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- The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site
- Report highlights
Chapter 1 Reseach and Development
Chapter 2 Technical Performance
Chapter 3 Technical AI Ethics
Chapter 4 The Economy and Education
Chapter 5 AI Policy and Governance
Appendix - Exciting, Useful, Worrying, Futuristic:
Public Perception of Artificial Intelligence in 8 Countries / 2001.00081 / ISBN:https://doi.org/10.48550/arXiv.2001.00081 / Published by ArXiv / on (web) Publishing site
- Abstract
CCS Concept
1 Introduction
2 Background
3 Methodology
4 Findings
5 Discussion
6 Conclusions
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
2 Background
5 Detail results and analysis
7 Conclusions and future directions
9 Appendices - AI Ethics Issues in Real World: Evidence from AI Incident Database / 2206.07635 / ISBN:https://doi.org/10.48550/arXiv.2206.07635 / Published by ArXiv / on (web) Publishing site
- 3 Method
4 Results
5 Discussion - 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
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
- Introductionn
1. Problems with AI
2. Defining ethical AI
3. Implementing ethical AI - Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance / 2206.11922 / ISBN:https://doi.org/10.48550/arXiv.2206.11922 / Published by ArXiv / on (web) Publishing site
- 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
- Keywords
- ESR: Ethics and Society Review of Artificial Intelligence Research / 2106.11521 / ISBN:https://doi.org/10.48550/arXiv.2106.11521 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
3 The ESR Process
4 Deployment and Evaluation
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
- 3 Practical Challengesof Ethical AI
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
- 1 Introduction
4 Proposed competency framework for responsible AI practitioners
References - GPT detectors are biased against non-native English writers / 2304.02819 / ISBN:https://doi.org/10.48550/arXiv.2304.02819 / Published by ArXiv / on (web) Publishing site
- Results
Discussion
Materials and Methods - Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects / 2304.08275 / ISBN:https://doi.org/10.48550/arXiv.2304.08275 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Underlying Aspects
III. Interactions between Aspects
References - QB4AIRA: A Question Bank for AI Risk Assessment / 2305.09300 / ISBN:https://doi.org/10.48550/arXiv.2305.09300 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 The Question Bank: QB4AIRA - A multilevel framework for AI governance / 2307.03198 / ISBN:https://doi.org/10.48550/arXiv.2307.03198 / Published by ArXiv / on (web) Publishing site
- 3. International and National Governance
4. Corporate Self-Governance
6. Psychology of Trust
8. Ethics and Trust Lenses in the Multilevel Framework
References - From OECD to India: Exploring cross-cultural differences in perceived trust, responsibility and reliance of AI and human experts / 2307.15452 / ISBN:https://doi.org/10.48550/arXiv.2307.15452 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
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
- 2. Theory
3. Methodology
4. Ethical Implications of AI Value Chains
5. Future Directions for Research, Practice, & Policy - 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
- 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
2 Clarifying Terminologies of Article-5: Insights from Behavioral Economics and Psychology
3 Enhancing Protection for the General Public and Vulnerable Groups
4 Conclusion
References - From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence / 2308.02448 / ISBN:https://doi.org/10.48550/arXiv.2308.02448 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Applications in Military Versus Healthcare
Identifying Ethical Concerns and Risks
GREAT PLEA Ethical Principles for Generative AI in Healthcare
Conclusion
References - Ethical Considerations and Policy Implications for Large Language Models: Guiding Responsible Development and Deployment / 2308.02678 / ISBN:https://doi.org/10.48550/arXiv.2308.02678 / Published by ArXiv / on (web) Publishing site
- System-role
Image-related
Bias and Discrimination of Training Data - 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
- 1 Introduction
2 Background
3 Policy scope
4 Centralized regulation in the US context
5 Crowdsourced safety mechanism - Normative Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions / 2208.12616 / ISBN:https://doi.org/10.48550/arXiv.2208.12616 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Taxonomy of ethical principles
4 Previous operationalisation of ethical principles
References - Bad, mad, and cooked: Moral responsibility for civilian harms in human-AI military teams / 2211.06326 / ISBN:https://doi.org/10.48550/arXiv.2211.06326 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Responsibility in War
Computers, Autonomy and Accountability
Moral Injury
Human Factors
AI Workplace Health and Safety Framework
References - The Future of ChatGPT-enabled Labor Market: A Preliminary Study / 2304.09823 / ISBN:https://doi.org/10.48550/arXiv.2304.09823 / Published by ArXiv / on (web) Publishing site
- 2 Results
- A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation / 2305.11391 / ISBN:https://doi.org/10.48550/arXiv.2305.11391 / Published by ArXiv / on (web) Publishing site
- 2 Large Language Models
5 Falsification and Evaluation
6 Verification
8 Regulations and Ethical Use
Reference - Getting pwn'd by AI: Penetration Testing with Large Language Models / 2308.00121 / ISBN:https://doi.org/10.48550/arXiv.2308.00121 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 LLM-based penetration testing
4 Discussion - 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
3 Targeted data augmentation
4 Experiments
5 Conclusions
References - Exploring the Power of Creative AI Tools and Game-Based Methodologies for Interactive Web-Based Programming / 2308.11649 / ISBN:https://doi.org/10.48550/arXiv.2308.11649 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
11 Bias Awareness: Navigating AI-Generated Content in Education - 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
5 Results
6 Discussion
7 Conclusions
References - 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
- I. Introduction
III. Comprehensive review of state-of-the-art LLMs
IV. Applied and technology implications for LLMs
VI. Solution architecture for privacy-aware and trustworthy conversational AI - 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
- 3 Emerging dual-use risks and vulnerabilities in AI systems
4 Integrating red teaming, blue teaming, and ethics with violet teaming
5 Research directions in AI safety and violet teaming
6 A pathway for balanced AI innovation
7 Violet teaming to address dual-use risks of AI in biotechnology
9 The path forward
10 Supplemental & additional details
References - Artificial Intelligence in Career Counseling: A Test Case with ResumAI / 2308.14301 / ISBN:https://doi.org/10.48550/arXiv.2308.14301 / Published by ArXiv / on (web) Publishing site
- 4 Results and discussion
- 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
- 2 Related Works
References - The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / ISBN:https://doi.org/10.48550/arXiv.2308.16538 / Published by ArXiv / on (web) Publishing site
- Table of contents and index
Executive summary
1 Introduction
2 Key AI technology in financial services
3 Benefits of AI use in the finance sector
4 Threaths & potential pitfalls
5 Challenges
6 Regulation of AI and regulating through AI
7 Recommendations
References - Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / ISBN:https://doi.org/10.48550/arXiv.2309.00064 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Black box and lack of transparency
3 Bias and fairness
4 Human-centric AI
5 Ethical concerns and value alignment
6 Way forward
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
- 3. ChatGPT Training Process
4. Methods
5. Discussion
6. Conclusion - Pathway to Future Symbiotic Creativity / 2209.02388 / ISBN:https://doi.org/10.48550/arXiv.2209.02388 / Published by ArXiv / on (web) Publishing site
- Introduction
Part 1 - 1 Generatives Systems: Mimicking Artifacts
Part 1 - 3 Artistic Systems: Mimicking Inspiration
Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data
Part 3 - 2 Machine Artist Models
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 - 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
- 2. Fairness - For Equitable AI in Medical Imaging
4. Traceability - For Transparent and Dynamic AI in Medical Imaging
6. Robustness - For Reliable AI in Medical Imaging
7. Explainability - For Enhanced Understanding of AI in Medical Imaging
9. Discussion and Conclusion
References - The Cambridge Law Corpus: A Corpus for Legal AI Research / 2309.12269 / ISBN:https://doi.org/10.48550/arXiv.2309.12269 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 The Cambridge Law Corpus
D Case Outcome Annotation Instructions
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
- 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
IV. Attack Surfaces
V. Ethical & Legal Concerns
VI. Human-Robot Interaction (HRI) Security Studies
VII. Future Research & Discussion
References - If our aim is to build morality into an artificial agent, how might we begin to go about doing so? / 2310.08295 / ISBN:https://doi.org/10.48550/arXiv.2310.08295 / Published by ArXiv / on (web) Publishing site
- 1 The Top-Down Approach Alone Might Be Insufficient
3 Proposing a Hybrid Approach
