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Bibliography items where occurs: 195
- The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site
- Report highlights
Chapter 2 Technical Performance
Chapter 3 Technical AI Ethics
Chapter 5 AI Policy and Governance
Appendix - Exciting, Useful, Worrying, Futuristic:
Public Perception of Artificial Intelligence in 8 Countries / 2001.00081 / ISBN:https://doi.org/10.48550/arXiv.2001.00081 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background
3 Methodology
4 Findings
5 Discussion
References - Ethics of AI: A Systematic Literature Review of Principles and Challenges / 2109.07906 / ISBN:https://doi.org/10.48550/arXiv.2109.07906 / Published by ArXiv / on (web) Publishing site
- Abstract
2 Background
5 Detail results and analysis
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
- 1Introduction
2 Related Work
4 Results
5 Discussion
References - The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis / 2206.03225 / ISBN:https://doi.org/10.48550/arXiv.2206.03225 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 Study Methodology
4 Evaluation of Ethical AI Principles
5 Evaluation of Ethical Principle Implementations
6 Gap Mitigation
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
- Abstract
1 Introduction
2 Related Work
3 Methodology
4 Results
5 Discussion - Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society / 2001.04335 / ISBN:https://doi.org/10.48550/arXiv.2001.04335 / Published by ArXiv / on (web) Publishing site
- 2 The Near-Long
3 The Problem with the Near/Long-Term Distinction
References - ESR: Ethics and Society Review of Artificial Intelligence Research / 2106.11521 / ISBN:https://doi.org/10.48550/arXiv.2106.11521 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
3 The ESR Process
4 Deployment and Evaluation
5 Discussion
References - On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services / 2111.01306 / ISBN:https://doi.org/10.48550/arXiv.2111.01306 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 The Need forEthical AI in Finance
3 Practical Challengesof Ethical AI
References - A primer on AI ethics via arXiv- focus 2020-2023 / Kaggle / on (web) Publishing site
- Section 1: Introduction and concept
Section 2: History and prospective
Section 3: Current trends 2020-2023 - What does it mean to be a responsible AI practitioner: An ontology of roles and skills / 2205.03946 / ISBN:https://doi.org/10.48550/arXiv.2205.03946 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background
3 Methodology
4 Proposed competency framework for responsible AI practitioners
5 Discussion
References
Appendix A supplementary material - GPT detectors are biased against non-native English writers / 2304.02819 / ISBN:https://doi.org/10.48550/arXiv.2304.02819 / Published by ArXiv / on (web) Publishing site
- Introduction
References - Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects / 2304.08275 / ISBN:https://doi.org/10.48550/arXiv.2304.08275 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Underlying Aspects
III. Interactions between Aspects
IV. Concluding Remarks
References - QB4AIRA: A Question Bank for AI Risk Assessment / 2305.09300 / ISBN:https://doi.org/10.48550/arXiv.2305.09300 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 The Question Bank: QB4AIRA
3 Evaluation - A multilevel framework for AI governance / 2307.03198 / ISBN:https://doi.org/10.48550/arXiv.2307.03198 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introductioon
2. A Multilevel Approach to AI Governance for Trust-Enhancing Practices
3. International and National Governance
4. Corporate Self-Governance
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
Acknowledgments
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
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
- Literature Review
Methods
Results
References - Regulating AI manipulation: Applying Insights from behavioral economics and psychology to enhance the practicality of the EU AI Act / 2308.02041 / ISBN:https://doi.org/10.48550/arXiv.2308.02041 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Clarifying Terminologies of Article-5: Insights from Behavioral Economics and Psychology
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
What is Generative Artificial Intelligence?
