Why_this_webapp Bibliography

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 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

1 Introduction
2 Background
3 Methodology
4 Findings
5 Discussion
References

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
2 Background
5 Detail results and analysis
6 Threats to validity
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

3 Method
4 Results

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

1 Introduction
3 Study Methodology
4 Evaluation of Ethical AI Principles
5 Evaluation of Ethical Principle Implementations
6 Gap Mitigation
8 Conclusion
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

1. Problems with AI
2. Defining ethical AI
3. Implementing ethical AI

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

Abstract
2 Related Work
3 Methodology
4 Results
5 Discussion

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

4 A Clearer Account of Research Priorities and Disagreements

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

2 Related Work
4 Deployment and Evaluation
5 Discussion
6 Conclusion
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

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 2: History and prospective
Section 3: Current trends 2020-2023
Section 4: Considerations and conclusions

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

1 Introduction
2 Background
4 Proposed competency framework for responsible AI practitioners
5 Discussion
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

Introduction
Results
Discussion
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

1 Introduction
2 The Question Bank: QB4AIRA
3 Evaluation

A multilevel framework for AI governance / 2307.03198 / ISBN:https://doi.org/10.48550/arXiv.2307.03198 / Published by ArXiv / on (web) Publishing site

1. Introductioon
3. International and National Governance
4. Corporate Self-Governance
5. AI Literacy and Governance by Citizen
6. Psychology of 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

Abstract
1. Introduction
2. Method
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

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

Results

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
3 Enhancing Protection for the General Public and Vulnerable Groups
4 Conclusion
References

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

Abstract
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
Ethics declarations
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

System-role
Image-related
Generation-related
Bias and Discrimination of Training Data
References

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

Abstract
1 Introduction
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

1 Introduction
3 Taxonomy of ethical principles
4 Previous operationalisation of ethical principles
5 Gaps in operationalising ethical principles
References

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

Abstract
Introduction
Responsibility in War
Computers, Autonomy and Accountability
Moral Injury
Human Factors
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

1 Introduction
2 Results

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
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

Abstract
3 LLM-based penetration testing
4 Discussion
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

1 Introduction
2 Results
3 Discussion
4 Conclusions
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
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

Introduction

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

3 Emergence of Creative AI Tools and Game-Based Methodologies
4 Enhancing User Experience through Creative AI Tools
6 Unveiling the Potential: Benefits of Interactive Web-Based Programming
7 Navigating Constraints: Limitations of Creative AI and GameBased Techniques
11 Bias Awareness: Navigating AI-Generated Content in Education
12 The Future Landscape: Creative AI Tools and Game-Based Methodologies in Education
13 Case Study Example: Learning Success with Creative AI and Game-Based Techniques
14 Conclusion & Discussion

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

Abstract
1 Introduction
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
7 Conclusions
References
A Agreement Analysis
B Variability Analysis
C Power analysis
D Stability 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

Abstract
I. Introduction
II. Methods and training process of LLMs
IV. Applied and technology implications for LLMs
V. Market analysis of LLMs and cross-industry use cases
VI. Solution architecture for privacy-aware and trustworthy conversational AI
VII. Discussions
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

Abstract
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
5 Research directions in AI safety and 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
4 Results and discussion
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

Abstract
1 Introduction
2 Related Works
3 Theory and Method
4 Experiment
5 Conclusion
Ethical Impact
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

Abstract
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
7 Conclusion
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

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 - 2 Appreciate Systems: Mimicking Styles
Part 1 - 3 Artistic Systems: Mimicking Inspiration
Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data
Part 2 - 3 Photogrammetry / Volumetric Capture
Part 2 - 4 Aesthetic Descriptor: Labelling Artefacts with Emotion
Part 3 Towards a Machine Artist Model
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
References

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

Abstract
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
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
4 Modeling Ethics
5 Experiments
Appendix
References

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

Abstract
I. Introduction and Motivation
II. AI-Robotics Systems Architecture
IV. Attack Surfaces
V. Ethical & Legal Concerns
VI. Human-Robot Interaction (HRI) Security Studies
VII. Future Research & Discussion
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

2 Emotion, Sentience and Morality
3 Proposing a Hybrid Approach
4 AI Governance Principles
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
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

Introduction
ClausewitzGPT and Modern Strategy
Mathematical Foundations
Ethical and Strategic Considerations: AI Mediators in the Age of LLMs
Integrating Computational Social Science, Computational Ethics, Systems Engineering, and AI Ethics in LLMdriven Operations
Conclusion

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
3 Analysis and Findings
4 Discussion
5 Conclusion
References
B Pre-class Questionnaire (Verbatim)
D Post-Activity Questionnaire (Verbatim)
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

Abstract
1. Introduction
2. Literature Review
3. AI Ethical Principles
4. Implementing the Practical Use of Ethical AI Applications
5. Conclusions and Recommendations

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
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

1 Introduction
3 The applications of STREAM

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

2 Regulation: A Short Introduction
3 LLMs: Risk and Uncertainty
5 Regulation and NLP (RegNLP): A New Field
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
3. Ethics of AI and Robotics
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

Evaluation of the Pilot Study

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

2. The practice of multilateral negotiation and the mechanisms of compromises
4. Towards a compromise: drafting the normative hybridity
5. Text negotiations as normative testing

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
Why Ethics
Principal Ethics in Healthcare
Method
Results and Discussion
A Unified Utilitarian Ethics Framework
Theory and Practical Implications
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

1. Introduction
2. Methods for Comprehensive Review
3. Clinical Risks
4. Technical Risks
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
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

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

3 Results
A GPT-4’s Training Set Personality Profile

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 in AI
Different Types of Trust
Trust and AI Ethics Principles
Trust in AI as Socio-Technical Systems
Conclusion
References

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

3 Objectives
4 Methodology
5 Relating Case Studies to Indigenous Data Sovereignty and CARE Principles
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

3 Ethical Data Collection, Responsible AI Development, and the Path Forward
4 Conclusion
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

1. Introduction
2. AI and blockchain in education: An overview of the benefits and challenges
4. Blockchain-based credentialing and certification
5. AI-powered assessment and evaluation
6. Blockchain-based decentralized learning networks
7. AI-powered content creation and curation
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

