussion
Conclusion
References

The Design Space of in-IDE Human-AI Experience / 2410.08676 / ISBN:https://doi.org/10.48550/arXiv.2410.08676 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Related Work
III. Method
IV. Results
V. Discussion
VII. Conclusion

Trust or Bust: Ensuring Trustworthiness in Autonomous Weapon Systems / 2410.10284 / ISBN:https://doi.org/10.48550/arXiv.2410.10284 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Related Work
III. Research Methodology
IV. Challenges of AWS
V. Opportunities of AWS
VI. Conclusion
References

Learning Human-like Representations to Enable Learning Human Values / 2312.14106 / ISBN:https://doi.org/10.48550/arXiv.2312.14106 / Published by ArXiv / on (web) Publishing site
A. Appendix

When AI Eats Itself: On the Caveats of Data Pollution in the Era of Generative AI / 2405.09597 / ISBN:https://doi.org/10.48550/arXiv.2405.09597 / Published by ArXiv / on (web) Publishing site
References

Study on the Helpfulness of Explainable Artificial Intelligence / 2410.11896 / ISBN:https://doi.org/10.48550/arXiv.2410.11896 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Measuring Explainability
References

Navigating the Cultural Kaleidoscope: A Hitchhiker's Guide to Sensitivity in Large Language Models / 2410.12880 / ISBN:https://doi.org/10.48550/arXiv.2410.12880 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
4 Cultural safety dataset
5 Experimental setup
6 Main results on evaluation set
References

Is ETHICS about ethics- Evaluating the ETHICS benchmark / 2410.13009 / ISBN:https://doi.org/10.48550/arXiv.2410.13009 / Published by ArXiv / on (web) Publishing site
2 Gap between knowledge of moral theory and acting morally
4 Poor quality of prompts and labels

How Do AI Companies Fine-Tune Policy? Examining Regulatory Capture in AI Governance / 2410.13042 / ISBN:https://doi.org/10.48550/arXiv.2410.13042 / Published by ArXiv / on (web) Publishing site
Executive Summary
2 Defining “Regulatory Capture”
3 Methods
4 Outcomes of Regulatory Capture in US AI Policy
5 Mechanisms of Industry Influence in US AI Policy
6 Mitigating or Preventing Regulatory Capture in AI Policy
Adverse Impacts Statement
Acknowledgments
References
Appendices

Data Defenses Against Large Language Models / 2410.13138 / ISBN:https://doi.org/10.48550/arXiv.2410.13138 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Ethics of Resisting LLM Inference
5 Experiments
7 Conclusion and Limitations
References
Appendices

Do LLMs Have Political Correctness? Analyzing Ethical Biases and Jailbreak Vulnerabilities in AI Systems / 2410.13334 / ISBN:https://doi.org/10.48550/arXiv.2410.13334 / Published by ArXiv / on (web) Publishing site
1 Introduction
5 Conclusion
Refefences

A Simulation System Towards Solving Societal-Scale Manipulation / 2410.13915 / ISBN:https://doi.org/10.48550/arXiv.2410.13915 / Published by ArXiv / on (web) Publishing site
3 Methodology
4 Analysis
6 Social Impact Statement
References
Appendices

Confrontation or Acceptance: Understanding Novice Visual Artists' Perception towards AI-assisted Art Creation / 2410.14925 / ISBN:https://doi.org/10.48550/arXiv.2410.14925 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background and Related Work
3 Positionality Statementy
5 RQ1: Evolution of the Opinions Towards AI Tools
6 RQ2: Practices of AI Tools
7 RQ3: The Stakeholder's Opinions Towards AI Tools
8 RQ4: Expectation and Confrontation Towards The Future
9 General Discussions and Design Implications
10 Ethical Considerations
References

Jailbreaking and Mitigation of Vulnerabilities in Large Language Models / 2410.15236 / ISBN:https://doi.org/10.48550/arXiv.2410.15236 / Published by ArXiv / on (web) Publishing site
IV. Defense Mechanisms Against Jailbreak Attacks
V. Evaluation and Benchmarking
VII. Conclusion
References

