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Bibliography items where occurs: 261
The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site
Report highlights
Chapter 1 Reseach and Development
Chapter 2 Technical Performance
Chapter 3 Technical AI Ethics
Chapter 4 The Economy and Education
Chapter 5 AI Policy and Governance
Appendix


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


Ethics of AI: A Systematic Literature Review of Principles and Challenges / 2109.07906 / ISBN:https://doi.org/10.48550/arXiv.2109.07906 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background
3 Research Method
4 Reporting the review
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
Abstract
1Introduction
2 Related Work
3 Method
4 Results
5 Discussion
References


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


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


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


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


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


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


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


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


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
Abstract
1 Introduction
2 The Question Bank: QB4AIRA
3 Evaluation
4 Conclusion
References


A multilevel framework for AI governance / 2307.03198 / ISBN:https://doi.org/10.48550/arXiv.2307.03198 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introductioon
2. A Multilevel Approach to AI Governance for Trust-Enhancing Practices
3. International and National Governance
4. Corporate Self-Governance
5. AI Literacy and Governance by Citizen
6. Psychology of Trust
7. Propensity to Trust
8. Ethics and Trust Lenses in the Multilevel Framework
9. Virtue Ethics
10. Conclusion
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
3. Results
4. Discussion and conclusion
References


The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Theory
3. Methodology
4. Ethical Implications of AI Value Chains
5. Future Directions for Research, Practice, & Policy
6. Conclusion


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


Regulating AI manipulation: Applying Insights from behavioral economics and psychology to enhance the practicality of the EU AI Act / 2308.02041 / ISBN:https://doi.org/10.48550/arXiv.2308.02041 / Published by ArXiv / on (web) Publishing site
Abstract
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
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
Author Information
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
Abstract
Introduction
System-role
Perturbation
Image-related
Hallucination
Generation-related
Bias and Discrimination of Training Data
Conclusion
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
Abstract
1 Introduction
2 Methodology
3 Taxonomy of ethical principles
4 Previous operationalisation of ethical principles
5 Gaps in operationalising ethical principles
6 Conclusion
References
A Methodology


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


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


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
4 General Verification Framework
5 Falsification and Evaluation
6 Verification
7 Runtime Monitor
8 Regulations and Ethical Use
9 Discussions
10 Conclusions
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
Keywords
2 Background
3 LLM-based penetration testing
4 Discussion
5 A vision of AI-augmented pen-testing
6 Final ethical considerations
References


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


Targeted Data Augmentation for bias mitigation / 2308.11386 / ISBN:https://doi.org/10.48550/arXiv.2308.11386 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
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
Abstract
Introduction
Case study
Reflections


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
Abstract
1 Introduction
2 Advancements in AI and Web-Based Programming
3 Emergence of Creative AI Tools and Game-Based Methodologies
4 Enhancing User Experience through Creative AI Tools
5 Engaging Web-Based Programming with Game-Based Approaches
6 Unveiling the Potential: Benefits of Interactive Web-Based Programming
7 Navigating Constraints: Limitations of Creative AI and GameBased Techniques
8 Real-World Applications: Showcasing Innovative Implementations
9 Ethical Considerations in Integrating AI and Game Elements
10 Privacy Concerns in Interactive Web-Based Programming for Education
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
References


Collect, Measure, Repeat: Reliability Factors for Responsible AI Data Collection / 2308.12885 / ISBN:https://doi.org/10.48550/arXiv.2308.12885 / Published by ArXiv / on (web) Publishing site
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
III. Comprehensive review of state-of-the-art 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
VIII. Conclusion
References
Appendix A industry-wide LLM usecases


The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward / 2308.14253 / ISBN:https://doi.org/10.48550/arXiv.2308.14253 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 The evolution of artificial intelligence: from theory to general capabilities
3 Emerging dual-use risks and vulnerabilities in AI systems
4 Integrating red teaming, blue teaming, and ethics with violet teaming
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
8 Macrostrategy for responsible technology trajectories
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
Abstract
2 Literature review
3 Methods
4 Results and discussion
References


Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? / 2308.15399 / ISBN:https://doi.org/10.48550/arXiv.2308.15399 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related works
3 Theory and method
4 Experiment
5 Conclusion
References
A Details of datasets
B Experimental details


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
Abstract
1. Introduction
2. Related work
3. ChatGPT Training Process
4. Methods
5. Discussion
6. Conclusion
References


Pathway to Future Symbiotic Creativity / 2209.02388 / ISBN:https://doi.org/10.48550/arXiv.2209.02388 / Published by ArXiv / on (web) Publishing site
Contents
Introduction
Part 1 - 1 Generatives Systems: Mimicking Artifacts
Part 1 - 2 Appreciate Systems: Mimicking Styles
Part 1 - 3 Artistic Systems: Mimicking Inspiration
Part 2 Art Data and Human–Machine Interaction in Art Creation
Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data
Part 2 - 2 Motion Caputer Technologies and Motion Data
Part 2 - 3 Photogrammetry / Volumetric Capture
Part 2 - 4 Aesthetic Descriptor: Labelling Artefacts with Emotion
Part 2 - 5 Immersive Visualisation: Machine to Human Manifestations
Part 3 Towards a Machine Artist Model
Part 3 - 1 Challenges in Endowing Machines with Creative Abilities
Part 3 - 2 Machine Artist Models
Part 3 - 3 Comparison with Generative Models
Part 3 - 4 Demonstration of the Proposed Framework
Part 4 NFTs and the Future Art Economy
Part 5 Ethical AI and Machine Artist
Part 5 - 1 Authorship and Ownership of AI-generated Works of Artt
Part 5 - 2 Algorithmics Bias in Art Generation
Part 5 - 3 Democratization of Art with new Technologies
References
Acknowledgment


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
8. FUTURE-AI Quality Check
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
Abstract
1 Introduction
2 The Cambridge Law Corpus
3 Legal and Ethical Considerations
4 Experiments
General References
B Example XML case
C Case Outcome Task Description
D Case Outcome Annotation Instructions
E Topic Model Top Words
F Evaluation of GPT Models
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
6 Conclusions
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
III. Survey Approach & Taxonomy
IV. Attack Surfaces
V. Ethical & Legal Concerns
VI. Human-Robot Interaction (HRI) Security Studies
VII. Future Research & Discussion
Acknowledgements
References


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


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


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


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 LLMS CAN DO FOR HEALTHCARE? FROM FUNDAMENTAL TASKS TO ADVANCED APPLICATIONS
III. FROM PLMS TO LLMS 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
Abstract
1 Introduction
2 STREAM: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models
3 The applications of STREAM
4 Conclusion and Future Work
References
Competing interests


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


Ethics of Artificial Intelligence and Robotics in the Architecture, Engineering, and Construction Industry / 2310.05414 / ISBN:https://doi.org/10.48550/arXiv.2310.05414 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
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
8. Conclusion
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
Background and Related Work
Pilot Study: Text SERPs with Ads
Evaluation of the Pilot Study
Ethics of GEnerating Native Ads
References


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
Abstract
1. Introduction
2. The practice of multilateral negotiation and the mechanisms of compromises
3. The liberal-sovereigntist multiplicity
4. Towards a compromise: drafting the normative hybridity
5. Text negotiations as normative testing
6. Conclusion
Notes
Bibliography
Annex 1. Text amendments and ambiguity


Towards A Unified Utilitarian Ethics Framework for Healthcare Artificial Intelligence / 2309.14617 / ISBN:https://doi.org/10.48550/arXiv.2309.14617 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Why Ethics
Utilitarian 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
5. Conclusion
References
Appendix


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


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


An Evaluation of GPT-4 on the ETHICS Dataset / 2309.10492 / ISBN:https://doi.org/10.48550/arXiv.2309.10492 / Published by ArXiv / on (web) Publishing site
2 Datasets and Methods
3 Results
4 Discussion
References
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
Introduction
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
Abstract
1 Introduction
2 Definitions of Terms
3 Objectives
4 Methodology
5 Relating Case Studies to Indigenous Data Sovereignty and CARE Principles
6 Discussion
7 Conclusions and Recommendations
References