2. “Belief” in Humans and AI
3. Proposed Novel Topics in an Ethics of AI Belief
References

A Conceptual Algorithm for Applying Ethical Principles of AI to Medical Practice / 2304.11530 / ISBN:https://doi.org/10.48550/arXiv.2304.11530 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Ethical concerns of AI in medicine
3 Ethical datasets and algorithm development guidelines
4 Towards solving key ethical challenges in Medical AI
5 Ethical guidelines for medical AI model deployment
6 Discussion
7 Conclusion and Future Directions
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

1 Introduction
2 Methodology
3 Governance Patterns
4 Process Patterns
5 Product Patterns
6 Related Work
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

Abstract
INTRODUCTION
METHODS
FUTURE-AI GUIDELINE
DISCUSSION
COMPETING INTERESTS

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

2 Agent Design
4 Agent Performance
References
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
7 Contribution Statement
B Trait Preference Modeling
C General Prompts for GfH Preference Modeling
D Generalization to Other Traits
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
5 Discussion
7 Limitation and Future Research

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

1 Introduction
2 Trifecta of AI Challenges
3 Systematic AI Approach for AGI
4 Systematic AI for Energy Wall
6 System Insights from the Brain
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

IV. Artificial Intelligence Embedded UAV
V. Challenges and Future Aspect on AI Enabled UAV
VI. Review Summary
VII. Conclusion
References

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

Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Causal Models
3 The BvH and HK Definitions
5 The Epistemic Condition
6 Degree of Responsibility
References
Appendix

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

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

Introduction
AI Ethics in Cybersecurity
Educational Challenges of Teaching AI Ethics in Cybersecurity and Core Ethical Principles
AI tool-specific educational concerns
Communication skills in cybersecurity and ethics
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

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
References
Appendix B Placing Research Ethics for Human Participans in Historical Context

LLMs grasp morality in concept / 2311.02294 / ISBN:https://doi.org/10.48550/arXiv.2311.02294 / Published by ArXiv / on (web) Publishing site

3 The Meaning 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

Introduction
Literature Review
Research questions

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

1 Introduction
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

2 Overview of Kantian Deontology
3 Measuring Fairness Metrics
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

Abstract
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
9 Future directions for ChatGPT and natural language processing
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
III. Impacts of bias in AI
VI. Mitigation strategies for fairness in AI
VII. Conclusions
References

Towards ethical multimodal systems / 2304.13765 / ISBN:https://doi.org/10.48550/arXiv.2304.13765 / Published by ArXiv / on (web) Publishing site

2 Related Work
3 Crafting an Ethical Dataset

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
III. Prehistoric prompting: pre NN-era
IV. History of NLP between 2010 and 2015: the pre-attention mechanism era
VI. 2015: birth of the transformer
VII. The second wave in 2017: rise of RL
VIII. The third wave 2018: the rise of transformers
IX. 2019: THE YEAR OF CONTROL
X. 2020-2021: the rise of LLMS
XI. 2022-current: beyond language generation
XII. Conclusions

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

1 Introduction
2 Related work
3 Method
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
4 Empirical Evaluation and Outcomes
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

I. Introduction
III. Safety
IV. Trust
V. Ethics
VI. Conclusion
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
Ethical Considerations

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

1 Introduction
2 UnknownBench: Evaluating LLMs on the Unknown
3 Experiments
4 Related Work
5 Conclusion
References
B Confidence Elicitation Method Comparison
D Additional Results and Figures

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

Abstract
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
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
2 Background
3 Methodology
4 Findings
5 Discussion
6 Limitations
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

Executive Summary
Preface
The Problem
Why Liability Law?
Harms, Risk, and Liability Practices
Mitigation Tools
Conclusion
Appendix A - What is an Algorithmic Harm? And a Bibliography
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
References

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

2 Background & Related Work
4 Findings
5 Discussion and Recommendations
References
B Methodology

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
References
A Overview of AIIA Instruments
B Study Materials

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

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

What do RAI venues do?
References

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

I. Introduction
II. Education and LLMS
IV. LLM-empowered education
V. Key points in LLMSEDU
VI. Challenges and future directions
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
II. Extent and impact of generative AI
V. Additional thoughts
VI. Conclusion

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

2 Related Works
3 Methodology
4 Results and Discussion
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

Results
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

OVERVIEW OF SOCIETAL BIASES IN GAI MODELS
ANALYTICAL FRAMEWORK
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

1. Introduction
2. Pre-Deployment phase
3. Production deployment monitoring phase
4. Post-market surveillance phase

Ethics and Responsible AI Deployment / 2311.14705 / ISBN:https://doi.org/10.48550/arXiv.2311.14705 / Published by ArXiv / on (web) Publishing site

3. Ethical considerations in AI decision-making
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.
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

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

I. Very slowly then all-at-once
V. Potential harms and mitigation

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
7 Conclusion
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
III. The rise of large AI models
IV. Societal implications
V. Technical defense mechanisms
VII. Ethical considerations
IX. Discussion
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

1 Introduction
3 Mapping Challenges throughout the Data Lifecycle
4 Lifecycle Approaches
References

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

Introduction
Related works
System Evaluation and Results
Conclusion

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

3 Results
4 Conclusions

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

4. Method
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

1. Introduction
2. The pitfalls in detecting generative AI output
3. Detectors are not useful
4. Teach critical usage of AI

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
5 System design of intelligence
6 Measuring intelligence
7 Mathematically modeling intelligence
8 Consciousness
10 Exceeding human intelligence
11 Control of intelligence
12 Large language models and Generative AI
14 Wrong numbers
15 Final thoughts

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

Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site

Abstract
II. Background
IV. Guidelines for promoting ethical responsibility

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

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
Appendix A Assessing the Risks of AI Misuse in Scientific Research
Appendix B Details of Risks Demonstration in Chemical Science
Appendix C Detailed Implementation of SciGuard

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

General Discussion
Moral Factors
References

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

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
Artificial intelligence – concept and ethical background
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
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

3 Materials and methods
4 Results
5 Discussion
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

3 Taking a Step Forward
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

1 Introduction
2 Related Work
3 Problem Formulation
4 Learning Human Morality Judgments
5 Representational Alignment Supports Learning Multiple Human Values
6 Discussion