4 AI Governance Principles - 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
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
- Introduction
Nation-State Advances in AI-driven Information Operations
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
References
B Pre-class Questionnaire (Verbatim)
D Post-Activity Questionnaire (Verbatim)
G Statistical Tests - A Review of the Ethics of Artificial Intelligence and its Applications in the United States / 2310.05751 / ISBN:https://doi.org/10.48550/arXiv.2310.05751 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Literature Review
3. AI Ethical Principles
4. Implementing the Practical Use of Ethical AI Applications
5. Conclusions and Recommendations
References - A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics / 2310.05694 / ISBN:https://doi.org/10.48550/arXiv.2310.05694 / Published by ArXiv / on (web) Publishing site
- Abstract
I. INTRODUCTION
II. WHAT LLM S CAN DO FOR HEALTHCARE ? FROM FUNDAMENTAL TASKS TO ADVANCED APPLICATIONS
IV. TRAIN AND USE LLM FOR HEALTHCARE
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
- 2 STREAM: Social data and knowledge collective intelligence platform for TRaining
Ethical AI Models
3 The applications of STREAM
References - Regulation and NLP (RegNLP): Taming Large Language Models / 2310.05553 / ISBN:https://doi.org/10.48550/arXiv.2310.05553 / Published by ArXiv / on (web) Publishing site
- 2 Regulation: A Short Introduction
3 LLMs: Risk and Uncertainty
5 Regulation and NLP (RegNLP): A New Field
References - Ethics of Artificial Intelligence and Robotics in the Architecture, Engineering, and Construction Industry / 2310.05414 / ISBN:https://doi.org/10.48550/arXiv.2310.05414 / Published by ArXiv / on (web) Publishing site
- 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 - 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
- Ethics of GEnerating Native Ads
- Compromise in Multilateral Negotiations and the Global Regulation of Artificial Intelligence / 2309.17158 / ISBN:https://doi.org/10.48550/arXiv.2309.17158 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
3. The liberal-sovereigntist multiplicity
4. Towards a compromise: drafting the normative hybridity
5. Text negotiations as normative testing
Notes
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
- Why Ethics
Principal Ethics in Healthcare
Method
Results and Discussion
A Unified Utilitarian Ethics Framework
Theory and Practical Implications
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
4. Technical Risks
References
Appendix - Autonomous Vehicles an overview on system, cyber security, risks, issues, and a way forward / 2309.14213 / ISBN:https://doi.org/10.48550/arXiv.2309.14213 / Published by ArXiv / on (web) Publishing site
- 5. Cybersecurity Risks
6. Risk management
7. Issues
9. References - The Return on Investment in AI Ethics: A Holistic Framework / 2309.13057 / ISBN:https://doi.org/10.48550/arXiv.2309.13057 / Published by ArXiv / on (web) Publishing site
- 2. AI Ethics
3. Return on Investment (ROI)
4. A Holistic Framework
6. References - Who to Trust, How and Why: Untangling AI Ethics Principles, Trustworthiness and Trust / 2309.10318 / ISBN:https://doi.org/10.48550/arXiv.2309.10318 / Published by ArXiv / on (web) Publishing site
- 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
- 1 Introduction
2 Definitions of Terms
4 Methodology
5 Relating Case Studies to Indigenous Data Sovereignty and CARE Principles
References - The Glamorisation of Unpaid Labour: AI and its Influencers / 2308.02399 / ISBN:https://doi.org/10.48550/arXiv.2308.02399 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
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
- 2. AI and blockchain in education: An overview of the benefits and
challenges
- Toward an Ethics of AI Belief / 2304.14577 / ISBN:https://doi.org/10.48550/arXiv.2304.14577 / Published by ArXiv / on (web) Publishing site
- 3. Proposed Novel Topics in an Ethics of AI Belief
- 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
- 2 Methodology
3 Governance Patterns
4 Process Patterns
5 Product Patterns
6 Related Work
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
INTRODUCTION
METHODS
FUTURE-AI GUIDELINE
DISCUSSION - 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
- 3 Agent Benchmark
References - 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
- 4 Reinforcement Learning with Good-for-Humanity Preference Models
6 Discussion
B Trait Preference Modeling
H Samples - 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
- 2 Related Work
3 Method
4 Findings
5 Discussion
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
- 5 System Design for AI Alignment
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
3 Arrow-Sen Impossibility Theorems for RLHF
4 Implications for AI Governance and Policy - A Comprehensive Review of
AI-enabled Unmanned Aerial Vehicle:
Trends, Vision , and Challenges / 2310.16360 / ISBN:https://doi.org/10.48550/arXiv.2310.16360 / Published by ArXiv / on (web) Publishing site
- I. Introduction
IV. Artificial Intelligence Embedded UAV
VI. Review Summary
References - Unpacking the Ethical Value Alignment in Big Models / 2310.17551 / ISBN:https://doi.org/10.48550/arXiv.2310.17551 / Published by ArXiv / on (web) Publishing site
- Abstract
2 Risks and Ethical Issues of Big Model
3 Investigating the Ethical Values of Large Language Models
References - Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 The BvH and HK Definitions
4 The Causal 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
- 5 Why Openness in AI for Science
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
Broader educational preparedness for work in AI Cybersecurity
Communication skills in cybersecurity and ethics
References - Human participants in AI research: Ethics and transparency in practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site
- 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
B Placing Research Ethics for Human Participants in Historical Context
C Defining the Scope of Research Participation in AI Research - LLMs grasp morality in concept / 2311.02294 / ISBN:https://doi.org/10.48550/arXiv.2311.02294 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 The Meaning Model
4 The Moral Model
A Supplementary Material - 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
- Literature Review
Research questions - Towards Effective Paraphrasing for Information
Disguise / 2311.05018 / ISBN:https://doi.org/10.1007/978-3-031-28238-6_22 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
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
3 Measuring Fairness Metrics
4 Deontological AI Alignment
5 Aligning with Deontological Principles: Use Cases - Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing / 2304.02017 / ISBN:https://doi.org/10.48550/arXiv.2304.02017 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Applications of ChatGPT in real-world scenarios
5 Advantages of ChatGPT in natural language processing
7 Ethical considerations when using ChatGPT
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
II. Sources of bias in AI
III. Impacts of 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
- 3 Crafting an Ethical Dataset
- 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
- 2 Related work
3 Method
4 Findings
5 Discussion
References - She had Cobalt Blue Eyes: Prompt Testing to Create Aligned and Sustainable Language Models / 2310.18333 / ISBN:https://doi.org/10.48550/arXiv.2310.18333 / Published by ArXiv / on (web) Publishing site
- 2 Related Works
3 ReFLeCT: Robust, Fair, and Safe LLM Construction Test Suite
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
- IV. Trust
V. Ethics
References - How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
3 Methodology
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
2 UnknownBench: Evaluating LLMs on the Unknown
3 Experiments
4 Related Work
References
D Additional Results and Figures
F NEC Question Generation Template - Revolutionizing Customer Interactions: Insights and Challenges in Deploying ChatGPT and Generative Chatbots for FAQs / 2311.09976 / ISBN:https://doi.org/10.48550/arXiv.2311.09976 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Chatbots Background and Scope of Research
3. Chatbot approaches overview: Taxonomy of existing methods
4. ChatGPT
5. Applications
6. Open chanllenges
7. Future Research Directions - 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
- 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
Appendix A - What is an Algorithmic Harm? And a Bibliography - Case Repositories: Towards Case-Based Reasoning for AI Alignment / 2311.10934 / ISBN:https://doi.org/10.48550/arXiv.2311.10934 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
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
- 4 Findings
References - Assessing AI Impact Assessments: A Classroom Study / 2311.11193 / ISBN:https://doi.org/10.48550/arXiv.2311.11193 / Published by ArXiv / on (web) Publishing site
- 2 Background
3 Study Design
4 Findings
5 Discussion
References
A Overview of AIIA Instruments
B Study Materials - GPT in Data Science: A Practical Exploration of Model Selection / 2311.11516 / ISBN:https://doi.org/10.48550/arXiv.2311.11516 / Published by ArXiv / on (web) Publishing site
- III. Approach: capturing and representing heuristics behind GPT's decision-making process
- Responsible AI Research Needs Impact Statements Too / 2311.11776 / ISBN:https://doi.org/10.48550/arXiv.2311.11776 / Published by ArXiv / on (web) Publishing site
- What are other research communities doing?
What do RAI venues do?