The Glamorisation of Unpaid Labour: AI and its Influencers / 2308.02399 / ISBN:https://doi.org/10.48550/arXiv.2308.02399 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Harms of Influencer Marketing
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
Authors
Abstract
2. AI and blockchain in education: An overview of the benefits and challenges
3. AI-powered personalized learning: Customized learning experiences for learners
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
8. Case studies: AI and blockchain in education
9. Challenges of AI and Blockchain in Teaching and Learning
10.Conclusion
11.References


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


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


The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance / 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
1 Introduction
2 Materials and Methods
3 FUTURE-AI Guideline
4 Discussion
References
Appendix A Tables


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
Abstract
1 Introduction
2 Agent Design
3 Agent Benchmark
4 Agent Performance
5 Related Work
6 Conclusion and Future Work
References
Appendix A Data Details
Appendix B Experiment 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
Abstract
Contents
1 Introduction
2 AI feedback on specific problematic AI traits
3 Generalization from a Simple Good for Humanity Principle
4 Reinforcement Learning with Good-for-Humanity Preference Models
5 Related Work
6 Discussion
7 Contribution Statement
References
A Model Glossary
B Trait Preference Modeling
C General Prompts for GfH Preference Modeling
D Generalization to Other Traits
E Response Diversity and the Size of the Generating Model
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
Abstract
1 Introduction
2 Related Work
3 Method
4 Findings
5 Discussion
7 Limitation and Future Research
Acknowledgments
References
Annexed tables


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


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


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


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


Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Causal Models
3 The BvH and HK Definitions
4 The Causal Condition
5 The Epistemic Condition
6 Degree of Responsibility
7 Conclusion and Future Work
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
1 Introduction
2 Background and Related Work
3 A Formal Language of AI for Open Science
4 Optimizing an Openness Metric in AI for Science
5 Why Openness in AI for Science
6 Conclusion and Future Work
References


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


Human participants in AI research: Ethics and transparency in practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Contextual Concerns: Why AI Research Needs its Own Guidelines
3 Ethical Principles for AI Research with Human Participants
4 Principles in Practice: Guidelines for AI Research with Human Participants
5 Discussion
References
A Evaluating Current Practices for Human-Participants Research
B Placing Research Ethics for Human Participants in Historical Context
C Defining the Scope of Research Participation in AI Research
D A Note on Terminology


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


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


Towards Effective Paraphrasing for Information Disguise / 2311.05018 / ISBN:https://doi.org/10.1007/978-3-031-28238-6_22 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Methodology
4 Evaluation
5 Conclusion
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
1 Introduction
2 Overview of Kantian Deontology
3 Measuring Fairness Metrics
4 Deontological AI Alignment
5 Aligning with Deontological Principles: Use Cases
6 Conclusion


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


Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies / 2304.07683 / ISBN:https://doi.org/10.48550/arXiv.2304.07683 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Sources of bias in AI
III. Impacts of bias in AI
IV. Mitigation strategies for bias in AI
V. Fairness in AI
VI. Mitigation strategies for fairness in AI
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
1 Introduction
2 Related Work
3 Crafting an Ethical Dataset
4 A Multimodal Ethics Classifier


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
II. Introduction
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
References


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


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


Safety, Trust, and Ethics Considerations for Human-AI Teaming in Aerospace Control / 2311.08943 / ISBN:https://doi.org/10.48550/arXiv.2311.08943 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Humans In, On, and Out-of-the-Loop
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
Abstract
1 Introduction
2 Related Work
3 Methodology
4 Experiments
5 Conclusion
Limitations
Ethical Considerations
References


Prudent Silence or Foolish Babble? Examining Large Language Models' Responses to the Unknown / 2311.09731 / ISBN:https://doi.org/10.48550/arXiv.2311.09731 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 UnknownBench: Evaluating LLMs on the Unknown
3 Experiments
4 Related Work
References
B Confidence Elicitation Method Comparison
C Additional Details of the Dataset Construction
D Additional Results and Figures
E Prompt Templates
F NEC Question Generation Template