Ethical AI in Retail: Consumer Privacy and Fairness / 2410.15369 / ISBN:https://doi.org/10.48550/arXiv.2410.15369 / Published by ArXiv / on (web) Publishing site
1.0 Introduction
2.0 Literature Review
4.0 Results
5.0 Discussions
6.0 Conclusion
8.0 References

Redefining Finance: The Influence of Artificial Intelligence (AI) and Machine Learning (ML) / 2410.15951 / ISBN:https://doi.org/10.48550/arXiv.2410.15951 / Published by ArXiv / on (web) Publishing site
Introduction
Current Perspective on AI & ML in Finance
Redefining the Landscape
Future Scope
Conclusion
References

Vernacularizing Taxonomies of Harm is Essential for Operationalizing Holistic AI Safety / 2410.16562 / ISBN:https://doi.org/10.48550/arXiv.2410.16562 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Understanding Social Spaces: An Anthropological Ethics Approach
Taxonomies of Harm Must be Vernacularized to be Operationalized
Overgeneral Taxonomies Can Compound Potential Harms
Vernacularization as a General AI Safety Operationalization Methodology
Limitations
Conclusion
References

Distribution of Responsibility During the Usage of AI-Based Exoskeletons for Upper Limb Rehabilitation / 2410.16887 / ISBN:https://doi.org/10.48550/arXiv.2410.16887 / Published by ArXiv / on (web) Publishing site
Abstract
II. Case Studfy: AIBle
III. Ethics Guidelines
V. Technical Factors During the System Design

Trustworthy XAI and Application / 2410.17139 / ISBN:https://doi.org/10.48550/arXiv.2410.17139 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Trustworthy XAI Vs AI
3 Applications of Trustworthy XAI
4 Future of Trustworthy (XAI)
5 Conclusions
References

Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements / 2410.17141 / ISBN:https://doi.org/10.48550/arXiv.2410.17141 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Benchmark
4 Evaluation
7 Potential Risks
References
Supplementary Materials

Ethical Leadership in the Age of AI Challenges, Opportunities and Framework for Ethical Leadership / 2410.18095 / ISBN:https://doi.org/10.48550/arXiv.2410.18095 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Understanding Ethical Leadership
Ethical Challenges Presented by AI
Opportunities for Ethical Leadership in the age of AI
Framework for Ethical Leadership
Conclusion
References

Demystifying Large Language Models for Medicine: A Primer / 2410.18856 / ISBN:https://doi.org/10.48550/arXiv.2410.18856 / Published by ArXiv / on (web) Publishing site
Introduction
Task Formulation
Large Language Model Selection
Deployment considerations
Glossary
Acknowledgements
References

The Cat and Mouse Game: The Ongoing Arms Race Between Diffusion Models and Detection Methods / 2410.18866 / ISBN:https://doi.org/10.48550/arXiv.2410.18866 / Published by ArXiv / on (web) Publishing site
Abstract
II. Fundamentals of Diffusion Models and Detection Challenges
IV. Detection Methods Based on Textual and Multimodal Analysis for Text-to-Image Models
V. Datasets and Benchmarks
VI. Evaluation Metrics
VII. Applications and Implications

TRIAGE: Ethical Benchmarking of AI Models Through Mass Casualty Simulations / 2410.18991 / ISBN:https://doi.org/10.48550/arXiv.2410.18991 / Published by ArXiv / on (web) Publishing site
Abstract
3 Results
4 Discussion
Acknowledgments and Disclosure of Funding
Appendices

My Replika Cheated on Me and She Liked It: A Taxonomy of Algorithmic Harms in Human-AI Relationships / 2410.20130 / ISBN:https://doi.org/10.48550/arXiv.2410.20130 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Methodology
4 Results
5 Discussion
6 Conclusion
References

The Trap of Presumed Equivalence: Artificial General Intelligence Should Not Be Assessed on the Scale of Human Intelligence / 2410.21296 / ISBN:https://doi.org/10.48550/arXiv.2410.21296 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Assessing the Current State of Self-Awareness in Artificial Intelligent Systems
5 The Runaway AGI Evolutionary Gap
References

Standardization Trends on Safety and Trustworthiness Technology for Advanced AI / 2410.22151 / ISBN:https://doi.org/10.48550/arXiv.2410.22151 / Published by ArXiv / on (web) Publishing site
Abstract
3 Trends in advanced AI safety and trustworthiness standardization
4 Conclusion
Glossary Acronyms Acknowledgments
References