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

II. Theoretical background and hypotheses
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

Abstract
Introduction
Results
Discussion
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

Abstract
1. Introduction
2. Foundations of AI-driven threat intelligence
3. Autonomous threat hunting: conceptual framework
4. State-of-the-art AI techniques in autonomous threat hunting
5. Challenges in autonomous threat hunting
6. Case studies and applications
7. Evaluation metrics and performance benchmarks
8. Future directions and emerging trends
9. Conclusion
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

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

2. The generation of synthetic data
3. The usage of synthetic data
4. Risks and Challenges in Utilizing Synthetic Datasets for AI

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
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

Results
Discussion

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
IV. Concluding Remarks
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
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

1 Introduction
2 Background
4 Results
5 Discussion
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
5 Discussion
6 Conclusion
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

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

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
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
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

Abstract
1 Introduction
2 Generation
3 Detection
4 Tools
5 Discussion
6 Conclusion
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
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

3. Research study
4. Findings
5. Discussion
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

1. Introduction
3. Methodology
4. Discussion
References
B. An Example Dialog With Sentiment Analysis
C. ROSE: Tool and Data ResOurces to Explore the Instability of SEntiment Analysis Systems

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

Abstract
1 Introduction
2 Related work and our approach
3 Methods: case-based expert deliberation
4 Results
5 Discussion
References

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

1 Introduction
2 Background
3 State of the practice
4 The POLARIS framework
5 POLARIS framework application
6 Limitations
7 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

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
4 Challenges, Threats and Limitations
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
Results
Discussion
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
3. AIcon2abs Instructional Unit
4. Results
5. Conclusion

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

Abstract
1 Introduction
2 Related Work
3 Awareness in LLMs
4 Awareness Dataset: AWAREEVAL
5 Experiments
6 Conclusion
A AWAREEVAL Dataset Details
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

3 Results
4 Discussion
References
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

Abstract
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

Abstract
1 Introduction
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
I. Introduction
II. Background and Related Work
III. Unified Evaluation Framework For LLM Benchmarks
IV. Technological Aspects
V. Processual Elements
VI. Human Dynamics
VII. Discussions
VIII. Conclusion
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

2 Related Work
3 The AIGC Copyright Dilemma: A What-if Analysis
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

2. Emergence of Free-Formed AI Collectives
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

2 Related Work
3 Model of Civilization Evolution
4 CosmoAgent Architecture
5 Experiment Design
6 Results and Evaluation
7 Conclusion
A Appendix

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
Results
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

Abstract
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
5 There is no community without common language and communication
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

Abstract
1 Introduction
2 Background
3 Materials and Methods
4 Analysis
5 Results
6 Discussion
References
Appendix 1 Scenarios

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

I. Introduction
II. The AI-Powered Development Life-Cycle in Autonomous Vehicles
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
VI. AI and Learning Algorithms Statistics for Autonomous Vehicles
References

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

2 The Suitability of Generative AI for Newsroom Tasks
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
1. Introduction
2. Background
3. Methods
4. Results
5. Discussion
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
References
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

Abstract
1 Motivation & Background
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 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
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
I. Introduction & Motivation
II. Background & Literature Review
III. The AI-Enhanced CTI Processing Pipeline
IV. Challenges and Considerations
V. Conclusions & Future Research

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

2 AI Model Improvements with Human-AI Teaming
3 Effective Human-AI Joint Systems
4 Safe, Secure and Trustworthy AI
5 Applications
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

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

Abstract
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

Abstract
1. Introduction
4. Methods
5. Results
References

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
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

1 Introduction
2 Related Work
4 Informational Fairness
5 Representational Fairness
6 Ethics and Morality
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
2 Theoretical Background
3 Research Methodology
4 Results of the Systematic Literature Review
5 Towards Privacy- and Security-Aware Framework for Ethical AI
6 Discussion and Limitations

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

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

Abstract
2 Related Work
3 Method
4 Experiment
6 Limitations
__ The present study possesses certain limitations, specifically including the following: • Sole reliance on Chinese datasets without validation of feasibility on other languages. • Exclusive use of legal cases from the PRC, without addressing applicability in other legal systems. • The evaluation aspects may not be comprehensive, given the vast scope of legal ethics, with only a partial coverage attempted. • There is potential for expanding the number of LLM evaluated.
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

Abstract
AI Ethics Development Phases Based on Keyword Analysis
Key AI Ethics Issues
Limitations and Conclusion
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

Abstract
Introduction
Methodology
Data
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
7 Explainable AI as an Enabler of Trustworthy AI
8 Implementation Framework
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 Business Self-Regulation
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

3 Conceptualizing Fairness and Bias in ML
5 Ways to mitigate bias and promote Fairness
6 How Users can be affected by unfair ML Systems
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

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

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
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

Abstract
1 Introduction
2 Non-discrimination law vs. algorithmic fairness
References
A Appendix

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
7. Artificial intelligence Liability
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

Abstract
1 Introduction
2 Applications of Large Language Models in Legal Tasks
3 Fine-Tuned Large Language Models in Various Countries and Regions
4 Legal Problems of Large Languge Models
6 Conclusion and Future Directions
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
2 What is a Language Model?
4 Specific Large Language Models
5 Vision Models and Multi-Modal Large Language Models
6 Model Tuning
7 Model Evaluation and Benchmarking
8 Conclusions

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

Abstract
I. Introduction
II. Background and Related Work
III. Study Design
IV. Results
V. Discussion
VI. Threats to Validity
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

Abstract
1 Introduction
4 Findings

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

Abstract
I. Introduction
III. Proposed Design: IBIS
IV. Detailed Construction
VI. Evaluation
VII. Conclusion
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
Polarised Responses
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
1 Introduction
2 Background
3 Methodology
4 Critical Survey
References

AI Alignment: A Comprehensive Survey / 2310.19852 / ISBN:https://doi.org/10.48550/arXiv.2310.19852 / Published by ArXiv / on (web) Publishing site