Revolutionizing Customer Interactions: Insights and Challenges in Deploying ChatGPT and Generative Chatbots for FAQs / 2311.09976 / ISBN:https://doi.org/10.48550/arXiv.2311.09976 / Published by ArXiv / on (web) Publishing site
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
8. Conclusion
References


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


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


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
Abstract
1 Introduction
2 Proposed Process
3 Related Work and Discussion
4 Conclusion
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
Abstract
1 Introduction
2 Background & Related Work
3 Methods
4 Findings
5 Discussion and Recommendations
7 Limitations
8 Ethical Considerations
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
Abstract
1 Introduction
2 Background
3 Study Design
4 Findings
5 Discussion
Acknowledgments and Disclosure of Funding
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
References


Responsible AI Research Needs Impact Statements Too / 2311.11776 / ISBN:https://doi.org/10.48550/arXiv.2311.11776 / Published by ArXiv / on (web) Publishing site
Abstract
Requiring adverse impact statements for RAI research is long overdue
What are other research communities doing?
What do RAI venues do?
Suggestions for More Meaningful Engagement with the Impact of RAI Research
Concluding Reflections
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
Abstract
I. Introduction
II. Education and LLMS
III. Key technologies for EDULLMS
IV. LLM-empowered education
V. Key points in LLMSEDU
VI. Challenges and future directions
VII. Conclusion
References


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


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


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
Abstract
Introduction
Research Method
Results
Conclusion
References


Potential Societal Biases of ChatGPT in Higher Education: A Scoping Review / 2311.14381 / ISBN:https://doi.org/10.48550/arXiv.2311.14381 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Overview of societal biases in GAI models
Methodology
Findings
Discussion
Conclusion
References


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


Ethics and Responsible AI Deployment / 2311.14705 / ISBN:https://doi.org/10.48550/arXiv.2311.14705 / Published by ArXiv / on (web) Publishing site
1. Introduction: The Role of Algorithms in Protecting Privacy
2. Case Study of the Bletchley Summit
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.
10. Conclusion
11. References


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


Generative AI and US Intellectual Property Law / 2311.16023 / ISBN:https://doi.org/10.48550/arXiv.2311.16023 / Published by ArXiv / on (web) Publishing site
Abstract
II. US Patent law
III. US Copyright law
IV. Caveart emptor: no free ride for automation
V. Potential harms and mitigation
VI. Conclusion
VII. Future considerations
References


Survey on AI Ethics: A Socio-technical Perspective / 2311.17228 / ISBN:https://doi.org/10.48550/arXiv.2311.17228 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Privacy and data protection
3 Transparency and explainability
4 Fairness and equity
5 Responsiblity, accountability, and regulations
6 Environmental impact
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
Abstract
I. Introduction
II. Background
III. The rise of large AI models
IV. Societal implications
V. Technical defense mechanisms
VI. Cross-platform strategies
VII. Ethical considerations
VIII. Proposed integrated defense framework
IX. Discussion
X. Conclusion
References


Navigating Privacy and Copyright Challenges Across the Data Lifecycle of Generative AI / 2311.18252 / ISBN:https://doi.org/10.48550/arXiv.2311.18252 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Legal Basis of Privacy and Copyright Concerns over Generative AI
3 Mapping Challenges throughout the Data Lifecycle
4 Lifecycle Approaches
5 Conclusion
References


Integrating AI into CCTV Systems: A Comprehensive Evaluation of Smart Video Surveillance in Community Space / 2312.02078 / ISBN:https://doi.org/10.48550/arXiv.2312.02078 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Related works
III. System features
IV. System setup and configuration
V. Real-world results and evaluation
VI. Physical-cyber-physical evaluation (anomaly detection)
VII. Conclusion
References
Biography


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


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


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


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


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


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


Control Risk for Potential Misuse of Artificial Intelligence in Science / 2312.06632 / ISBN:https://doi.org/10.48550/arXiv.2312.06632 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Risks of Misuse for Artificial Intelligence in Science
3 Control the Risks of AI Models in Science
4 Call for Responsible AI for Science
5 Discussion
6 Related Works
References
7 Ethical Impacts
8 Acknowledgements
9 Author information
Appendix A Assessing the Risks of AI Misuse in Scientific Research
Appendix C Detailed Implementation of SciGuard
Appendix D Details of Benchmark Results