Identifying Ethical Concerns and Risks
GREAT PLEA Ethical Principles for Generative AI in Healthcare
Conclusion
Acknowledgements
References - Ethical Considerations and Policy Implications for Large Language Models: Guiding Responsible Development and Deployment / 2308.02678 / ISBN:https://doi.org/10.48550/arXiv.2308.02678 / Published by ArXiv / on (web) Publishing site
- 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
- 2 Background
3 Policy scope
4 Centralized regulation in the US context
5 Crowdsourced safety mechanism
6 The dual governance framework
7 Limitations - Normative Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions / 2208.12616 / ISBN:https://doi.org/10.48550/arXiv.2208.12616 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
5 Gaps in operationalising ethical principles
References
A Methodology - Bad, mad, and cooked: Moral responsibility for civilian harms in human-AI military teams / 2211.06326 / ISBN:https://doi.org/10.48550/arXiv.2211.06326 / Published by ArXiv / on (web) Publishing site
- 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
3 Discussion
References - 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
- 1 Introduction
2 Large Language Models
3 Vulnerabilities, Attack, and Limitations
5 Falsification and Evaluation
6 Verification
7 Runtime Monitor
8 Regulations and Ethical Use
Reference - Getting pwn'd by AI: Penetration Testing with Large Language Models / 2308.00121 / ISBN:https://doi.org/10.48550/arXiv.2308.00121 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
References - Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust / 2308.09979 / ISBN:https://doi.org/10.48550/arXiv.2308.09979 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Results
3 Discussion
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
- 1 Introduction
4 Experiments
5 Conclusions
References - AIxArtist: A First-Person Tale of Interacting with Artificial Intelligence to Escape Creative Block / 2308.11424 / ISBN:https://doi.org/10.48550/arXiv.2308.11424 / Published by ArXiv / on (web) Publishing site
- Abstract
Reflections - Exploring the Power of Creative AI Tools and Game-Based Methodologies for Interactive Web-Based Programming / 2308.11649 / ISBN:https://doi.org/10.48550/arXiv.2308.11649 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Advancements in AI and Web-Based Programming
3 Emergence of Creative AI Tools and Game-Based Methodologies
4 Enhancing User Experience through Creative AI Tools
5 Engaging Web-Based Programming with Game-Based Approaches
6 Unveiling the Potential: Benefits of Interactive Web-Based Programming
8 Real-World Applications: Showcasing Innovative Implementations
9 Ethical Considerations in Integrating AI and Game Elements
10 Privacy Concerns in Interactive Web-Based Programming for Education
11 Bias Awareness: Navigating AI-Generated Content in Education
12 The Future Landscape: Creative AI Tools and Game-Based Methodologies in Education
13 Case Study Example: Learning Success with Creative AI and Game-Based Techniques
14 Conclusion & Discussion - Collect, Measure, Repeat: Reliability Factors for Responsible AI Data Collection / 2308.12885 / ISBN:https://doi.org/10.48550/arXiv.2308.12885 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work on Data Excellence
3 Reliability and Reproducibility Metrics for Responsible Data Collection
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
- Abstract
I. Introduction
II. Methods and training process of LLMs
IV. Applied and technology implications for LLMs
V. Market analysis of LLMs and cross-industry use cases
VI. Solution architecture for privacy-aware and trustworthy conversational AI
VII. Discussions
VIII. Conclusion
References
Appendix A industry-wide LLM usecases - The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward / 2308.14253 / ISBN:https://doi.org/10.48550/arXiv.2308.14253 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 The evolution of artificial intelligence: from theory to general capabilities
3 Emerging dual-use risks and vulnerabilities in AI systems
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
10 Supplemental & additional details
References - Artificial Intelligence in Career Counseling: A Test Case with ResumAI / 2308.14301 / ISBN:https://doi.org/10.48550/arXiv.2308.14301 / Published by ArXiv / on (web) Publishing site
- 2 Literature review
References - Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? / 2308.15399 / ISBN:https://doi.org/10.48550/arXiv.2308.15399 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
References - The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / ISBN:https://doi.org/10.48550/arXiv.2308.16538 / Published by ArXiv / on (web) Publishing site
- Table of contents and index
Executive summary
1 Introduction
2 Key AI technology in financial services
3 Benefits of AI use in the finance sector
4 Threaths & potential pitfalls
5 Challenges