Abstract
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

3 Remote Biometric Identification and the AI Act
4 Public Opinion on AI Governance
8 Conclusion
References

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

2 Related Work
3 Generative Ghosts: A Design Space
4 Benefits and Risks of Generative Ghost
5 Discussion

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

Abstract
1 Introduction
3 Automated Model Cards: Legitimacy via Quantified Objectivity
5 Alternative AI Ethics: Space for Embodied Complaints
6 Conclusions: Towards Humble Technical Practices
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

Abstract
Background
Ethical considera5ons
Sustainability considera5ons
Recommenda5ons
Conclusion
About the authors

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

2 Background and Related Work
3 Methodology
References

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

Abstract
I. Introduction
II. Literature Review
III. Proposed Methodology
V. Conclusion

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
4 The Machines Like us Argument: Mistaking the Map for the Territory
8 The Troubling Implications of Legal Rationales for Robot Rights
9 The Enduring Irresponsibility of AI Rights Talk
References

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

1 Introduction
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
3 A Geo-Political AI Risk Taxonomy
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

Abstract
1 Introduction
5 Limitations
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

Abstract
3 LLM Infrastructure
4 LLM Lifecycle
5 Downstream Ecosystem
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

1 Introduction
3 3 Governance for safety
4 4 Auditing standards body, not standard audits
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

1 Introduction
3 Case Study #1: Linguistic Features of Emotion
4 Qualifying and Quantifying Ethics
5 Concluding Remarks

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

Abstract
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
5 Concluding Remarks
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

Abstract
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
V. Conclusion
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

Abstract
1 Introduction
2 Mechanistic Agency: A Common View in AI Practice
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

Abstract
1 Introduction
2 Towards Ethical and Engaging AI Interfaces for Children: a Comprehensive Framework
4 Metrics for Assessing Trustworthiness, Reliability, and Safety in Human-AI Interaction
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
4 Building Towards Better Governance of Government AI
References

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

Abstract
Findings
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

II. Discrimination in Law
III. Prevalent Algorithmic Fairness Definitions
IV. Criteria for the Selection of Fairness Methods
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

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
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

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

Abstract
1. Introduction
2. Current State of AWS
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

I. Introduction
II. Conceptualization: Responsible AI
IV. Bibliometric Portraits of Responsible AI
References

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

1 Introduction
2 Related Work
3 Method
4 Results
5 Discussion

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

Abstract
1 Introduction
2 Motivation
3 Proposed Organizational Forms
4 Interaction Mechanisms
5 Governance and Organization
6 Unified Legal Framework
7 Conclusion
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

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

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

I. Introduction
II. Trustworthy AIGC in 6G Network
III. Adversarial of AIGC Models in 6G Network
IV. Privacy of AIGC in 6G Network
VII. Challenges and Future Research Directions

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

1 Introduction
2 Related Work
4 Method for Generating Responsible AI Guidelines
5 Evaluation of the 22 Responsible AI Guidelines
6 Discussion
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
1 Introduction
2 Related Work
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

Abstract
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
5. Conclusions and prospects
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

Social-interactional harms
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
A Dimensions of AGI: a Summary

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

2 Related Work
6 Taxonomy of Harms
7 Discussion
References
A Appendix

The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative / 2402.14859 / ISBN:https://doi.org/10.48550/arXiv.2402.14859 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
4. Experiments
5. Conclusion

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

3. What Are the Collective Decision Problems and their Alternatives in this Context?
8. How Should We Account for Behavioral Aspects and Human Cognitive Structures?
10. Conclusion
Impact Statement
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
Appendix
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

Abstract
1 Introduction
2 Related Work
3 Quantitative Models of Emotions, Behaviors, and Ethics
4 Pilot Studies
Limitations
References
Appendix S: Multiple Adversarial LLMs
Appendix C: Z. Sayre to F. S. Fitzgerald w/ Mixed 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
4 Validation Using Topic Modeling
5 Discussion and Limitations
6 OpenAI Updates on Policies and Model Capabilities: Implications for Thematic Analysis
7 Conclusion
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

Abstract
1 Introduction
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?
5 Conclusions and Outlook
6 Ethical Disclaimer and 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

4.Error Analysis
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

1 Introduction
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
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

Abstract
1 Introduction
2 Related Work
3 The Audit Procedure
4 Conducting the Pilots
5 Lessons Learned from the Pilots
6 Conclusion and Outlook
References
D Lifecycle Mapping of Pilot 1

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

Abstract
I. Introduction
II. Threat Intelligence
III. Vulnerability Assessment
IV. Network Security
V. Privacy Preservation
VI. Awareness
VII. Cyber Security Operations Automation
VIII. Ethical LLMs
IX. Challenges and Open Problems
X. Conclusions
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

Methods in clinical AI fairness research
Discussion
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

2 Understanding what can DALL-E 2 actually do
5 Technology and society, a complex relationship
References

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

1. Introduction
2. Anticipated AI Use for Children
3. Discussion
Bibliography

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
3. Method
4. Quantitative Results
5. Interview Results: Opportunities and Concerns of Using LLMs in the Frontline
6. Discussion
A. Appendix

Responsible AI for Earth Observation / 2405.20868 / ISBN:https://doi.org/10.48550/arXiv.2405.20868 / Published by ArXiv / on (web) Publishing site

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
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

1 Introduction
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

2 Preliminary Analysis
3 ML model construction
4 Fairness violation analysis in BRIO
6 Risk analysis via BRIO for the German Credit Dataset
7 Revenue analysis
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
References
Appendix A. Terminology

MoralBench: Moral Evaluation of LLMs / 2406.04428 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related Work
3 Benchmark and Method
4 Experiments
References

Can Prompt Modifiers Control Bias? A Comparative Analysis of Text-to-Image Generative Models / 2406.05602 / Published by ArXiv / on (web) Publishing site

2. Related Work
3. Bias Evaluation
5. Results
6. Discussion
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

Abstract
2 Theories and Components of Deception
3 Reductionism & Previous Research in Deceptive AI
4 DAMAS: A MAS Framework for Deception Analysis
References

The Impact of AI on Academic Research and Publishing / 2406.06009 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction

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
6 Conclusions and Recommendations
References
Appendix B: Collected data summary