References - Large Language Models in Education: Vision and Opportunities / 2311.13160 / ISBN:https://doi.org/10.48550/arXiv.2311.13160 / Published by ArXiv / on (web) Publishing site
- IV. LLM-empowered education
- 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
III. Insights from top generative AI companies
IV. Risks of generative AI
VI. Conclusion - Towards Auditing Large Language Models: Improving Text-based Stereotype Detection / 2311.14126 / ISBN:https://doi.org/10.48550/arXiv.2311.14126 / Published by ArXiv / on (web) Publishing site
- Abstract
2 Related Works
3 Methodology
4 Results and Discussion
References - Ethical Implications of ChatGPT in Higher Education: A Scoping Review / 2311.14378 / ISBN:https://doi.org/10.48550/arXiv.2311.14378 / Published by ArXiv / on (web) Publishing site
- Results
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
- OVERVIEW OF SOCIETAL BIASES IN GAI MODELS
ANALYTICAL FRAMEWORK
FINDINGS
DISCUSSION
CONCLUSION - RAISE -- Radiology AI Safety, an End-to-end lifecycle approach / 2311.14570 / ISBN:https://doi.org/10.48550/arXiv.2311.14570 / Published by ArXiv / on (web) Publishing site
- 2. Pre-Deployment phase
3. Production deployment monitoring phase - Ethics and Responsible AI Deployment / 2311.14705 / ISBN:https://doi.org/10.48550/arXiv.2311.14705 / Published by ArXiv / on (web) Publishing site
- 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
7. Establishing responsible AI governance and oversight
8. AI in sensitive domains: healthcare, finance, criminal justice, defence, and human resources
9. Discussion on engaging stakeholders: fostering dialogue and collaboration between developers, users, and affected communities.
11. References - From deepfake to deep useful: risks and opportunities through a systematic literature review / 2311.15809 / ISBN:https://doi.org/10.48550/arXiv.2311.15809 / Published by ArXiv / on (web) Publishing site
- 2. Material and methods
- 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
- III. US Copyright law
V. Potential harms and mitigation
VII. Future considerations - 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
7 Conclusion
References - Deepfakes, Misinformation, and Disinformation in the Era of Frontier AI, Generative AI, and Large AI Models / 2311.17394 / ISBN:https://doi.org/10.48550/arXiv.2311.17394 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Background
V. Technical defense mechanisms
VI. Cross-platform strategies
VII. Ethical considerations
VIII. Proposed integrated defense framework
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
- 3 Mapping Challenges throughout the Data Lifecycle
References - From Lab to Field: Real-World Evaluation of an AI-Driven Smart Video Solution to Enhance Community Safety / 2312.02078 / ISBN:https://doi.org/10.48550/arXiv.2312.02078 / Published by ArXiv / on (web) Publishing site
- Applications and Visualizations
System Evaluation and Results
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
- 5. Conclusion
- Intelligence Primer / 2008.07324 / ISBN:https://doi.org/10.48550/arXiv.2008.07324 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
6 Measuring intelligence
7 Mathematically modeling intelligence
8 Consciousness
11 Control of intelligence
12 Large language models and Generative AI
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
- 2 Related work
3 Methodology
4 Results & analysis
5 Discussion
References - Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site
- III. Ethics: a primer
V. Implications whit future directions - Control Risk for Potential Misuse of Artificial Intelligence in Science / 2312.06632 / ISBN:https://doi.org/10.48550/arXiv.2312.06632 / Published by ArXiv / on (web) Publishing site
- 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
Appendix C Detailed Implementation of SciGuard - Disentangling Perceptions of Offensiveness: Cultural and Moral Correlates / 2312.06861 / ISBN:https://doi.org/10.48550/arXiv.2312.06861 / Published by ArXiv / on (web) Publishing site
- Abstract
...
Data Collection
Study 1: Geo-cultural Differences in Offensiveness
Study 2: Moral Foundations of Offensiveness
General Discussion
Geo-Cultural 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
- Introduction
The AI Assessment Scale
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
- Introduction
Artificial intelligence – concept and ethical background
Culturally responsive AI – current landscape
Recommendations
References - Investigating Responsible AI for Scientific Research: An Empirical Study / 2312.09561 / ISBN:https://doi.org/10.48550/arXiv.2312.09561 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Background and motivation
III. Research methodology
IV. Results
V. Discussion
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
- 4 Results
References
A Extended Survey Results
B Extended Guiding Principles
C Full survey questions - Beyond Fairness: Alternative Moral Dimensions for Assessing Algorithms and Designing Systems / 2312.12559 / ISBN:https://doi.org/10.48550/arXiv.2312.12559 / Published by ArXiv / on (web) Publishing site
- 3 Taking a Step Forward
References - Learning Human-like Representations to Enable Learning Human Values / 2312.14106 / ISBN:https://doi.org/10.48550/arXiv.2312.14106 / Published by ArXiv / on (web) Publishing site
- 3. Experiments on Synthetic Data
A. Appendix - Improving Task Instructions for Data Annotators: How Clear Rules and Higher Pay Increase Performance in Data Annotation in the AI Economy / 2312.14565 / ISBN:https://doi.org/10.48550/arXiv.2312.14565 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Theoretical background and hypotheses
III. Method
IV. Results
V. Discussion
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
- Introduction
Discussion - 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
- 2. Foundations of AI-driven threat intelligence
5. Challenges in autonomous threat hunting
6. Case studies and applications
8. Future directions and emerging trends
References - Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site
- 3. LLMs in clinical and counseling psychology
5. LLMs in social and cultural psychology
7. Challenges and future directions - 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
- 3. The usage of synthetic data
4. Risks and Challenges in Utilizing Synthetic Datasets for AI
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
- I. Introduction
II. Related work
III. Methodology: model development
IV. System design
V. Evaluation
VI. Discussion and future work
VII. Conclusion
References - AI Ethics Principles in Practice: Perspectives of Designers and Developers / 2112.07467 / ISBN:https://doi.org/10.48550/arXiv.2112.07467 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Related work
III. Methods
IV. Results
V. Discussion and suggestions
VI. Support mechanisms
VII. Conclusion
References - Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models / 2310.19917 / ISBN:https://doi.org/10.48550/arXiv.2310.19917 / Published by ArXiv / on (web) Publishing site
- Results
- Resolving Ethics Trade-offs in Implementing Responsible AI / 2401.08103 / ISBN:https://doi.org/10.48550/arXiv.2401.08103 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Approaches for Resolving Trade-offs
III. Discussion and Recommendations
IV. Concluding Remarks
References - Towards Responsible AI in Banking: Addressing Bias for Fair Decision-Making / 2401.08691 / ISBN:https://doi.org/10.48550/arXiv.2401.08691 / Published by ArXiv / on (web) Publishing site
- Abstract
Contents / List of figures / List of tables / Acronyms
1 Introduction
I Understanding bias - 2 Bias and moral framework in AI-based decision making
3 Bias on demand: a framework for generating synthetic data with bias
4 Fairness metrics landscape in machine learning
II Mitigating bias - 5 Fairness mitigation
6 FFTree: a flexible tree to mitigate multiple fairness criteria
III Accounting for bias - 7 Addressing fairness in the banking sector
8 Fairview: an evaluative AI support for addressing fairness
9 Towards fairness through time
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
- 2 Background
5 Discussion - 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
- 2 FAIR Data Principles: Theoretical Background and Significance
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
- 1. Motivation for White Paper
2. Background - 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
- Principle 1: Understand model training and output
Principle 3: Avoid plagiarism and policy violations - 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
- 1 Introduction
2 Related work
3 Methods
4 RAI tool evaluation practices
5 Towards evaluation of RAI tool effectiveness
References
A List of RAI tools, with their primary publication
B RAI tools listed by target stage of AI development
C List of publications, with their associated RAI tools
D Summary of themes and codes - Detecting Multimedia Generated by Large AI Models: A Survey / 2402.00045 / ISBN:https://doi.org/10.48550/arXiv.2402.00045 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Detection
5 Discussion
References - Responsible developments and networking research: a reflection beyond a paper ethical statement / 2402.00442 / ISBN:https://doi.org/10.48550/arXiv.2402.00442 / Published by ArXiv / on (web) Publishing site
- 2 Networking research today
4 Sense of engagement and responsibility
5 Possible next steps
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
- 2. Related literature
3. Research study
4. Findings
5. Discussion - Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cubeà / 2402.01760 / ISBN:https://doi.org/10.48550/arXiv.2402.01760 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