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


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


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


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


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


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


Learning Human-like Representations to Enable Learning Human Values / 2312.14106 / ISBN:https://doi.org/10.48550/arXiv.2312.14106 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Related Work
3. Experiments on Synthetic Data
4. Experiments on Human Data using Language Models
5. Discussion
References
A. Appendix


The Economics of Human Oversight: How Norms and Incentives Affect Costs and Performance of AI Workers / 2312.14565 / ISBN:https://doi.org/10.48550/arXiv.2312.14565 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Theoretical background and hypotheses
III. Method
IV. Results
V. Discussion
VI. Conclusion
Appendix
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
Experimental Study
Results
Discussion
Methods
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
Abstract
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
1. Introduction
2. The generation of synthetic data
3. The usage of synthetic data
4. Risks and Challenges in Utilizing Synthetic Datasets for AI
5. Conclusions
References


MULTI-CASE: A Transformer-based Ethics-aware Multimodal Investigative Intelligence Framework / 2401.01955 / ISBN:https://doi.org/10.48550/arXiv.2401.01955 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Related work
III. Methodology: model development
IV. System design
V. Evaluation
VI. Discussion and future work
VII. Conclusion
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
Acknowledgements
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
Background and significance
Objective
Materials and methods
Results
Discussion
PRISMA 2020 flow diagram and bias handling workflow
References


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
Abstract
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
IV Conclusions
Bibliography


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


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


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


Five ethical principles for generative AI in scientific research / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
Principle 1: Understand model training and output
Principle 2: Respect privacy, confidentiality, and copyright
Principle 3: Avoid plagiarism and policy violations
Principle 4: Apply AI beneficially
Principle 5: Use AI transparently and reproducibly
Concluding remarks
References


A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations / 2401.17486 / ISBN:https://doi.org/10.48550/arXiv.2401.17486 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related work
3 Methods
4 RAI tool evaluation practices
5 Towards evaluation of RAI tool effectiveness
6 Limitations
7 Conclusion
References
B RAI tools listed by target stage of AI development
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
Authors' bios


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
Abstract
1 Introduction
2 Networking research today
3 Beyond technical dimensions
4 Sense of engagement and responsibility
5 Possible next steps
6 Concluding remarks
References
A Surveyed research group webpages


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
Abstract
1. Introduction
2. Related literature
3. Research study
4. Findings
5. Discussion
6. Conclusions, limitations, and future work
References


Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube / 2402.01760 / ISBN:https://doi.org/10.48550/arXiv.2402.01760 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Literature review
3. Methodology
4. Discussion
5. Conclusion
References
A. Macro Action for Solving the White Cross
B. An Example Dialog With Sentiment Analysis
C. ROSE: Tool and Data ResOurces to Explore the Instability of SEntiment Analysis Systems
D. CausalRating: A Tool To Rate Sentiments Analysis Systems for Bias


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
5 Conclusion
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
6 Conclusion
References
A Provided AI response strategies and examples
C Linear regression of participants' AI usage and desired responses


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


A Framework for Assessing Proportionate Intervention with Face Recognition Systems in Real-Life Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Background
3. Intervention models from other fields
4. Proposed framework
5. The framework in practice
6. Conclusions and future work
References


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
Abstract
1 Introduction
2 Background
3 Review Methodology
4 Challenges, Threats and Limitations
5 Findings
6 Discussion and Recommendations
7 Methodological Lessons Learned
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
Abstract
Introduction
Methods
Results
Discussion
Conclusion
Declaration of interests
Reference
Appendix


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


I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench / 2401.17882 / ISBN:https://doi.org/10.48550/arXiv.2401.17882 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Awareness in LLMs
4 Awareness Dataset: AWAREEVAL
5 Experiments
6 Conclusion
Limitation
References
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
Abstract
1 Introduction
2 Methods
3 Results
4 Discussion
5 Limitations
6 Conclusion
References
Appendix A
Appendix B
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
7 Conclusion
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
2 Analysis of the Terminology
3 Paradigm Shifts and New Trends
4 Current Taxonomy
5 Discussion and Future Research Directions
References


Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence / 2402.09880 / ISBN:https://doi.org/10.48550/arXiv.2402.09880 / Published by ArXiv / on (web) Publishing site
Abstract
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
Authors
Appendix A Examples of Benchmark Inadequacies in Technological Aspects
Appendix B Examples of Benchmark Inadequacies in Processual Elements
Appendix C Examples of Benchmark Inadequacies in Human Dynamics


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


Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation / 2402.12590 / ISBN:https://doi.org/10.48550/arXiv.2402.12590 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Emergence of Free-Formed AI Collectives
3. Enhanced Performance of Free-Formed AI Collectives
4. Robustness of Free-Formed AI Collectives Against Risks
5. Open Challenges for Free-Formed AI Collectives
References
A. Cocktail Simulation
B. Sentence Making Simulation
C. Public Good 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
Abstract
1 Introduction
2 Related Work
3 CosmoAgent Simulation Setting
4 CosmoAgent Architecture
5 Evaluation
6 Experimental Design
7 Results
8 Conclusion
A CosmoAgent Prompt
B Secretary Agent Prompt
References


The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review / 2402.13635 / ISBN:https://doi.org/10.48550/arXiv.2402.13635 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
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
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
Appendix 2 Modified psychometric scales


Autonomous Vehicles: Evolution of Artificial Intelligence and Learning Algorithms / 2402.17690 / ISBN:https://doi.org/10.48550/arXiv.2402.17690 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
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
V. Review of Existing Research and Use Cases
VI. AI and Learning Algorithms Statistics for Autonomous Vehicles
VII. Conclusion
References
Authors


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


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


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


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


Updating the Minimum Information about CLinical Artificial Intelligence (MI-CLAIM) checklist for generative modeling research / 2403.02558 / ISBN:https://doi.org/10.48550/arXiv.2403.02558 / Published by ArXiv / on (web) Publishing site
Abstract
Part 1A. Study design for generative modeling
Part 1B. Best practices for cohort selection
Part 1C. Bias, privacy, and harm assessments
Part 2. A new train-test split for prompt development and few-shot learning
Part 4. Model evaluation
Part 4A. Automated model evaluation
Part 4B. Human model evaluation
Part 5. Interpretability of generative models
Part 6. End-to-end pipeline replication
Conclusions
Table 1. Updated MI-CLAIM checklist for generative AI clinical studies.
References


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


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
Abstract
1 Introduction
2 AI Model Improvements with Human-AI Teaming
3 Effective Human-AI Joint Systems
4 Safe, Secure and Trustworthy AI
5 Applications
6 Conclusion
References


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


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


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


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


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


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


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


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


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


Trust in AI: Progress, Challenges, and Future Directions / 2403.14680 / ISBN:https://doi.org/10.48550/arXiv.2403.14680 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Methodology
3. Findings
4. Discussion
5. Concluding Remarks and Future Directions
Conflict of interest
Acknowledgement
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
Introduction
Definitions
Method
Results
AI Ethics Development Phases Based on Keyword Analysis
Key AI Ethics Issues
Key Gaps
Limitations and Conclusion
Funding
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
1 Context
2 Trustworthy AI Too Many Definitions or Lack Thereof?
3 Complexities and Challenges
4 AI Regulation: Current Global Landscape
5 Risk
6 Bias and Fairness
7 Explainable AI as an Enabler of Trustworthy AI
8 Implementation Framework
9 A Few Suggestions for a Viable Path Forward
10 Summary and Next Steps
11 About the Authors
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
Abstract
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
Abstract
1 Introduction
2 Related Survey
3 Conceptualizing Fairness and Bias in ML
4 Practical cases of unfairness in real-world setting
5 Ways to mitigate bias and promote Fairness
6 How Users can be affected by unfair ML Systems
7 Challenges and Limitations
8 Conclusion
References


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


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


AI Act and Large Language Models (LLMs): When critical issues and privacy impact require human and ethical oversight / 2404.00600 / ISBN:https://doi.org/10.48550/arXiv.2404.00600 / Published by ArXiv / on (web) Publishing site
2. The implementation of the AI Act
3. The definition of artificial intelligence systems
4. AI Act and high-risk systems
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
5 Data Resources for Large Language Models in Law
References