Democratizing Reward Design for Personal and Representative Value-Alignment / 2410.22203 / ISBN:https://doi.org/10.48550/arXiv.2410.22203 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background and Related Work
3 Interactive-Reflective Dialogue Alignment (IRDA) System
4 Study Design & Methodology
5 Results: Study 1 - Multi-Agent Apple Farming
6 Results: Study 2 - The Moral Machine
7 Discussion
References
Appendices

Ethical Statistical Practice and Ethical AI / 2410.22475 / ISBN:https://doi.org/10.48550/arXiv.2410.22475 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
Acknowledgements

Moral Agency in Silico: Exploring Free Will in Large Language Models / 2410.23310 / ISBN:https://doi.org/10.48550/arXiv.2410.23310 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Theoretical Framework
Discussion
Conclusion
References

Web Scraping for Research: Legal, Ethical, Institutional, and Scientific Considerations / 2410.23432 / ISBN:https://doi.org/10.48550/arXiv.2410.23432 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 What is scraping?
3 Research Considerations
4 Recommendations
5 A Researchers’ Checklist
6 Discussion
7 Conclusions
References
Appendices

The Transformative Impact of AI and Deep Learning in Business: A Literature Review / 2410.23443 / ISBN:https://doi.org/10.48550/arXiv.2410.23443 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Background and Theoretical Foundations of AI and Deep Learning
III. Literature Review: Current Applications of AI and Deep Learning in Business
IV. Challenges and Ethical Considerations in AI Adoption for Business
V. Future Trends and Emerging Research in AI for Business
VI. Conclusion and Implications for Business Leaders
VII. References

Using Large Language Models for a standard assessment mapping for sustainable communities / 2411.00208 / ISBN:https://doi.org/10.48550/arXiv.2411.00208 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Literature Review
3 Methodology
4 CaseStudies and Results
5 Discussion
6 FutureDirections
7 Conclusion
References

Where Assessment Validation and Responsible AI Meet / 2411.02577 / ISBN:https://doi.org/10.48550/arXiv.2411.02577 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Classical Assessment Validation Theory and Responsible AI
The Evolution of Responsible AI for Assessment
Integrating Classical Validation Theory and Responsible AI
Conclusion & Future Directions
References

Examining Human-AI Collaboration for Co-Writing Constructive Comments Online / 2411.03295 / ISBN:https://doi.org/10.48550/arXiv.2411.03295 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Methods
4 Findings
5 Discussion
References
A Appendix

Smoke Screens and Scapegoats: The Reality of General Data Protection Regulation Compliance -- Privacy and Ethics in the Case of Replika AI / 2411.04490 / ISBN:https://doi.org/10.48550/arXiv.2411.04490 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. AI chatbots in privacy and ethics research
3. Method
4. Results
5. Discussion
6. Conclusions
References

A Comprehensive Review of Multimodal XR Applications, Risks, and Ethical Challenges in the Metaverse / 2411.04508 / ISBN:https://doi.org/10.48550/arXiv.2411.04508 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Multimodal Interaction Across the Virtual Continuum
3. XR Applications: Expanding Multimodal Interactions Across Domains
4. Potential Risks and Ethical Challenges of XR and the Metaverse
5. General Discussion
7. References

I Always Felt that Something Was Wrong.: Understanding Compliance Risks and Mitigation Strategies when Professionals Use Large Language Models / 2411.04576 / ISBN:https://doi.org/10.48550/arXiv.2411.04576 / Published by ArXiv / on (web) Publishing site
Abstract
2 Background and Related Work
3 Method: Semi-structured Interviews
4 Findings
5 Discussion
6 Conclusion
References

Navigating the Cultural Kaleidoscope: A Hitchhiker's Guide to Sensitivity in Large Language Models / 2410.12880 / ISBN:https://doi.org/10.48550/arXiv.2410.12880 / Published by ArXiv / on (web) Publishing site
Appendices

CogErgLLM: Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics / 2407.02885 / ISBN:https://doi.org/10.48550/arXiv.2407.02885 / Published by ArXiv / on (web) Publishing site
Acknowledgements