- 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
- 2 Establishing the novel aspect of AI as a crossover technology
3 Moral and ethical obligations when developing crossover AI technology
4 Recommendations to address threats posed by crossover AI technology
References - (A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice / 2402.01864 / ISBN:https://doi.org/10.48550/arXiv.2402.01864 / Published by ArXiv / on (web) Publishing site
- Abstract
3 Methods: case-based expert deliberation
4 Results
5 Discussion
References - POLARIS: A framework to guide the development of Trustworthy AI systems / 2402.05340 / ISBN:https://doi.org/10.48550/arXiv.2402.05340 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 State of the practice - Face Recognition: to Deploy or not to Deploy? A Framework for Assessing the Proportional Use of Face Recognition Systems in Real-World Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
- 2. Background
4. Proposed framework
5. The framework in practice
6. Compliance with International Regulations
7. Conclusions and future work - Ethics in AI through the Practitioner's View: A Grounded Theory Literature Review / 2206.09514 / ISBN:https://doi.org/10.48550/arXiv.2206.09514 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background
5 Findings
6 Discussion and Recommendations
A List of Included Studies
C Glossary of Terms
References
Authors - Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist / 2311.02107 / ISBN:https://doi.org/10.48550/arXiv.2311.02107 / Published by ArXiv / on (web) Publishing site
- Results
Discussion
Reference
Appendix - How do machines learn? Evaluating the AIcon2abs method / 2401.07386 / ISBN:https://doi.org/10.48550/arXiv.2401.07386 / Published by ArXiv / on (web) Publishing site
- 3. AIcon2abs Instructional Unit
- 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
- 5 Experiments
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
- 2 Methods
3 Results
4 Discussion
References
Appendix C - Taking Training Seriously: Human Guidance and Management-Based Regulation of Artificial Intelligence / 2402.08466 / ISBN:https://doi.org/10.48550/arXiv.2402.08466 / Published by ArXiv / on (web) Publishing site
- 2 Emerging Management-based
AI Regulation
References - User Modeling and User Profiling: A Comprehensive Survey / 2402.09660 / ISBN:https://doi.org/10.48550/arXiv.2402.09660 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Analysis of the Terminology
4 Current Taxonomy
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
- III. Unified Evaluation Framework For LLM
Benchmarks
IV. Technological Aspects
VI. Human Dynamics
VII. Discussions
VIII. Conclusion
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
- 2 Related Work
3 The AIGC Copyright Dilemma: A What-if Analysis
References - Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation / 2402.12590 / ISBN:https://doi.org/10.48550/arXiv.2402.12590 / Published by ArXiv / on (web) Publishing site
- 4. Robustness of Free-Formed AI Collectives
Against Risks
5. Open Challenges for Free-Formed AI Collectives - 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
- 4 CosmoAgent Architecture
5 Evaluation
6 Experimental Design
7 Results
A CosmoAgent Prompt - 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
- Introduction
METRIC-framework for medical training data
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
- 3 There is no reliable AI regulation without a
sound theory of human-AI interaction
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
- 2 Background
4 Analysis
References - Autonomous Vehicles: Evolution of Artificial Intelligence and Learning Algorithms / 2402.17690 / ISBN:https://doi.org/10.48550/arXiv.2402.17690 / Published by ArXiv / on (web) Publishing site
- I. Introduction
III. Ethical Considerations and Bias in AI-Driven Software Development for Autonomous Vehicles
VI. AI and Learning Algorithms Statistics for Autonomous Vehicles - Envisioning the Applications and Implications of Generative AI for News Media / 2402.18835 / ISBN:https://doi.org/10.48550/arXiv.2402.18835 / Published by ArXiv / on (web) Publishing site
- 2 The Suitability of Generative AI for Newsroom Tasks
References - FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics / 2402.19071 / ISBN:https://doi.org/10.48550/arXiv.2402.19071 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Background
3. Methods
4. Results
5. Discussion
References - Guidelines for Integrating Value Sensitive Design in Responsible AI Toolkits / 2403.00145 / ISBN:https://doi.org/10.48550/arXiv.2403.00145 / Published by ArXiv / on (web) Publishing site
- 2 Background and Related Work
3 Methodology
4 Results
5 Discussion
References
B Toolkits Considered for Inclusion - Implications of Regulations on the Use of AI and Generative AI for Human-Centered Responsible Artificial Intelligence / 2403.00148 / ISBN:https://doi.org/10.48550/arXiv.2403.00148 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Motivation & Background
References - The Minimum Information about CLinical Artificial Intelligence Checklist for Generative Modeling Research (MI-CLAIM-GEN) / 2403.02558 / ISBN:https://doi.org/10.48550/arXiv.2403.02558 / Published by ArXiv / on (web) Publishing site
- Part 3. Updates to baseline selection
Part 4. Model evaluation
Part 5. Interpretability of generative models
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
- II. Background & Literature Review
III. The AI-Enhanced CTI Processing Pipeline
IV. Challenges and Considerations
V. Conclusions & Future Research - A Survey on Human-AI Teaming with Large Pre-Trained Models / 2403.04931 / ISBN:https://doi.org/10.48550/arXiv.2403.04931 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 AI Model Improvements with Human-AI Teaming
3 Effective Human-AI Joint Systems
4 Safe, Secure and Trustworthy AI
5 Applications
References - Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness Metrics / 2311.05227 / ISBN:https://doi.org/10.48550/arXiv.2311.05227 / Published by ArXiv / on (web) Publishing site
- References
- Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance / 2206.11922 / ISBN:https://doi.org/10.48550/arXiv.2206.11922 / Published by ArXiv / on (web) Publishing site
- References
- How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site
- B Baseline Setup
D More Results - Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site
- References
- AGI Artificial General Intelligence for Education / 2304.12479 / ISBN:https://doi.org/10.48550/arXiv.2304.12479 / Published by ArXiv / on (web) Publishing site
- 3. The Potentials of AGI in Transforming Future Education
4. Ethical Issues and Concerns
References - Moral Sparks in Social Media Narratives / 2310.19268 / ISBN:https://doi.org/10.48550/arXiv.2310.19268 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
3. Data
4. Methods - 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
- 3. Analysis
4. Discussion
References - Legally Binding but Unfair? Towards Assessing Fairness of Privacy Policies / 2403.08115 / ISBN:https://doi.org/10.48550/arXiv.2403.08115 / Published by ArXiv / on (web) Publishing site
- 5 Representational Fairness
6 Ethics and Morality
References - Towards a Privacy and Security-Aware Framework for Ethical AI: Guiding the Development and Assessment of AI Systems / 2403.08624 / ISBN:https://doi.org/10.48550/arXiv.2403.08624 / Published by ArXiv / on (web) Publishing site
- 3 Research Methodology
4 Results of the Systematic Literature Review
5 Towards Privacy- and Security-Aware Framework for Ethical AI - Review of Generative AI Methods in Cybersecurity / 2403.08701 / ISBN:https://doi.org/10.48550/arXiv.2403.08701 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Attacking GenAI
4 Cyber Defence
5 Implications of Generative AI in Social, Legal, and Ethical Domains - 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
3 Method
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
Reference - AI Ethics: A Bibliometric Analysis, Critical Issues, and Key Gaps / 2403.14681 / ISBN:https://doi.org/10.48550/arXiv.2403.14681 / Published by ArXiv / on (web) Publishing site
- Method
AI Ethics Development Phases Based on Keyword Analysis
Key AI Ethics Issues
Key Gaps
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
- Introduction
Methodology
Results
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
6 Bias and Fairness
8 Implementation Framework
9 A Few Suggestions for a Viable Path Forward
10 Summary and Next Steps
A Appendix
References - Analyzing Potential Solutions Involving Regulation to Escape Some of AI's Ethical Concerns / 2403.15507 / ISBN:https://doi.org/10.48550/arXiv.2403.15507 / Published by ArXiv / on (web) Publishing site
- Various AI Ethical Concerns
A Possible Solution to These Concerns With Business Self-Regulation
A Possible Solution to These Concerns With Government Regulation
Feasibility of Government Regulation
References - The Pursuit of Fairness in Artificial Intelligence Models A Survey / 2403.17333 / ISBN:https://doi.org/10.48550/arXiv.2403.17333 / Published by ArXiv / on (web) Publishing site
- 3 Conceptualizing Fairness and Bias in ML
5 Ways to mitigate bias and promote Fairness
6 How Users can be affected by unfair ML Systems
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
- 3 Blueprints for AI Evaluation in
Journalism
- Power and Play Investigating License to Critique in Teams AI Ethics Discussions / 2403.19049 / ISBN:https://doi.org/10.48550/arXiv.2403.19049 / Published by ArXiv / on (web) Publishing site