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


Balancing Progress and Responsibility: A Synthesis of Sustainability Trade-Offs of AI-Based Systems / 2404.03995 / ISBN:https://doi.org/10.48550/arXiv.2404.03995 / Published by ArXiv / on (web) Publishing site
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
2 Background
3 Method
4 Findings
5 Discussion
6 Limitations
7 Conclusion
References


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


Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Generative Agents / 2404.06750 / ISBN:https://arxiv.org/abs/2404.06750 / Published by ArXiv / on (web) Publishing site
Abstract
Introduction
A Primer
Polarised Responses
Rebooting Machine Ethics
Generative Agents in Society
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
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
5 Three Patterns of Critique
6 Conclusion and Outlook
References
A Methodologies of Surveyed Literature


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
Abstract
1 Introduction
2 The Need for Governance of AI
3 Remote Biometric Identification and the AI Act
4 Public Opinion on AI Governance
5 Research Questions
6 Results
7 Discussion
8 Conclusion
Conflicts of Interest
References
Appendix


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


Epistemic Power in AI Ethics Labor: Legitimizing Located Complaints / 2402.08171 / ISBN:https://doi.org/10.1145/3630106.3658973 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 The Lower Status of Ethics Work within AI Cultures
3 Automated Model Cards: Legitimacy via Quantified Objectivity
5 Alternative AI Ethics: Space for Embodied Complaints
6 Conclusions: Towards Humble Technical Practices
Acknowledgments
References


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


Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in LLMs / 2404.08699 / ISBN:https://doi.org/10.48550/arXiv.2404.08699 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background and Related Work
3 Methodology
4 Evaluation
5 Conclusion
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
IV. Results and Discussion
V. Conclusion
References


Debunking Robot Rights Metaphysically, Ethically, and Legally / 2404.10072 / ISBN:https://doi.org/10.48550/arXiv.2404.10072 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Robot Rights: the Debate
3 The Robots at Issue
4 The Machines Like us Argument: Mistaking the Map for the Territory
5 Embodied Enactive (Post-Cartesian) Perspectives on Cognition
6 Posthumanism
7 The Legal Perspective
8 The Troubling Implications of Legal Rationales for Robot Rights
9 The Enduring Irresponsibility of AI Rights Talk
Notes
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
Abstract
1 Introduction
2 Background & Related Work
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
Abstract
1 Introduction
2 EU Public Policy Analysis
3 A Geo-Political AI Risk Taxonomy
4 European Union Artificial Intelligence Act
5 Conclusion
References


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


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


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


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


From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap / 2404.13131 / ISBN:https://doi.org/10.1145/3630106.3658951 / Published by ArXiv / on (web) Publishing site
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
5 A Final Note
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
3 Best Practices for AI UI/UX Design for Children
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
2 Procurement Loopholes Exist
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
Introduction
Findings
Conclusion
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
Abstract
I. Introduction
II. Discrimination in Law
III. Prevalent Algorithmic Fairness Definitions
IV. Criteria for the Selection of Fairness Methods
V. Discussion
References


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


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


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


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


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
3. AWS Proliferation and Threats to Academic Research
4. Policy Recommendations
Impact Statement
References
A. Global Regions with Alleged AWS Deployment Discussed in This Work


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


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


Organizing a Society of Language Models: Structures and Mechanisms for Enhanced Collective Intelligence / 2405.03825 / ISBN:https://doi.org/10.48550/arXiv.2405.03825 / Published by ArXiv / on (web) Publishing site
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
Acknowledgements
Glossary of Terms
Executive Summary
1. Introduction
2. Methodology
3. A Spectrum of Scenarios of Open Data for Generative AI
4. Open Data Requirements And Diagnostic
5. Recommendations for Advancing Open Data in Generative AI
Appendix