Improving governance outcomes through AI documentation: Bridging theory and practice / 2409.08960 / ISBN:https://doi.org/10.48550/arXiv.2409.08960 / Published by ArXiv / on (web) Publishing site
6 Directions for future research
7 Conclusions

How should AI decisions be explained? Requirements for Explanations from the Perspective of European Law / 2404.12762 / ISBN:https://doi.org/10.48550/arXiv.2404.12762 / Published by ArXiv / on (web) Publishing site
1 Introduction
4 Legal Requirements: Decision-Centric
5 Legal Requirements: Model-Centric
6 Discussion
7 Summary
References

A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions / 2406.03712 / ISBN:https://doi.org/10.48550/arXiv.2406.03712 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Background and Technology
III. From General to Medical-Specific LLMs
IV. Improving Algorithms for Med-LLMs
V. Applying Medical LLMs
VI. Trustworthiness and Safety
VII. Future Directions
VIII. Conclusions
References

The doctor will polygraph you now: ethical concerns with AI for fact-checking patients / 2408.07896 / ISBN:https://doi.org/10.48550/arXiv.2408.07896 / Published by ArXiv / on (web) Publishing site
Abstract
2. Clinical, Technical, and Ethical Concerns
3. Methods
4. Results
5. Discussion
6. Conclusion
References:

Nteasee: A mixed methods study of expert and general population perspectives on deploying AI for health in African countries / 2409.12197 / ISBN:https://doi.org/10.48550/arXiv.2409.12197 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusion
References

Large-scale moral machine experiment on large language models / 2411.06790 / ISBN:https://doi.org/10.48550/arXiv.2411.06790 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Results
Discussion
Supporting information
References

Persuasion with Large Language Models: a Survey / 2411.06837 / ISBN:https://doi.org/10.48550/arXiv.2411.06837 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Application Domains
3 Factors Influencing Persuasiveness
4 Experimental Design Patterns
5 Ethical Considerations
6 Conclusion and Future Directions
References

Enhancing Accessibility in Special Libraries: A Study on AI-Powered Assistive Technologies for Patrons with Disabilities / 2411.06970 / ISBN:https://doi.org/10.48550/arXiv.2411.06970 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
3. Literature review
4. Overview of Assistive Technology and AI-Based Assistive Technology
6. Data Collection Method
7. Case Studies:
9. Conclusion
References

Collaborative Participatory Research with LLM Agents in South Asia: An Empirically-Grounded Methodological Initiative and Agenda from Field Evidence in Sri Lanka / 2411.08294 / ISBN:https://doi.org/10.48550/arXiv.2411.08294 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Why South Asia Needs This Now
3 Proposed LLM4Participatory Research Framework
4 Field Work and Implementation Insights
5 Discussion and Future Agenda
6 Conclusion
References

The EU AI Act is a good start but falls short / 2411.08535 / ISBN:https://doi.org/10.48550/arXiv.2411.08535 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Methodology
3 Results
4 Discussion
5 Conclusion and Future Work
References

Human-Centered AI Transformation: Exploring Behavioral Dynamics in Software Engineering / 2411.08693 / ISBN:https://doi.org/10.48550/arXiv.2411.08693 / Published by ArXiv / on (web) Publishing site
II. Related Work
III. Research Method
IV. Results
V. Discussion
VI. Conclusions
References

Programming with AI: Evaluating ChatGPT, Gemini, AlphaCode, and GitHub Copilot for Programmers / 2411.09224 / ISBN:https://doi.org/10.48550/arXiv.2411.09224 / Published by ArXiv / on (web) Publishing site
Abstract
2 Related Work
3 Transformer Architecture
4 Methods
5 Empirical Result
6 Content
7 Response Accuracy
11 Future Work
12 Conclusion
13 Acknowledgement
References

Generative AI in Multimodal User Interfaces: Trends, Challenges, and Cross-Platform Adaptability / 2411.10234 / ISBN:https://doi.org/10.48550/arXiv.2411.10234 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Problem Statement: the Interface Dilemma
III. History and Evolution of User Interfaces
IV. Current App Frameworks and AI Integration
V. Multimodal Interaction
VI. Limitations, Challenges, and Future Directions for AI-Driven Interfaces
VIII. Conclusion
References