- 1 Introduction and Related Work
3 RQ1: What Factors Influence Members’ “Licens to Critique” when Discussing AI Ethics with their Team?
5 Discussion
References - Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness / 2403.20089 / ISBN:https://doi.org/10.48550/arXiv.2403.20089 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 Implications of the AI Act
References - AI Act and Large Language Models (LLMs): When critical issues and privacy impact require human and ethical oversight / 2404.00600 / ISBN:https://doi.org/10.48550/arXiv.2404.00600 / Published by ArXiv / on (web) Publishing site
- 5. Human Oversight
6. Large Language Models (LLMs) - Introduction - Exploring the Nexus of Large Language Models and Legal Systems: A Short Survey / 2404.00990 / ISBN:https://doi.org/10.48550/arXiv.2404.00990 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Applications of Large Language Models in Legal Tasks
3 Fine-Tuned Large Language Models in Various Countries and Regions
4 Legal Problems of Large Languge Models
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
- VI. Threats to Validity
VII. Conclusion - 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
- 4 Findings
7 Conclusion - Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage / 2404.06077 / ISBN:https://doi.org/10.48550/arXiv.2404.06077 / Published by ArXiv / on (web) Publishing site
- I. Introduction
III. Proposed Design: IBIS
V. Implementation on DAML
VI. Evaluation
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
- 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
2 Background
3 Methodology
4 Critical Survey
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
- 1 Introduction
2 Learning from Feedback
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
4 Public Opinion on AI Governance
7 Discussion
8 Conclusion
References - Generative Ghosts: Anticipating Benefits and Risks of AI Afterlives / 2402.01662 / ISBN:https://doi.org/10.48550/arXiv.2402.01662 / Published by ArXiv / on (web) Publishing site
- Related Work
Generative Ghosts: A Design Space
Anticipating Benefits and Risks of Generative Ghosts
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
4 Grey Skin as Technofix: Failures to Lodge Located Complaints
5 Alternative AI Ethics: Space for Embodied Complaints
6 Conclusions: Towards Humble Technical Practices
References - On the role of ethics and sustainability in business innovation / 2404.07678 / ISBN:https://doi.org/10.48550/arXiv.2404.07678 / Published by ArXiv / on (web) Publishing site
- Ethical considera5ons
Sustainability considera5ons
Recommenda5ons - PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Models / 2404.08699 / ISBN:https://doi.org/10.48550/arXiv.2404.08699 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background and Related Work
3 Methodology
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
- II. Literature Review
III. Proposed Methodology - Debunking Robot Rights Metaphysically, Ethically, and Legally / 2404.10072 / ISBN:https://doi.org/10.48550/arXiv.2404.10072 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 The Robots at Issue
7 The Legal Perspective
8 The Troubling Implications of Legal Rationales for Robot Rights
9 The Enduring Irresponsibility of AI Rights Talk
References - Characterizing and modeling harms from interactions with design patterns in AI interfaces / 2404.11370 / ISBN:https://doi.org/10.48550/arXiv.2404.11370 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Scoping Review of Design Patterns, Affordances, and Harms in AI Interfaces
4 DECAI: Design-Enhanced Control of AI Systems
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
- 2 EU Public Policy Analysis
3 A Geo-Political AI Risk Taxonomy
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
- 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
- 4 LLM Lifecycle
5 Downstream Ecosystem
References - The Necessity of AI Audit Standards Boards / 2404.13060 / ISBN:https://doi.org/10.48550/arXiv.2404.13060 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 3 Governance for safety
4 4 Auditing standards body, not standard audits
References - Modeling Emotions and Ethics with Large Language Models / 2404.13071 / ISBN:https://doi.org/10.48550/arXiv.2404.13071 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Qualifying and Quantifying Ethics - 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
- I. Introduction
II. Comprehensive Governance of Emerging Technologies
III. A Practical Multilevel Governance Framework for AIs
IV. Application of the Framework for the Development of AIs
References - Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis / 2404.13861 / ISBN:https://doi.org/10.48550/arXiv.2404.13861 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Mechanistic Agency: A Common View in AI Practice
4 Alternatives to AI as Agent
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
3 Substantive and Procedural Transparency are Necessary for Deploying Effective and Ethical AI systems
4 Building Towards Better Governance of Government AI
References - Who Followed the Blueprint? Analyzing the Responses of U.S. Federal Agencies to the Blueprint for an AI Bill of Rights / 2404.19076 / ISBN:https://doi.org/10.48550/arXiv.2404.19076 / Published by ArXiv / on (web) Publishing site
- Abstract
Findings - 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
- 3 Lessons from History: War Elephants
4 Discussion
5 Conclusions - Not a Swiss Army Knife: Academics' Perceptions of Trade-Offs Around Generative Artificial Intelligence Use / 2405.00995 / ISBN:https://doi.org/10.48550/arXiv.2405.00995 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
4 Findings
5 Discussion
7 Conclusion
References - Towards an Ethical and Inclusive Implementation of Artificial Intelligence in Organizations: A Multidimensional Framework / 2405.01697 / ISBN:https://doi.org/10.48550/arXiv.2405.01697 / Published by ArXiv / on (web) Publishing site
- Abstract
2 How can organizations participate
3 Four Pillars for Implementing an Ethical Framework in Organizations - 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
- 3 Finance
5 Law
6 Ethics
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
- 1. Introduction
2. Current State of AWS
3. AWS Proliferation and Threats to Academic Research
4. Policy Recommendations
Impact Statement
References - Responsible AI: Portraits with Intelligent Bibliometrics / 2405.02846 / ISBN:https://doi.org/10.48550/arXiv.2405.02846 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Conceptualization: Responsible AI
III. Data and Methodology
IV. Bibliometric Portraits of Responsible AI
References - Exploring the Potential of the Large Language Models (LLMs) in Identifying Misleading News Headlines / 2405.03153 / ISBN:https://doi.org/10.48550/arXiv.2405.03153 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Results - 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
- 1 Introduction
2 Motivation
3 Proposed Organizational Forms
4 Interaction Mechanisms - A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI / 2405.04333 / ISBN:https://doi.org/10.48550/arXiv.2405.04333 / Published by ArXiv / on (web) Publishing site
- Glossary of Terms
1. Introduction
3. A Spectrum of Scenarios of Open Data for Generative AI
Appendix - Guiding the Way: A Comprehensive Examination of AI Guidelines in Global Media / 2405.04706 / ISBN:https://doi.org/10.48550/arXiv.2405.04706 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Theoretical Framework
3 Data and Methods
4 Results
5 Discussion and conclusions - Trustworthy AI-Generative Content in Intelligent 6G Network: Adversarial, Privacy, and Fairness / 2405.05930 / ISBN:https://doi.org/10.48550/arXiv.2405.05930 / Published by ArXiv / on (web) Publishing site
- V. Fairness of AIGC in 6G Network
- RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical Roles / 2307.15158 / ISBN:https://doi.org/10.48550/arXiv.2307.15158 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
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 - 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
- 2
Related Work
3 Methods
5 Analyses of the Design Process
7 Discussion
8 Limitations and Future Work
References - XXAI: Towards eXplicitly eXplainable Artificial Intelligence / 2401.03093 / ISBN:https://doi.org/10.48550/arXiv.2401.03093 / Published by ArXiv / on (web) Publishing site
- 1.
Introduction
4. Discussion of the problems of symbolic AI and ways to overcome them
References - Should agentic conversational AI change how we think about ethics? Characterising an interactional ethics centred on respect / 2401.09082 / ISBN:https://doi.org/10.48550/arXiv.2401.09082 / Published by ArXiv / on (web) Publishing site
- 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
- 1 Introduction
2 Between Human Intelligence and Technology: AGI’s Dual Value-Laden Pedigrees
3 The Motley Choices of AGI Discourse
4 Towards Contextualized, Politically Legitimate, and Social Intelligence
5 Conclusion: Politically Legitimate Intelligence
References
A Dimensions of AGI: a Summary - Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators / 2402.01708 / ISBN:https://doi.org/10.48550/arXiv.2402.01708 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
7 Discussion
References
A Appendix - Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback / 2404.10271 / ISBN:https://doi.org/10.48550/arXiv.2404.10271 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Background
7. Which Traditional Social-Choice-Theoretic Concepts Are Most Relevant?
9. How Do We Navigate a Multiplicity of AIs?
10. Conclusion
Impact Statement
References - A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs) / 2405.03066 / ISBN:https://doi.org/10.48550/arXiv.2405.03066 / Published by ArXiv / on (web) Publishing site
- 2 Materials
3 Results
4 Discussion - Integrating Emotional and Linguistic Models for Ethical Compliance in Large Language Models / 2405.07076 / ISBN:https://doi.org/10.48550/arXiv.2405.07076 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
3 Quantitative Models of Emotions, Behaviors, and Ethics
Appendix S: Multiple Adversarial LLMs
Appendix B: Polarized Emotions in One Article - Using ChatGPT for Thematic Analysis / 2405.08828 / ISBN:https://doi.org/10.48550/arXiv.2405.08828 / Published by ArXiv / on (web) Publishing site
- 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
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
3 RQ2: What Technical Strategies Can Be Employed to Mitigate the Negative Consequences of AI Autophagy?
5 Conclusions and Outlook - 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
- 1.