6 Regulation of AI and regulating through AI
7 Recommendations
References - Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / ISBN:https://doi.org/10.48550/arXiv.2309.00064 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Black box and lack of transparency
3 Bias and fairness
4 Human-centric AI
5 Ethical concerns and value alignment
6 Way forward
7 Conclusion
References - The Impact of Artificial Intelligence on the Evolution of Digital Education: A Comparative Study of OpenAI Text Generation Tools including ChatGPT, Bing Chat, Bard, and Ernie / 2309.02029 / ISBN:https://doi.org/10.48550/arXiv.2309.02029 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
3. ChatGPT Training Process
4. Methods
5. Discussion
References - Pathway to Future Symbiotic Creativity / 2209.02388 / ISBN:https://doi.org/10.48550/arXiv.2209.02388 / Published by ArXiv / on (web) Publishing site
- Contents
Part 1 - 1 Generatives Systems: Mimicking Artifacts
Part 1 - 2 Appreciate Systems: Mimicking Styles
Part 2 Art Data and Human–Machine Interaction in Art Creation
Part 2 - 2 Motion Caputer Technologies and Motion Data
Part 2 - 3 Photogrammetry / Volumetric Capture
Part 2 - 4 Aesthetic Descriptor: Labelling Artefacts with Emotion
Part 3 - 2 Machine Artist Models
Part 3 - 3 Comparison with Generative Models
Part 3 - 4 Demonstration of the Proposed Framework
Part 4 NFTs and the Future Art Economy
Part 5 - 2 Algorithmics Bias in Art Generation
Part 5 - 3 Democratization of Art with new Technologies
References
Acknowledgment - FUTURE-AI: Guiding Principles and Consensus
Recommendations for Trustworthy Artificial Intelligence in
Medical Imaging / 2109.09658 / ISBN:https://doi.org/10.48550/arXiv.2109.09658 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Fairness - For Equitable AI in Medical Imaging
3. Universality - For Standardised AI in Medical Imaging
4. Traceability - For Transparent and Dynamic AI in Medical Imaging
5. Usability - For Effective and Beneficial AI in Medical Imaging
6. Robustness - For Reliable AI in Medical Imaging
7. Explainability - For Enhanced Understanding of AI in Medical Imaging
8. FUTURE-AI Quality Check
9. Discussion and Conclusion
References - The Cambridge Law Corpus: A Corpus for Legal AI Research / 2309.12269 / ISBN:https://doi.org/10.48550/arXiv.2309.12269 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 The Cambridge Law Corpus
4 Experiments
General References
E Topic Model Top Words
Cambridge Law Corpus: Datasheet - EALM: Introducing Multidimensional Ethical Alignment in
Conversational Information Retrieval / 2310.00970 / ISBN:https://doi.org/10.48550/arXiv.2310.00970 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
3 Dataset Construction
5 Experiments
Appendix
References - Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities / 2310.08565 / ISBN:https://doi.org/10.48550/arXiv.2310.08565 / Published by ArXiv / on (web) Publishing site
- I. Introduction and Motivation
II. AI-Robotics Systems Architecture
IV. Attack Surfaces
V. Ethical & Legal Concerns
VI. Human-Robot Interaction (HRI) Security Studies
VII. Future Research & Discussion
References - If our aim is to build morality into an artificial agent, how might we begin to go about doing so? / 2310.08295 / ISBN:https://doi.org/10.48550/arXiv.2310.08295 / Published by ArXiv / on (web) Publishing site
- 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
- 2 Background and Related Work
3 Method
4 Taxonomy of AI Privacy Risks
5 Discussion
6 Conclusion
References - ClausewitzGPT Framework: A New Frontier in Theoretical Large Language Model Enhanced Information Operations / 2310.07099 / ISBN:https://doi.org/10.48550/arXiv.2310.07099 / Published by ArXiv / on (web) Publishing site
- Introduction
Theoretical Impact of LLMs on Information Operations
ClausewitzGPT and Modern Strategy
Mathematical Foundations
Ethical and Strategic Considerations: AI Mediators in the Age of LLMs
Integrating Computational Social Science, Computational Ethics, Systems Engineering, and AI Ethics in LLMdriven Operations
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
- 1 Introduction
3 Analysis and Findings
4 Discussion
Acknowledgements
References
A Consent and Data Collection Processes
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 LLMS CAN DO FOR HEALTHCARE? FROM FUNDAMENTAL TASKS TO ADVANCED APPLICATIONS
III. FROM PLMS TO LLMS FOR HEALTHCARE
IV. TRAIN AND USE LLM FOR HEALTHCARE
V. EVALUATION METHOD
VI. IMPROVING FAIRNESS, ACCOUNTABILITY, TRANSPARENCY, AND ETHICS
VII. FUTURE WORK AND CONCLUSION
References - STREAM: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models / 2310.05563 / ISBN:https://doi.org/10.48550/arXiv.2310.05563 / Published by ArXiv / on (web) Publishing site
- 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
- 1 Introduction
2 Regulation: A Short Introduction
3 LLMs: Risk and Uncertainty
4 Scientific Expertise, Social Media and Regulatory Capture