Bias in Large Language Models: Origin, Evaluation, and Mitigation / 2411.10915 / ISBN:https://doi.org/10.48550/arXiv.2411.10915 / Published by ArXiv / on (web) Publishing site
References
1. Introduction
3. Extrinsic Bias
4. Bias Evaluation
5. Bias Mitigation
6. Ethical Concerns and Legal Challenges

Framework for developing and evaluating ethical collaboration between expert and machine / 2411.10983 / ISBN:https://doi.org/10.48550/arXiv.2411.10983 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Method
4. Acknowledgement
References

Chat Bankman-Fried: an Exploration of LLM Alignment in Finance / 2411.11853 / ISBN:https://doi.org/10.48550/arXiv.2411.11853 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related work
3 Experimental framework
4 Results
5 Conclusion
References

Artificial Intelligence in Cybersecurity: Building Resilient Cyber Diplomacy Frameworks / 2411.13585 / ISBN:https://doi.org/10.48550/arXiv.2411.13585 / Published by ArXiv / on (web) Publishing site
Paper
Bibliography

GPT versus Humans: Uncovering Ethical Concerns in Conversational Generative AI-empowered Multi-Robot Systems / 2411.14009 / ISBN:https://doi.org/10.48550/arXiv.2411.14009 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
3 Method
4 Results
5 Discussion
6 Conclusion
References

Privacy-Preserving Video Anomaly Detection: A Survey / 2411.14565 / ISBN:https://doi.org/10.48550/arXiv.2411.14565 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
III. P2VAD with non -Identifiable Elements
V. Edge-Cloud Intelligencve Empowered P2VAD
VI. Evaluation Benchmarks and Metrics
VII. Discussion
References

Advancing Transformative Education: Generative AI as a Catalyst for Equity and Innovation / 2411.15971 / ISBN:https://doi.org/10.48550/arXiv.2411.15971 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Theoretical Framework
3 Literature Review
4 Findings and Discussion
5 Case Studies
7 Long-Term Implications of Generative AI Integration
8 Global Trends in AI-Driven Education
9 Future Work
10 Proposed Policy Recommendations
11 Conclusion
References

Responsible forecasting: identifying and typifying forecasting harms / 2411.16531 / ISBN:https://doi.org/10.48550/arXiv.2411.16531 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Harms in forecasting
4 Findings: typology of harm in forecasting
5 Discussion
6 A Research agenda
7 Conclusions
Acknowledgments
References

AI-Augmented Ethical Hacking: A Practical Examination of Manual Exploitation and Privilege Escalation in Linux Environments / 2411.17539 / ISBN:https://doi.org/10.48550/arXiv.2411.17539 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Generative AI and ChatGPT
3 Laboratory Setup
4 Methodology
5 Execution
6 Discussion: Benefits, Risks and Limitations
7 Related Work
8 Conclusions and Directions for Further Research
References

Examining Multimodal Gender and Content Bias in ChatGPT-4o / 2411.19140 / ISBN:https://doi.org/10.48550/arXiv.2411.19140 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Related Works
3. Textual Generation Experiment
5. Discussion on Content and Gender Biases in ChatGPT-4O
6. Conclusion and Future Directions
References

Ethics and Artificial Intelligence Adoption / 2412.00330 / ISBN:https://doi.org/10.48550/arXiv.2412.00330 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Literature Review
III. Research Model
V. Analysis and Results
VI. Conclusions
References

Human-centred test and evaluation of military AI / 2412.01978 / ISBN:https://doi.org/10.48550/arXiv.2412.01978 / Published by ArXiv / on (web) Publishing site
Summary
Full Summary

Artificial Intelligence Policy Framework for Institutions / 2412.02834 / ISBN:https://doi.org/10.48550/arXiv.2412.02834 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Context for AI
III. Key Considerations for AI Policy
IV. Framework for AI Policy Development
V. Conclusion
References

Ethical Challenges and Evolving Strategies in the Integration of Artificial Intelligence into Clinical Practice / 2412.03576 / ISBN:https://doi.org/10.48550/arXiv.2412.03576 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction and Motivation
Core Ethical Challenges
Emerging Ideas

Towards a Practical Ethics of Generative AI in Creative Production Processes / 2412.03579 / ISBN:https://doi.org/10.48550/arXiv.2412.03579 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Ethics for AI in design
Conclusion