Introduction
5.Quality Metrics Performance - The Narrow Depth and Breadth of Corporate Responsible AI Research / 2405.12193 / ISBN:https://doi.org/10.48550/arXiv.2405.12193 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Motivations for Industry to Engage in Responsible AI Research
4 The Narrow Depth of Industry’s Responsible AI Research
5 The Narrow Breadth of Industry’s Responsible AI Research
6 Limited Adoption of Responsible AI Research in Commercialization: Patent Citation Analysis
7 Discussion
References
S1 Additional Analyses on Engagement Analysis
S2 Additional Analyses on Linguistic Analysis - Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems / 2405.13191 / ISBN:https://doi.org/10.48550/arXiv.2405.13191 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 The Audit Procedure
4 Conducting the Pilots
6 Conclusion and Outlook
References - A Comprehensive Overview of Large Language Models (LLMs) for Cyber Defences: Opportunities and Directions / 2405.14487 / ISBN:https://doi.org/10.48550/arXiv.2405.14487 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Threat Intelligence
III. Vulnerability Assessment
IV. Network Security
V. Privacy Preservation
VII. Cyber Security Operations Automation
IX. Challenges and Open Problems
References - Towards Clinical AI Fairness: Filling Gaps in the Puzzle / 2405.17921 / ISBN:https://doi.org/10.48550/arXiv.2405.17921 / Published by ArXiv / on (web) Publishing site
- Main
Methods in clinical AI fairness research
Methods
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
- 4 Following the RRI, (Responsible research innovation)
principles
5 Technology and society, a complex relationship
6 Technological mediation
7 Conclusion - The Future of Child Development in the AI Era. Cross-Disciplinary Perspectives Between AI and Child Development Experts / 2405.19275 / ISBN:https://doi.org/10.48550/arXiv.2405.19275 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Anticipated AI Use for Children
3. Discussion
Bibliography - Using Large Language Models for Humanitarian Frontline Negotiation: Opportunities and Considerations / 2405.20195 / ISBN:https://doi.org/10.48550/arXiv.2405.20195 / Published by ArXiv / on (web) Publishing site
- 2. Related Work
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
- Paper
- 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
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
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
3 Framework
4 Discussion
References - Transforming Computer Security and Public Trust Through the Exploration of Fine-Tuning Large Language Models / 2406.00628 / ISBN:https://doi.org/10.48550/arXiv.2406.00628 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Comparative Analysis of Pre-Trained Models. - How Ethical Should AI Be? How AI Alignment Shapes the Risk Preferences of LLMs / 2406.01168 / ISBN:https://doi.org/10.48550/arXiv.2406.01168 / Published by ArXiv / on (web) Publishing site
- Introduction
II. Risk Characteristics of LLMs
III. Impact of Alignment on LLMs’ Risk Preferences
IV. Impact of Alignments on Corporate Investment Forecasts
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
4 Fairness violation analysis in BRIO
5 Risk assessment in BRIO
6 Risk analysis via BRIO for the German Credit Dataset
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
- 1. Introduction
3. Related Work
4. Desiderata
5. Methodology
6. Discussion
7. Conclusions
References - MoralBench: Moral Evaluation of LLMs / 2406.04428 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
References - Can Prompt Modifiers Control Bias? A Comparative Analysis of Text-to-Image Generative Models / 2406.05602 / Published by ArXiv / on (web) Publishing site
- 2. Related Work
3. Bias Evaluation
References - Deception Analysis with Artificial Intelligence: An Interdisciplinary Perspective / 2406.05724 / ISBN:https://doi.org/10.48550/arXiv.2406.05724 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Theories and Components of Deception
3 Reductionism & Previous Research in Deceptive AI
4 DAMAS: A MAS Framework for Deception Analysis
5 Conclusion
References - The Impact of AI on Academic Research and Publishing / 2406.06009 / Published by ArXiv / on (web) Publishing site
- Introduction
- An Empirical Design Justice Approach to Identifying Ethical Considerations in the Intersection of Large Language Models and Social Robotics / 2406.06400 / ISBN:https://doi.org/10.48550/arXiv.2406.06400 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Theoretical Background
3 Methodology
4 Findings
6 Conclusions and Recommendations
References - The Ethics of Interaction: Mitigating Security Threats in LLMs / 2401.12273 / ISBN:https://doi.org/10.48550/arXiv.2401.12273 / Published by ArXiv / on (web) Publishing site
- 2 Why Ethics Matter in LLM Attacks?
3 Potential Misuse and Security Concerns
6 Ethical Response to LLM Attacks - Global AI Governance in Healthcare: A Cross-Jurisdictional Regulatory Analysis / 2406.08695 / ISBN:https://doi.org/10.48550/arXiv.2406.08695 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
4 Global Regulatory Landscape of AI
5 Generative AI: The New Frontier
6 Results and Conclusion
7 Future Directions
References
A Supplemental Tables - Fair by design: A sociotechnical approach to justifying the fairness of AI-enabled systems across the lifecycle / 2406.09029 / ISBN:https://doi.org/10.48550/arXiv.2406.09029 / Published by ArXiv / on (web) Publishing site
- 3 Assuring fairness across the AI lifecycle
4 Assuring AI fairness in healthcare
References - Some things never change: how far generative AI can really change software engineering practice / 2406.09725 / ISBN:https://doi.org/10.48550/arXiv.2406.09725 / Published by ArXiv / on (web) Publishing site
- 3 Methodology
4 Results - Federated Learning driven Large Language Models for Swarm Intelligence: A Survey / 2406.09831 / ISBN:https://doi.org/10.48550/arXiv.2406.09831 / Published by ArXiv / on (web) Publishing site
- III. Federated LLMs for Smarm Intelligence
IV. Learned Lessons and Open Challenges - Applications of Generative AI in Healthcare: algorithmic, ethical, legal and societal considerations / 2406.10632 / ISBN:https://doi.org/10.48550/arXiv.2406.10632 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Selection of application
III. Analysis
IV. Conclusion
References
Appendix B Legal aspects
Appendix C Algorithmic / technical aspects - Justice in Healthcare Artificial Intelligence in Africa / 2406.10653 / ISBN:https://doi.org/10.48550/arXiv.2406.10653 / Published by ArXiv / on (web) Publishing site
- Introduction
1. Beyond Bias and Fairness
2. Bridging the Justice Gap
3. Ensuring Equitable Access to AI Technologies
4. Prioritizing the Common Good Over Corporate Greed
5. Promoting Global Solidarity
References - Conversational Agents as Catalysts for Critical Thinking: Challenging Design Fixation in Group Design / 2406.11125 / ISBN:https://doi.org/10.48550/arXiv.2406.11125 / Published by ArXiv / on (web) Publishing site
- Abstract
2 BEYOND RECOMMENDATIONS: ENHANCING CRITICAL THINKING WITH GENERATIVE AI
3 CHALLENGES AND OPPORTUNITIES OF USING CONVERSATIONAL AGENTS IN GROUP DESIGN
4 POTENTIAL SCENARIO AND APPLICATIONS OF CONVERSATIONAL AGENTS IN GROUP DESIGN PROCESS
6 POTENTIAL DESIGN CONSIDERATIONS
7 CONCLUSION
REFERENCES - Current state of LLM Risks and AI Guardrails / 2406.12934 / ISBN:https://doi.org/10.48550/arXiv.2406.12934 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Large Language Model Risks
3 Strategies in Securing Large Language models
References - Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Health / 2406.13659 / ISBN:https://doi.org/10.48550/arXiv.2406.13659 / Published by ArXiv / on (web) Publishing site
- IV. DISCUSSION AND F UTURE D IRECTIONS
REFERENCES - Documenting Ethical Considerations in Open Source AI Models / 2406.18071 / ISBN:https://doi.org/10.48550/arXiv.2406.18071 / Published by ArXiv / on (web) Publishing site
- 1 INTRODUCTION
3 METHODOLOGY AND STUDY DESIGN
4 RESULTS
REFERENCES - AI Alignment through Reinforcement Learning from Human Feedback? Contradictions and Limitations / 2406.18346 / ISBN:https://doi.org/10.48550/arXiv.2406.18346 / Published by ArXiv / on (web) Publishing site
- 4 The Internal Tensions and Ethical Issues in RLxF
5 Rebooting Safety and Alignment: Integrating AI Ethics and System Safety
References - A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics / 2406.18812 / ISBN:https://doi.org/10.48550/arXiv.2406.18812 / Published by ArXiv / on (web) Publishing site
- II. BACKGROUND
IV. DT-INTEGRATED ROBOTICS DESIGN CONSIDERATIONS AND DISCUSSION
REFERENCES - Staying vigilant in the Age of AI: From content generation to content authentication / 2407.00922 / ISBN:https://doi.org/10.48550/arXiv.2407.00922 / Published by ArXiv / on (web) Publishing site
- Abstract
Art Practice: Human Reactions to Synthetic Fake Content
Emphasizing Reasoning Over Detection
Conclusions and Future Works - SecGenAI: Enhancing Security of Cloud-based Generative AI Applications within Australian Critical Technologies of National Interest / 2407.01110 / ISBN:https://doi.org/10.48550/arXiv.2407.01110 / Published by ArXiv / on (web) Publishing site
- II. UNDERSTANDING GENAI SECURITY
III. CRITICAL ANALYSIS
IV. SECGENAI FRAMEWORK REQUIREMENTS SPECIFICATIONS
REFERENCES - Artificial intelligence, rationalization, and the limits of control in the public sector: the case of tax policy optimization / 2407.05336 / ISBN:https://doi.org/10.48550/arXiv.2407.05336 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Artificial intelligence as Weberian rationalization
3. Bureaucratization, tax policy, and equality
4. AI-driven tax policy to reduce economic inequality: a thought experiment
5. Freedom, equality, and self-determination in the iron cage
6. Conclusion
References - A Blueprint for Auditing Generative AI / 2407.05338 / ISBN:https://doi.org/10.48550/arXiv.2407.05338 / Published by ArXiv / on (web) Publishing site
- 2 Why audit generative AI systems?