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?
3 Potential Misuse and Security Concerns
4 Towards Ethical Mitigation: A Proposed Methodology
6 Ethical Response to LLM Attacks
References

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

4 Global Regulatory Landscape of AI
5 Generative AI: The New Frontier
6 Results and Conclusion
7 Future Directions
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

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

Abstract
1 Introduction
2 Background and related work
3 Methodology
4 Results
5 Limitations

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
V. Conclusion

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

Abstract
I. Introduction
II. Selection of application
III. Analysis
IV. Conclusion
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

Abstract
Introduction
1. Beyond Bias and Fairness
3. Ensuring Equitable Access to AI Technologies
5. Promoting Global Solidarity
6. Ensuring Sustainable AI Development
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
3 CHALLENGES AND OPPORTUNITIES OF USING CONVERSATIONAL AGENTS IN GROUP DESIGN
4 POTENTIAL SCENARIO AND APPLICATIONS OF CONVERSATIONAL AGENTS IN GROUP DESIGN PROCESS
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
1 Introduction
2 Large Language Model Risks
3 Strategies in Securing Large Language models
4 Challenges in Implementing Guardrails
5 Open Source Tools
7 Conclusion
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

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
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
3 METHODOLOGY AND STUDY DESIGN
4 RESULTS
5 DISCUSSION AND IMPLICATIONS
6 THREATS TO VALIDITY
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

Abstract
2 Background
3 Limitations of RLxF
4 The Internal Tensions and Ethical Issues in RLxF
5 Rebooting Safety and Alignment: Integrating AI Ethics and System Safety
References

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
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

Art Practice: Human Reactions to Synthetic Fake Content
Emphasizing Reasoning Over Detection

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
III. CRITICAL ANALYSIS
IV. SECGENAI FRAMEWORK REQUIREMENTS SPECIFICATIONS
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

1. Introduction
2. Artificial intelligence as Weberian rationalization
4. AI-driven tax policy to reduce economic inequality: a thought experiment
6. Conclusion
References

A Blueprint for Auditing Generative AI / 2407.05338 / ISBN:https://doi.org/10.48550/arXiv.2407.05338 / Published by ArXiv / on (web) Publishing site

2 Why audit generative AI systems?
3 How to audit generative AI systems?
4 Governance audits
5 Model 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
3 Practical implementation challenges | What to be prepared for?
6 References

Operationalising AI governance through ethics-based auditing: An industry case study / 2407.06232 / Published by ArXiv / on (web) Publishing site

2. The need to operationalise AI governance
3. AstraZeneca and AI governance
6. Lessons learned from AstraZeneca’s 2021 AI audit
7. Limitations
REFERENCES
APPENDIX 1

Auditing of AI: Legal, Ethical and Technical Approaches / 2407.06235 / Published by ArXiv / on (web) Publishing site

1 Introduction
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
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

1 Introduction
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 1

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

Abstract
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
V. Conclusion

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

Abstract
1 Introduction
2 Background
3 Conceptual Foundations
4 Design Framework
5 Case Studies
6 Discussion
7 Conclusion
Limitations

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

I. Introduction
II. Background and Definitions
III. Method
IV. Evolution of Affective Robots for Well-Being
V. 10 Years of Affectivbe Robotics

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

Abstract
1 Introduction
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

1 Introduction
2 Literature Review
3 Methodology
4 Data Analysis and Results
5 Discussion
6 Conclusion

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
A brief history of AI and generative AI
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

Abstract
1 Introduction
3 Giraffe and Acacia: Reciprocal Adaptations and Shaping
4 Generative AI and Humans: Risks and Mitigation
5 Meta Analysis: Limits of the Analogy
6 Discussion
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

Abstract
Introduction
Proposed Approach to Determining High-Consequence Biological Capabilities of Concern
Next Steps for AI Biosecurity Evaluations

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
2. Ethics Frameworks
3. AI Institutes and Society

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

Abstract
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
3. OAK Dataset
4. Automatic Prompt Generation
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

II. Background
III. Methodology
IV. Results
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
3 Examples of Biases
5 Principles for the Nudge Lifecycle
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

Abstract
4 Mapping Individual, Social, and Biospheric Impacts of Foundation Models
References
A Appendix

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

Introduction
Artificial companions

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

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

4. Passive Deepfake Authentication Methods
5. Deepfakes Detection Method on Realistic Scenarios
6. Active Authentication
References

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

Abstract
1 Introduction
2 Background and Literature Review
3 Methodology
4 ESG-AI framework
5 Discussion
6 Conclusion
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

1 Introduction
2 Background and Related Work
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

2 Related Work
4 Large-Scale Surveys of AI in the Literature
5 Discussion
References
A Known Limitations of Surveys
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

Abstract
1. Introduction
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
VI. Conclusion
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

1 Preliminary notes
3 Critical Reflection on AI Risks
4 Exploring epistemic challenges

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

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

1 Introduction
2 Methodology & Guidelines
3 Data Sources
4 Data Preparation
6 Model Training
7 Environmental Impact
8 Model Evaluation
9 Model Release & Monitoring
References

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

Abstract
I. Introduction
II. Generative AI
III. Language Modeling
IV. Challenges of Generative AI and LLMs
V. Bridging Research Gaps and Future Directions
References

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

Abstract
I Introduction
3 Method
4 Experiment

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
3 Visualization Atlas Design Patterns
4 Interviews with Visualization Atlas Creators
6 Key Characteristics of Visualization Atlases
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

Avoiding harm
Responsible disclosure of vulnerabilities
Accurate Reporting and Reproducibility
Use of Generative AI in CS Conference Publications
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
3. Practical and Strategic Benefits of Using AI in Arbitration
Part II. The Critics are Killing the Baby
1. Resistance Against AI Does Not Offer Conclusive Reasons for Outright Rejection
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

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
Findings
Discussion
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

1 Main
2 Promises
3 Challenges
5 Conclusion and Future Directions
References
Tables

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

Summary
1 Introduction
3 European Union AI Act: a brief overview
4 Compliance and implementation of the suggested assessments
5 Overall Ethical Requirements (O)
6 Fairness (F)
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

Abstract
1. Introduction
2. Literature Review
4. Experiment Implementation, Results and Analysis
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