Exploring AI Text Generation, Retrieval-Augmented Generation, and Detection Technologies: a Comprehensive Overview / 2412.03933 / ISBN:https://doi.org/10.48550/arXiv.2412.03933 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. AI Text Generators (AITG)
III. Retrieval Augmented Generation (RAG)
V. AI Text Detectors (AITD)
VIII. Future Work and Conclusion
References

Large Language Models in Politics and Democracy: A Comprehensive Survey / 2412.04498 / ISBN:https://doi.org/10.48550/arXiv.2412.04498 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
3. LLM Applications in Politics
References

From Principles to Practice: A Deep Dive into AI Ethics and Regulations / 2412.04683 / ISBN:https://doi.org/10.48550/arXiv.2412.04683 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Preliminaries and definitions
3 How to design regulation-compliant systems: the synergies and conflicts
4 Discussion and future directions
5 Conclusion
References

Employee Well-being in the Age of AI: Perceptions, Concerns, Behaviors, and Outcomes / 2412.04796 / ISBN:https://doi.org/10.48550/arXiv.2412.04796 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
I. Key Concerns on AI and Employee Well-Being
II. The Impact on Job Satisfaction and Retention
III. The Role of Organizational Support
IV. Behavioral Ooutcomes Linked to AI Perceptions
V. AI-Employee Well-being Interaction Framework
VI. Future of AI and Employee Well-Being
X. Conclusion
References

Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground / 2412.05130 / ISBN:https://doi.org/10.48550/arXiv.2412.05130 / Published by ArXiv / on (web) Publishing site
II AI Practice and Contextual Integrity
III AI Ethics and the notion of AI as uncharted moral territory
IV Integrative AI Ethics
VI References

Can OpenAI o1 outperform humans in higher-order cognitive thinking? / 2412.05753 / ISBN:https://doi.org/10.48550/arXiv.2412.05753 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusion
6 Data availability statement
References

Political-LLM: Large Language Models in Political Science / 2412.06864 / ISBN:https://doi.org/10.48550/arXiv.2412.06864 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Preliminaries
4 Classical Political Science Functions and Modern Transformations
5 Technical Foundations for LLM Applications in Political Science
6 Future Directions & Challenges
References

Responsible AI in the Software Industry: A Practitioner-Centered Perspective / 2412.07620 / ISBN:https://doi.org/10.48550/arXiv.2412.07620 / Published by ArXiv / on (web) Publishing site
II. Method
III. Findings
IV. Discussions
V. Conclusions

Trustworthy artificial intelligence in the energy sector: Landscape analysis and evaluation framework / 2412.07782 / ISBN:https://doi.org/10.48550/arXiv.2412.07782 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Landscape of Trustworthy AI in the EU
III. E-TAI – Methodological Framework for Trustworthy AI in the Energy Domain
IV. Conclusions and Future Work
References

Digital Democracy in the Age of Artificial Intelligence / 2412.07791 / ISBN:https://doi.org/10.48550/arXiv.2412.07791 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Digital Citizenship: from Individualised to Stereotyped Identities
3. Participation: Civic Engagement and Digital Platforms
4. Representation: Digital and AI Technologies in Modern Electoral Processes
5. Public Sphere and Political Advocacy
6. Conclusions
References

Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact / 2412.07880 / ISBN:https://doi.org/10.48550/arXiv.2412.07880 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Preliminaries
4 Designing Solution Methods
5 Testing and Deployment
References

Bias in Large Language Models: Origin, Evaluation, and Mitigation / 2411.10915 / ISBN:https://doi.org/10.48550/arXiv.2411.10915 / Published by ArXiv / on (web) Publishing site
Appendices

Chat Bankman-Fried: an Exploration of LLM Alignment in Finance / 2411.11853 / ISBN:https://doi.org/10.48550/arXiv.2411.11853 / Published by ArXiv / on (web) Publishing site
Appendices

Ethical Challenges and Evolving Strategies in the Integration of Artificial Intelligence into Clinical Practice / 2412.03576 / ISBN:https://doi.org/10.48550/arXiv.2412.03576 / Published by ArXiv / on (web) Publishing site
Discussion
References

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