3 How to audit generative AI systems?
4 Governance audits
5 Model audits
7 Clarifications and limitations
8 Conclusion
Bibliography - Challenges and Best Practices in Corporate AI Governance:Lessons from the Biopharmaceutical Industry / 2407.05339 / ISBN:https://doi.org/10.48550/arXiv.2407.05339 / Published by ArXiv / on (web) Publishing site
- 1 Introduction | The need for corporate AI governance
2 Case study | AstraZeneca’s AI governance journey
3 Practical implementation challenges | What to be prepared for?
6 References - Operationalising AI governance through ethics-based auditing: An industry case study / 2407.06232 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. The need to operationalise AI governance
3. AstraZeneca and AI governance
6. Lessons learned from AstraZeneca’s 2021 AI audit
8. Conclusions
REFERENCES
APPENDIX 1 - Auditing of AI: Legal, Ethical and Technical Approaches / 2407.06235 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 The evolution of auditing as a governance mechanism
3 The need to audit AI systems – a confluence of top-down and bottom-up pressures
4 Auditing of AI’s multidisciplinary foundations
6 Concluding remarks
References - Why should we ever automate moral decision making? / 2407.07671 / ISBN:https://doi.org/10.48550/arXiv.2407.07671 / Published by ArXiv / on (web) Publishing site
- 2 Reasons for automated moral decision making
- Potential Societal Biases of ChatGPT in Higher Education: A Scoping Review / 2311.14381 / ISBN:https://doi.org/10.48550/arXiv.2311.14381 / Published by ArXiv / on (web) Publishing site
- REFERENCES
- FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare / 2309.12325 / ISBN:https://doi.org/10.48550/arXiv.2309.12325 / Published by ArXiv / on (web) Publishing site
- REFERENCES:
- Bridging the Global Divide in AI Regulation: A Proposal for a Contextual, Coherent, and Commensurable Framework / 2303.11196 / ISBN:https://doi.org/10.48550/arXiv.2303.11196 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Global Divide in AI Regulation: Horizontally. Context-Specific
III. Striking a Balance Betweeen the Two Approaches
IV. Proposing an Alternative 3C Framework
V. Conclusion - Past, Present, and Future: A Survey of The Evolution of Affective Robotics For Well-being / 2407.02957 / ISBN:https://doi.org/10.48550/arXiv.2407.02957 / Published by ArXiv / on (web) Publishing site
- I. Introduction
III. Method
IV. Evolution of Affective Robots for Well-Being
V. 10 Years of Affectivbe Robotics - With Great Power Comes Great Responsibility: The Role of Software Engineers / 2407.08823 / ISBN:https://doi.org/10.48550/arXiv.2407.08823 / Published by ArXiv / on (web) Publishing site
- 2 Background and Related Work
References - Have We Reached AGI? Comparing ChatGPT, Claude, and Gemini to Human Literacy and Education Benchmarks / 2407.09573 / ISBN:https://doi.org/10.48550/arXiv.2407.09573 / Published by ArXiv / on (web) Publishing site
- 5 Discussion
- Generative AI for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations / 2407.11054 / ISBN:https://doi.org/10.48550/arXiv.2407.11054 / Published by ArXiv / on (web) Publishing site
- Limitations of generative AI in HTA applications
Policy landscape
Appendix
References - Thorns and Algorithms: Navigating Generative AI Challenges Inspired by Giraffes and Acacias / 2407.11360 / ISBN:https://doi.org/10.48550/arXiv.2407.11360 / Published by ArXiv / on (web) Publishing site
- 3 Giraffe and Acacia: Reciprocal Adaptations and Shaping
4 Generative AI and Humans: Risks and Mitigation
5 Meta Analysis: Limits of the Analogy
References - Prioritizing High-Consequence Biological Capabilities in Evaluations of Artificial Intelligence Models / 2407.13059 / ISBN:https://doi.org/10.48550/arXiv.2407.13059 / Published by ArXiv / on (web) Publishing site
- Introduction
Proposed Approach to Determining High-Consequence Biological Capabilities of Concern
References - Report on the Conference on Ethical and Responsible Design in the National AI Institutes: A Summary of Challenges / 2407.13926 / ISBN:https://doi.org/10.48550/arXiv.2407.13926 / Published by ArXiv / on (web) Publishing site
- 2. Ethics Frameworks
3. AI Institutes and Society - Assurance of AI Systems From a Dependability Perspective / 2407.13948 / ISBN:https://doi.org/10.48550/arXiv.2407.13948 / Published by ArXiv / on (web) Publishing site
- 2 Assurance for Systems Extended with AI and ML
3 Assurance of AI Systems for Specific Functions
4 Assurance for General-Purpose AI
5 Assurance and Alignment for AGI
References - Open Artificial Knowledge / 2407.14371 / ISBN:https://doi.org/10.48550/arXiv.2407.14371 / Published by ArXiv / on (web) Publishing site
- Appendices
- Honest Computing: Achieving demonstrable data lineage and provenance for driving data and process-sensitive policies / 2407.14390 / ISBN:https://doi.org/10.48550/arXiv.2407.14390 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Threat Model for Honest Computing
3. Honest Computing reference specifications
4. Discussion
5. Conclusion
References - RogueGPT: dis-ethical tuning transforms ChatGPT4 into a Rogue AI in 158 Words / 2407.15009 / ISBN:https://doi.org/10.48550/arXiv.2407.15009 / Published by ArXiv / on (web) Publishing site
- II. Background
III. Methodology
IV. Results
V. Benchmarking with Chat GPT4 Default Interface
VI. Discussion
References - Nudging Using Autonomous Agents: Risks and Ethical Considerations / 2407.16362 / ISBN:https://doi.org/10.48550/arXiv.2407.16362 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Technology Mediated Nudging
3 Examples of Biases
4 Ethical Considerations
5 Principles for the Nudge Lifecycle - Mapping the individual, social, and biospheric impacts of Foundation Models / 2407.17129 / ISBN:https://doi.org/10.48550/arXiv.2407.17129 / Published by ArXiv / on (web) Publishing site
- Abstract
3 Methods: Snowball and Structured Search
4 Mapping Individual, Social, and Biospheric Impacts of Foundation Models
5 Discussion: Grappling with the Scale and Interconnectedness of Foundation Models
Impact Statement
References
A Appendix - Navigating the United States Legislative Landscape on Voice Privacy: Existing Laws, Proposed Bills, Protection for Children, and Synthetic Data for AI / 2407.19677 / ISBN:https://doi.org/10.48550/arXiv.2407.19677 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
6. Conclusion - Exploring the Role of Social Support when Integrating Generative AI into Small Business Workflows / 2407.21404 / ISBN:https://doi.org/10.48550/arXiv.2407.21404 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 Methodology
4 Findings
6 Discussion and Future Work
References
A Example Storyboards - Deepfake Media Forensics: State of the Art and Challenges Ahead / 2408.00388 / ISBN:https://doi.org/10.48550/arXiv.2408.00388 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
4. Passive Deepfake Authentication Methods
5. Deepfakes Detection Method on Realistic Scenarios
VII. Conclusion - Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework / 2408.00965 / ISBN:https://doi.org/10.48550/arXiv.2408.00965 / Published by ArXiv / on (web) Publishing site
- 2 Background and Literature Review
4 ESG-AI framework
5 Discussion
References - AI for All: Identifying AI incidents Related to Diversity and Inclusion / 2408.01438 / ISBN:https://doi.org/10.48550/arXiv.2408.01438 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Methodology
4 Results - Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governance / 2408.01458 / ISBN:https://doi.org/10.48550/arXiv.2408.01458 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 Methods
4 Large-Scale Surveys of AI in the Literature
5 Discussion
7 Research Ethics and Social Impact
References
A Known Limitations of Surveys
B Additional Materials for Pilot Survey - Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity / 2408.04023 / ISBN:https://doi.org/10.48550/arXiv.2408.04023 / Published by ArXiv / on (web) Publishing site
- 3. Proposed framework
References - AI-Driven Chatbot for Intrusion Detection in Edge Networks: Enhancing Cybersecurity with Ethical User Consent / 2408.04281 / ISBN:https://doi.org/10.48550/arXiv.2408.04281 / Published by ArXiv / on (web) Publishing site
- II. Related Work
III. Methodology - Criticizing Ethics According to Artificial Intelligence / 2408.04609 / ISBN:https://doi.org/10.48550/arXiv.2408.04609 / Published by ArXiv / on (web) Publishing site
- 2 Clarifying conceptual ambiguities