II. Related Work
III. Generative AI
IV. Attack Methodology
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

3 Multimodal Medical Studies
4 Contrastice Foundation Models (CFMs)
5 Multimodal LLMs (MLLMs)
6 Discussions of Current Studies
7 Challenges and Future Directions
References

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

Abstract
1 Introduction
2 Related Work
3 Methodology
4 Background
5 Explanation Requirements and Legal Explanatory Goals
6 A Categorisation of XAI in Terms of Explanatory Goals
8 Instructions for Use & Discussion of Findings
9 Threats to Validity
10 Conclusion
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

Introduction
“Fine cuts” of Empathy: Capabilities and Distinctions under the Empathy Umbrella
What Empathic Capabilities Do AIs Need?
Implications for AI Creators and Users
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

Abstract
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
6 Open Challenges
7 Guidelines and Recommendations
8 Conclusion and Final Remarks
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

Abstract
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

Abstract
1. Introduction
2. The Experimentation Bottleneck
3. How GenAI Could Make a Difference
4. Risks and Caveats
5. Annoyances or Dealbreakers?
6. Conclusion
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

Practical considerations for ethical actions in complexity science
Conclusion
References

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

Introduction
Background
Results
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

4 Findings

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

1 Introduction
2 Prior Benchmarks
3 Data Details
4 LLM Services (Infrastructure)
9 Conclusion & Future Work
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

Abstract
Introduction
Reflections from two workshop participants
Discussion and conclusion

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

D. CausalRating: A Tool To Rate Sentiments Analysis Systems for Bias

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

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

1 Introduction
2 A Creative Journey from Ada Lovelace to Foundation Models
3 Large Language Models and Boden’s Three Criteria
4 Easy and Hard Problems in Machine Creativity
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
9 Limitations
B Experiment Setup Details

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
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: Ethics (the stereotype
The complex reality: Where Ethics and Alignment (actually) differ
The complex reality: Where Ethics and Alignment (actually) are similar
The complex reality: Complication: Good and bad ideas can be knotted together
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

1 Introduction
2 Foundation Models
3 Foundation Models in Healthcare
4 Multi-Modal Data Fusion
5 Data Quantity
6 Data Annotation
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
Discussion

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
3 Methodology
4 Challenges
5 Future Directions

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

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

Language models as human participants
Six fallacies that misinterpret language models
Using language models to simulate roles and model cognitive processes
Concluding remarks

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

Abstract
I. Introduction
II. Conceptualization and frameworks
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

Abstract
3 Research Design
4 Results
5 Open Challenges and Future Research Directions (RQ5)
6 Discussions
7 Threats to Validity
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

1 Related Work
2 Methodology
5 Discussion
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
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
3 Case Studies in AI-Enabled Optimization
4 Lessons Learned from the Case Studies
5 Conclusion
References
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

1 Introduction
3 Method
5 Discussion
6 Conclusion
References

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

Abstract
Data and Results
Middle-aged and elders’ representation
Conclusion

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

Abstract
2 Background and Related Work
4 Effects of Ad Injection on LLM Performance
5 User Study Methodology
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

3 XTRUST Construction
4 Experiments
5 Conclusion

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
2 Views on Intelligence
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
6. Conclusion

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
2 Systematic Reviews
5 Aims & Objectives (RQ1)
6 Methodologies & Capabilities (RQ2)
7 Limitations & Considerations (RQ3)
8 Discussion
References

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

II. Related Work
III. Current Platform Measures
V. Results

Safety challenges of AI in medicine / 2409.18968 / ISBN:https://doi.org/10.48550/arXiv.2409.18968 / Published by ArXiv / on (web) Publishing site

Abstract
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
5 Conclusion
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
A Benchmarks in Open LLM Leaderboard
B Service-ready Features and Identifiers

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
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
II. Background
IV. Results
VI. Threats to Validity
References
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
V. Proof of Concepts 2
VI. Collaborative Network
VII. Evaluations and Experiments
References

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
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

Literature Review
Methodology
Results
Discussion
Conclusion
Ethical considerations
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

4 Experimental Setup
5 Results
6 Conclusion
Appendices

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

2. Related Work
3. Method
References

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
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

Abstract
I. Introduction
II. Related Work
III. Method
IV. Results
V. Discussion
VI. Threats to Validity
VII. Conclusion
References

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
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

Abstract
1 Introduction
2 Measuring Explainability
3 An objective Methodology for evaluating XAI
5 Discussion
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

4 Cultural safety dataset
5 Experimental setup
6 Main results on evaluation set

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

3 Misunderstanding the nature of general moral theories
References

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”
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
References

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
2 Ethics of Resisting LLM Inference
3 Threat Model
5 Experiments
6 Discussion
References

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
2 Background and Related Works
3 Methodology PCJAILBREAK
4 Experiment
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

1 Introduction
2 Related Work
3 Methodology
4 Analysis
5 Future Work and Discussion
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

2 Background and Related Work
4 Study Setup
5 RQ1: Evolution of the Opinions Towards AI Tools
6 RQ2: Practices of AI Tools
8 RQ4: Expectation and Confrontation Towards The Future
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

I. Introduction
II. Background and Concepts
III. Jailbreak Attack Methods and Techniques
IV. Defense Mechanisms Against Jailbreak Attacks
V. Evaluation and Benchmarking
VI. Research Gaps and Future Directions
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
3.0 Methodology
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

What Is AI & ML
Future Scope
Conclusion

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
Taxonomies of Harm Must be Vernacularized to be Operationalized
Overgeneral Taxonomies Can Compound Potential Harms
Vernacularization as a General AI Safety Operationalization Methodology
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

I. Introduction
III. Ethics Guidelines

Trustworthy XAI and Application / 2410.17139 / ISBN:https://doi.org/10.48550/arXiv.2410.17139 / Published by ArXiv / on (web) Publishing site

Abstract
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

3 Benchmark
4 Evaluation
6 Conclusion and Future work
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
Understanding Ethical Leadership
Ethical Challenges Presented by AI
Opportunities for Ethical Leadership in the age of AI
Framework for Ethical Leadership
The Importance of Interdisciplinary Collaboration
Case Studies of Ethical Leadership in AI
Recommendations for Leaders
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
Prompt engineering
Deployment considerations
Glossary
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
I. Introduction
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
VIII. Research Gaps and Future Directions
References