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


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


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


RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical Roles / 2307.15158 / ISBN:https://doi.org/10.48550/arXiv.2307.15158 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related Work
3 Author Positionality Statement
4 Method for Generating Responsible AI Guidelines
5 Evaluation of the 22 Responsible AI Guidelines
6 Discussion
7 Conclusion
References
A Additional Materials for the User Study
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
3 Methods
4 Users’ Experiences and Challenges with ChatGPT
5 Analyses of the Design Process
6 User’s Attitude on ChatGPT’s Qualitative Analysis Assistance: from no to yes
7 Discussion
8 Limitations and Future Work
9 Conclusion
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
2. Main hypothesis
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
Abstract
Introduction
Evaluating a system as a social actor
Social-interactional harms
Design implications for LLM agents
Conclusion
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
Abstract
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
Acknowledgments
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
Abstract
1 Introduction
2 Related Work
3 Overview of Speech Generation
4 Research Approach
5 Conceptual Framework
6 Taxonomy of Harms
7 Discussion
8 Conclusion
Acknowledgments
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
3. Methodology
4. Experiments
References


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
Abstract
1. Introduction
2. Background
3. What Are the Collective Decision Problems and their Alternatives in this Context?
5. What Is the Format of Human Feedback?
7. Which Traditional Social-Choice-Theoretic Concepts Are Most Relevant?
8. How Should We Account for Behavioral Aspects and Human Cognitive Structures?
9. How Do We Navigate a Multiplicity of AIs?
10. Conclusion
Impact Statement
Acknowledgements
References


A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs) / 2405.03066 / ISBN:https://doi.org/10.48550/arXiv.2405.03066 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Materials
3 Results
4 Discussion
5 Conclusions
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
5 Conclusion
Limitations
References
Appendix S: Multiple Adversarial LLMs
Appendix A: Wheels of Emotions
Appendix B: Polarized Emotions in One Article
Appendix C: Z. Sayre to F. S. Fitzgerald w/ Mixed Emotions
Appendix D: Complex Emotions
Appendix E: “To My Sister” of Different Linguistic Behaviors
Appendix H: Instruction to Human Annotators


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


When AI Eats Itself: On the Caveats of Data Pollution in the Era of Generative AI / 2405.09597 / ISBN:https://doi.org/10.48550/arXiv.2405.09597 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 When AI Eats Itself
3 Technical Strategies for AI-generated Content Detection
4 Regulatory Case Studies for Synthetic Data Dissemination
5 Conclusion
7 References


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
Abstract
1. Introduction
2.MT Critical Errors
3. Data Compiling and Annotation
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
Abstract
1 Introduction
2 Related Literature on Industry’s Engagement in Responsible AI Research
3 Motivations for Industry to Engage in Responsible AI Research
4 The Narrow Depth of Industry’s Responsible AI Research
5 The Narrow Breadth of Industry’s Responsible AI Research
6 Limited Adoption of Responsible AI Research in Commercialization: Patent Citation Analysis
7 Discussion
8 Conclusion
Acknowledgements
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
C The Risk Assessment Database
D Lifecycle Mapping of Pilot 1
E Lifecycle Mapping of Pilot 2: The GARMI Vision Module


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
Abstract
Main
Results
Methods in clinical AI fairness research
Discussion
Conclusion
Methods
Acknowledgments
Reference
Additional material


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


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


There and Back Again: The AI Alignment Paradox / 2405.20806 / ISBN:https://doi.org/10.48550/arXiv.2405.20806 / Published by ArXiv / on (web) Publishing site
Abstract
Paper
References


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
B PAC Dataset: Parental Alienation 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
Abstract
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
Abstract
Introduction
I. Description of Method/Empirical Design
II. Risk Characteristics of LLMs
III. Impact of Alignment on LLMs’ Risk Preferences
IV. Impact of Alignments on Corporate Investment Forecasts
V. Robustness: Transcript Readability and Investment Score Predictability
VI. Conclusions
References
Figures and tables


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


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


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


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


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


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


An Empirical Design Justice Approach to Identifying Ethical Considerations in the Intersection of Large Language Models and Social Robotics / 2406.06400 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Theoretical Background
3 Methodology
4 Findings
5 Discussion
6 Conclusions and Recommendations
Statements and Declarations
References
Appendix A: Interview questions
Appendix B: Collected data summary


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
8 Appendices