5 Investigating fundamental normative issues - Between Copyright and Computer Science: The Law and Ethics of Generative AI / 2403.14653 / ISBN:https://doi.org/10.48550/arXiv.2403.14653 / Published by ArXiv / on (web) Publishing site
- I. The Why and How Behind LLMs
III. A Guide for Data in LLM Research
IV. The Path Ahead - The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources / 2406.16746 / ISBN:https://doi.org/10.48550/arXiv.2406.16746 / Published by ArXiv / on (web) Publishing site
- 5 Data Documentation and Release
6 Model Training
References - Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives / 2407.14962 / ISBN:https://doi.org/10.48550/arXiv.2407.14962 / Published by ArXiv / on (web) Publishing site
- II. Generative AI
III. Language Modeling
IV. Challenges of Generative AI and LLMs
References - VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative Adversary / 2407.19524 / ISBN:https://doi.org/10.48550/arXiv.2407.19524 / Published by ArXiv / on (web) Publishing site
- Appendices
- Speculations on Uncertainty and Humane Algorithms / 2408.06736 / ISBN:https://doi.org/10.48550/arXiv.2408.06736 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 The Numbers of the Future
3 Uncertainty Ex Machina
References - Visualization Atlases: Explaining and Exploring Complex Topics through Data, Visualization, and Narration / 2408.07483 / ISBN:https://doi.org/10.48550/arXiv.2408.07483 / Published by ArXiv / on (web) Publishing site
- 2 Visualization Atlases : Examples and Collection
3 Visualization Atlas Design Patterns
4 Interviews with Visualization Atlas Creators
5 Visualization Atlases Genres
7 Discussion - Neuro-Symbolic AI for Military Applications / 2408.09224 / ISBN:https://doi.org/10.48550/arXiv.2408.09224 / Published by ArXiv / on (web) Publishing site
- II. Neuro-Symbolic AI
III. Autonomy in Military Weapons Systems
IV. Military Applications of Neuro-Symbolic AI
V. Challenges and Risks
VI. Interpretability and Explainability
References - Conference Submission and Review Policies to Foster Responsible Computing Research / 2408.09678 / ISBN:https://doi.org/10.48550/arXiv.2408.09678 / Published by ArXiv / on (web) Publishing site
- Introduction
Ethics Board Review
Obtaining Consent
Use of Generative AI in CS Conference Publications
References - Don't Kill the Baby: The Case for AI in Arbitration / 2408.11608 / ISBN:https://doi.org/10.48550/arXiv.2408.11608 / Published by ArXiv / on (web) Publishing site
- Introduction
1. What is AI
3. Practical and Strategic Benefits of Using AI in Arbitration
Part II. The Critics are Killing the Baby
2. Let AI Grow Under Favorable Conditions: Avoiding Overly Moralistic Views
3. Arbitration Should Allow Flexible, Contract-Based Experimentation in a Fast- Evolving Regulatory Landscape - CIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical Researcher / 2408.11650 / ISBN:https://doi.org/10.48550/arXiv.2408.11650 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Background and Related Works
3. Methodology
4. Experiment Results - The Problems with Proxies: Making Data Work Visible through Requester Practices / 2408.11667 / ISBN:https://doi.org/10.48550/arXiv.2408.11667 / Published by ArXiv / on (web) Publishing site
- Introduction
Findings
References - Promises and challenges of generative artificial intelligence for human learning / 2408.12143 / ISBN:https://doi.org/10.48550/arXiv.2408.12143 / Published by ArXiv / on (web) Publishing site
- 5 Conclusion and Future Directions
References - Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Operationalizable minimum requirements
3 European Union AI Act: a brief overview
4 Compliance and implementation of the suggested assessments
5 Overall Ethical Requirements (O)
6 Fairness (F)
8 Safety and Robustness (SR)
9 Sustainability (SU)
10 Transparency and Explainability (T)
11 Truthfulness (TR) - Dataset | Mindset = Explainable AI | Interpretable AI / 2408.12420 / ISBN:https://doi.org/10.48550/arXiv.2408.12420 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
3. Database and Experimental Setup
References - Is Generative AI the Next Tactical Cyber Weapon For Threat Actors? Unforeseen Implications of AI Generated Cyber Attacks / 2408.12806 / ISBN:https://doi.org/10.48550/arXiv.2408.12806 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Related Work
IV. Attack Methodology
V. Conclusion
References - Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey / 2408.12880 / ISBN:https://doi.org/10.48550/arXiv.2408.12880 / Published by ArXiv / on (web) Publishing site
- 4 Contrastice Foundation Models (CFMs)
5 Multimodal LLMs (MLLMs)
6 Discussions of Current Studies
7 Challenges and Future Directions
References - Aligning XAI with EU Regulations for Smart Biomedical Devices: A Methodology for Compliance Analysis / 2408.15121 / ISBN:https://doi.org/10.48550/arXiv.2408.15121 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
6 A Categorisation of XAI in Terms of Explanatory Goals
7 Case Studies: Closed-Loop and Semi-Closed-Loop Control
9 Threats to Validity
References - What Is Required for Empathic AI? It Depends, and Why That Matters for AI Developers and Users / 2408.15354 / ISBN:https://doi.org/10.48550/arXiv.2408.15354 / Published by ArXiv / on (web) Publishing site
- “Fine cuts” of Empathy: Capabilities and
Distinctions under the Empathy Umbrella
What Empathic Capabilities Do AIs Need?
Implications for AI Creators and Users
References - Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems / 2408.15550 / ISBN:https://doi.org/10.48550/arXiv.2408.15550 / Published by ArXiv / on (web) Publishing site
- 2 Trustworthy and Responsible AI Definition
3 Governance for Human-Centric Intelligence Systems
4 Biases
5 Trustworthy and Responsible AI in Human-centric Applications
6 Open Challenges
7 Guidelines and Recommendations
8 Conclusion and Final Remarks
References - A Survey for Large Language Models in Biomedicine / 2409.00133 / ISBN:https://doi.org/10.48550/arXiv.2409.00133 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Adapting General LLMs to the Biomedical Field
5 Discussion - Digital Homunculi: Reimagining Democracy Research with Generative Agents / 2409.00826 / ISBN:https://doi.org/10.48550/arXiv.2409.00826 / Published by ArXiv / on (web) Publishing site
- 2. The Experimentation Bottleneck
4. Risks and Caveats
5. Annoyances or Dealbreakers?
References - The overlooked need for Ethics in Complexity Science: Why it matters / 2409.02002 / ISBN:https://doi.org/10.48550/arXiv.2409.02002 / Published by ArXiv / on (web) Publishing site
- Introduction
Mapping ethical challenges in complexity science
Limited research on ethics in complexity science
Practical considerations for ethical actions in complexity science - AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities / 2409.02017 / ISBN:https://doi.org/10.48550/arXiv.2409.02017 / Published by ArXiv / on (web) Publishing site
- Background
Results
Limitation
References - Preliminary Insights on Industry Practices for Addressing Fairness Debt / 2409.02432 / ISBN:https://doi.org/10.48550/arXiv.2409.02432 / Published by ArXiv / on (web) Publishing site
- 4 Findings
- DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection / 2409.06072 / ISBN:https://doi.org/10.48550/arXiv.2409.06072 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Prior Benchmarks
3 Data Details - Exploring AI Futures Through Fictional News Articles / 2409.06354 / ISBN:https://doi.org/10.48550/arXiv.2409.06354 / Published by ArXiv / on (web) Publishing site
- Introduction
Reflections from two workshop participants - Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cubeà / 2402.01760 / ISBN:https://doi.org/10.48550/arXiv.2402.01760 / Published by ArXiv / on (web) Publishing site
- D. CausalRating: A Tool To Rate Sentiments Analysis Systems for Bias
- Face Recognition: to Deploy or not to Deploy? A Framework for Assessing the Proportional Use of Face Recognition Systems in Real-World Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
- References
- The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources / 2406.16746 / ISBN:https://doi.org/10.48550/arXiv.2406.16746 / Published by ArXiv / on (web) Publishing site
- B Cheatsheet Samples
- Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site
- References
- The overlooked need for Ethics in Complexity Science: Why it matters / 2409.02002 / ISBN:https://doi.org/10.48550/arXiv.2409.02002 / Published by ArXiv / on (web) Publishing site
- Annexus