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
1 Introduction
2 Methods
4 Discussion
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
5 Discussion
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
4 Free Evolution, The Imperative and Intent
5 The Runaway AGI Evolutionary Gap
6 Conclusions

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
1 Introduction
2 Advanced Artificial Intelligence
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
8 Conclusion
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

1. Introduction
4. Conclusions

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
Defining Key Concepts
Theoretical Framework
Methodology
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
3 Research Considerations
4 Recommendations
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

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
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

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

Abstract
1. Introduction
2. AI chatbots in privacy and ethics research
3. Method
5. Discussion

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

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
6. Conclusion
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

1 Introduction
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

References

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

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

References

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

Abstract
1 Introduction
2 Related Work
3 Properties of XAI-Methods (Possibly) Relevant for their Legal Use
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

2. Clinical, Technical, and Ethical Concerns
3. Methods
6. Conclusion

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

2 Methods
3 Results
4 Discussion
5 Conclusion

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

Results
Discussion
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
2. Objectives of the study
3. Literature review
5. Methodology
6. Data Collection Method
7. Case Studies:
9. Conclusion
10. Future research:
11. Recommendations for Implementation of AI-based Assistive Technologies in Indian Libraries
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

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

Abstract
1 Introduction
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

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
3 Transformer Architecture
5 Empirical Result
6 Content
7 Response Accuracy
8 Ethical Issues
10 Limitations
11 Future Work
12 Conclusion

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

Abstract
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
VII. Metrics for Evaluating AI-Driven Multimodal UIs
VIII. Conclusion

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
4. Bias Evaluation
5. Bias Mitigation

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

Abstract
1. Introduction
2. Method

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
II. Foundations of P2VAD
III. P2VAD with non -Identifiable Elements
IV. Desensitized Intermediate Modalities P2VAD
VI. Evaluation Benchmarks and Metrics
VII. Discussion

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

2 Theoretical Framework
3 Literature Review
6 Ethical Implications of Generative AI in Education
9 Future Work
10 Proposed Policy Recommendations
11 Conclusion

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

2 Harms in forecasting
3 Methods
4 Findings: typology of harm in forecasting
5 Discussion
6 A Research agenda
7 Conclusions
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
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

Abstract
3. Textual Generation Experiment
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

II. Literature Review
IV. Method
V. Analysis and Results

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

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
II. Context for AI
III. Key Considerations for AI Policy
IV. Framework for AI Policy Development
V. Conclusion
VI. Acknowledgments

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

Introduction
Ethics for AI in design
References

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)
IV. Tools and Methods for RAG
V. AI Text Detectors (AITD)
VI. Ethical Considerations
VII. Limitations
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
4. Future Prospects
5. Conclusion
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

Abstract
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

Introduction
I. Key Concerns on 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

I Introduction
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
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
3 Taxonomy on LLM for Political Science
4 Classical Political Science Functions and Modern Transformations
5 Technical Foundations for LLM Applications in Political Science
6 Future Directions & Challenges
7 Conclusion
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

Abstract
I. Introduction
II. Method
III. Findings
References

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

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

2. Digital Citizenship: from Individualised to Stereotyped Identities
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
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

CERN for AI: A Theoretical Framework for Autonomous Simulation-Based Artificial Intelligence Testing and Alignment / 2312.09402 / ISBN:https://doi.org/10.48550/arXiv.2312.09402 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
Methods
Establishing a framework for interactions in an autonomous digital city
Creating elements of an autonomous digital city
Discussion
Conclusion
References

Reviewing Intelligent Cinematography: AI research for camera-based video production / 2405.05039 / ISBN:https://doi.org/10.48550/arXiv.2405.05039 / Published by ArXiv / on (web) Publishing site

2 Technical Background
3 Intelligent Cinematography in Production
4 Concluding Remarks

Shaping AI's Impact on Billions of Lives / 2412.02730 / ISBN:https://doi.org/10.48550/arXiv.2412.02730 / Published by ArXiv / on (web) Publishing site

Introduction
II. Demystifying the Potential Impact on AI
III. Harnessing AI for the Public Good
Appendices

Intelligent Electric Power Steering: Artificial Intelligence Integration Enhances Vehicle Safety and Performance / 2412.08133 / ISBN:https://doi.org/10.48550/arXiv.2412.08133 / Published by ArXiv / on (web) Publishing site

Abstract
II. Review of Existing Research
III. AI Integration in EPS: Safety and Performance Enhancement
IV. Effects on Vehicle Safety Through AI in EPS
V. Performance Capabilities of AI-Driven EPS
VI. Conclusion and Future Strategy
References

AI Ethics in Smart Homes: Progress, User Requirements and Challenges / 2412.09813 / ISBN:https://doi.org/10.48550/arXiv.2412.09813 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Background
3 Smart Home Technologies and AI Ethics
4 AI Ethics from User Requirements' Perspective
5 AI Ethics from Technology's Perspective
6 Challenges
7 Conclusions
References

Research Integrity and GenAI: A Systematic Analysis of Ethical Challenges Across Research Phases / 2412.10134 / ISBN:https://doi.org/10.48550/arXiv.2412.10134 / Published by ArXiv / on (web) Publishing site

Introduction
Research Phases and AI Tools
Discussion
Bibliography

On Large Language Models in Mission-Critical IT Governance: Are We Ready Yet? / 2412.11698 / ISBN:https://doi.org/10.48550/arXiv.2412.11698 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
II. Study Design
III. Results
IV. Discussions
V. Threats to Validity
VI. Related Works
VII. Conclusions
References

Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity / 2412.12108 / ISBN:https://doi.org/10.48550/arXiv.2412.12108 / Published by ArXiv / on (web) Publishing site

Our Response
References

Bots against Bias: Critical Next Steps for Human-Robot Interaction / 2412.12542 / ISBN:https://doi.org/10.1017/9781009386708.023 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Track: Robots against Bias
3 Track: Against Bias in Robots

Clio: Privacy-Preserving Insights into Real-World AI Use / 2412.13678 / ISBN:https://doi.org/10.48550/arXiv.2412.13678 / Published by ArXiv / on (web) Publishing site

2 High-level design of Clio
4 Clio for safety
5 Limitations
6 Risks, ethical considerations, and mitigations
7 Related work
References
Appendices

User-Generated Content and Editors in Games: A Comprehensive Survey / 2412.13743 / ISBN:https://doi.org/10.48550/arXiv.2412.13743 / Published by ArXiv / on (web) Publishing site

Abstract
I. Introduction
II. Related Work
IV. User-Generated Content Editor
V. Discussion
VI. Conclusion
References

Understanding and Evaluating Trust in Generative AI and Large Language Models for Spreadsheets / 2412.14062 / ISBN:https://doi.org/10.48550/arXiv.2412.14062 / Published by ArXiv / on (web) Publishing site

Abstract
1.0 Introduction
2.0 Trust in Automation
3.0 Conclusions and Areas for Future Research
References

Towards Friendly AI: A Comprehensive Review and New Perspectives on Human-AI Alignment / 2412.15114 / ISBN:https://doi.org/10.48550/arXiv.2412.15114 / Published by ArXiv / on (web) Publishing site

I. Introduction
III. Theoretical Perspectives
IV. Applications
V. Challenges and Suggestions
References

Autonomous Vehicle Security: A Deep Dive into Threat Modeling / 2412.15348 / ISBN:https://doi.org/10.48550/arXiv.2412.15348 / Published by ArXiv / on (web) Publishing site

I. Introduction
II. Autonomous Vehicles
III. Autonomous Vehicle Cybersecurirty Attacks
IV. Overview of Threat Modelling
V. Stride & Dread Threat Model for Autonomous Vehicles Architecture
VI. Comparative Analysis of Threat Modeling Frameworks for Autonomous Vehicles
VII. Legal and Ethical Considerations in Autonomous Vehicle Security
VIII. Future Direction and Discussion

Navigating AI to Unpack Youth Privacy Concerns: An In-Depth Exploration and Systematic Review / 2412.16369 / ISBN:https://doi.org/10.48550/arXiv.2412.16369 / Published by ArXiv / on (web) Publishing site

Abstract
III. Results
IV. Discussion
V. Conclusion
References

Ethics and Technical Aspects of Generative AI Models in Digital Content Creation / 2412.16389 / ISBN:https://doi.org/10.48550/arXiv.2412.16389 / Published by ArXiv / on (web) Publishing site

2 Literature Review
3 Methodology
4 Results
5 Discussion
References
Appendices

Large Language Model Safety: A Holistic Survey / 2412.17686 / ISBN:https://doi.org/10.48550/arXiv.2412.17686 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Taxonomy
3 Value Misalignment
4 Robustness to Attack
5 Misuse
6 Autonomous AI Risks
7 Agent Safety
8 Interpretability for LLM Safety
9 Technology Roadmaps / Strategies to LLM Safety in Practice
10 Governance
11 Challenges and Future Directions
12 Conclusion
References

Self-Disclosure to AI: The Paradox of Trust and Vulnerability in Human-Machine Interactions / 2412.20564 / ISBN:https://doi.org/10.48550/arXiv.2412.20564 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Trust in Human-Machine Interaction
3 The Psychology of Confiding and Self-Disclosure
4 Technological Philosophy and Ethics
5 Conclusion
References

Autonomous Alignment with Human Value on Altruism through Considerate Self-imagination and Theory of Mind / 2501.00320 / ISBN:https://doi.org/10.48550/arXiv.2501.00320 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Results
3 Discussion
4 Methods
Appendices
References

Generative AI and LLMs in Industry: A text-mining Analysis and Critical Evaluation of Guidelines and Policy Statements Across Fourteen Industrial Sectors / 2501.00957 / ISBN:https://doi.org/10.48550/arXiv.2501.00957 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
II. Methodology
III. Qualitative Findings and Resultant Themes
V. Discussion and Synthesis
VI. Concluding Remarks and Future Directions
References

Implications of Artificial Intelligence on Health Data Privacy and Confidentiality / 2501.01639 / ISBN:https://doi.org/10.48550/arXiv.2501.01639 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
HIPAA Overview
AI and Machine Learning in Healthcare
Legal Implications of AI in Healthcare
Conclusion
References

INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models / 2501.01973 / ISBN:https://doi.org/10.48550/arXiv.2501.01973 / Published by ArXiv / on (web) Publishing site

3 Preliminaries
4 Method
5 Experiments & Results
References

Curious, Critical Thinker, Empathetic, and Ethically Responsible: Essential Soft Skills for Data Scientists in Software Engineering / 2501.02088 / ISBN:https://doi.org/10.48550/arXiv.2501.02088 / Published by ArXiv / on (web) Publishing site

I. Introduction
II. Background
IV. Findings
V. Discussions
VI. Conclusion
References

Trust and Dependability in Blockchain & AI Based MedIoT Applications: Research Challenges and Future Directions / 2501.02647 / ISBN:https://doi.org/10.48550/arXiv.2501.02647 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
Scene Setting
Ten Challenges & Future Research Directions
In The Field: Perspectives from Patients and Health Practitioners
References

Human-centered Geospatial Data Science / 2501.05595 / ISBN:https://doi.org/10.48550/arXiv.2501.05595 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
2. Understanding Human Experiences
3. Prioritize Human Values with Ethical Discussions and Practices
4. Conclusions

Datasheets for Healthcare AI: A Framework for Transparency and Bias Mitigation / 2501.05617 / ISBN:https://doi.org/10.48550/arXiv.2501.05617 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
2. Literature Review
3. Developing an Improved Machine-Readable Datasheet
5. Conclusion & Future Work

Concerns and Values in Human-Robot Interactions: A Focus on Social Robotics / 2501.05628 / ISBN:https://doi.org/10.48550/arXiv.2501.05628 / Published by ArXiv / on (web) Publishing site

2 Related Work
3 Phase 1: Scoping Review
4 Phase 2: Focus Groups
5 Phase 3: Design and Evaluation of the HRI- Value Compass
6 General Discussion and Conclusion
References
Appendices