5 Regulation and NLP (RegNLP): A New Field
References - Ethics of Artificial Intelligence and Robotics in the Architecture, Engineering, and Construction Industry / 2310.05414 / ISBN:https://doi.org/10.48550/arXiv.2310.05414 / Published by ArXiv / on (web) Publishing site
- Abstract
2. Research Methodology
3. Ethics of AI and Robotics
4. Systematic Review and Scientometric Analysis
5. Ethical Issues of AI and Robotics in AEC Industry
6. Discussion
7. Future Research Direction
References - Commercialized Generative AI: A Critical Study of the Feasibility and Ethics of Generating Native Advertising Using Large Language Models in Conversational Web Search / 2310.04892 / ISBN:https://doi.org/10.48550/arXiv.2310.04892 / Published by ArXiv / on (web) Publishing site
- Evaluation of the Pilot Study
- Compromise in Multilateral Negotiations and the Global Regulation of Artificial Intelligence / 2309.17158 / ISBN:https://doi.org/10.48550/arXiv.2309.17158 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. The practice of multilateral negotiation and the mechanisms of compromises
3. The liberal-sovereigntist multiplicity
4. Towards a compromise: drafting the normative hybridity
5. Text negotiations as normative testing
Notes
Bibliography - 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
- Introduction
Principal Ethics in Healthcare
Results and Discussion
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
- 2. Autonomous vehicles
4. Traffic Flow prediction in Autonomous vehicles
5. Cybersecurity Risks
6. Risk management
7. Issues
8. Conclusion
9. References - The Return on Investment in AI Ethics: A Holistic Framework / 2309.13057 / ISBN:https://doi.org/10.48550/arXiv.2309.13057 / Published by ArXiv / on (web) Publishing site
- 2. AI Ethics
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
- Abstract
Trust in AI
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
- 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
2 Harms of Influencer Marketing
3 Ethical Data Collection, Responsible AI Development, and the Path Forward
4 Conclusion
References - AI & Blockchain as sustainable teaching and learning tools to cope with the 4IR / 2305.01088 / ISBN:https://doi.org/10.48550/arXiv.2305.01088 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. AI and blockchain in education: An overview of the benefits and challenges
4. Blockchain-based credentialing and certification
6. Blockchain-based decentralized learning networks
7. AI-powered content creation and curation
10.Conclusion - Toward an Ethics of AI Belief / 2304.14577 / ISBN:https://doi.org/10.48550/arXiv.2304.14577 / Published by ArXiv / on (web) Publishing site
- 2. “Belief” in Humans and AI
References - Ensuring Trustworthy Medical Artificial Intelligence through Ethical and Philosophical Principles / 2304.11530 / ISBN:https://doi.org/10.48550/arXiv.2304.11530 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Ethical concerns of AI in medicine
Ethical datasets and algorithm development guidelines
Towards solving key ethical challenges in Medical AI
Ethical guidelines for medical AI model deployment
Discussion
Conclusion and future directions
References - Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineering / 2209.04963 / ISBN:https://doi.org/10.48550/arXiv.2209.04963 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Methodology
3 Governance Patterns
4 Process Patterns
5 Product Patterns
6 Related Work
References - The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site
- Bibliography
Appendix A: Integrated Inventory of Ethical Concerns, Value Chains Actors, Resourcing Activities, & Sampled Sources - FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare / 2309.12325 / ISBN:https://doi.org/10.48550/arXiv.2309.12325 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Materials and Methods
3 FUTURE-AI Guideline
4 Discussion
References
Appendix A Tables
Appendix B Full Author Affiliations - Language Agents for Detecting Implicit Stereotypes in Text-to-Image Models at Scale / 2310.11778 / ISBN:https://doi.org/10.48550/arXiv.2310.11778 / Published by ArXiv / on (web) Publishing site
- 2 Agent Design
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
- 1 Introduction
2 AI feedback on specific problematic AI traits
5 Related Work
6 Discussion
References
F Scaling Trends for GfH PMs
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
- Abstract
2 Related Work
3 Method
4 Findings
5 Discussion
7 Limitation and Future Research
References
Annexed tables - Systematic AI Approach for AGI:
Addressing Alignment, Energy, and AGI Grand Challenges / 2310.15274 / ISBN:https://doi.org/10.48550/arXiv.2310.15274 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Trifecta of AI Challenges
4 Systematic AI for Energy Wall
5 System Design for AI Alignment
6 System Insights from the Brain
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
2 Reinforcement Learning with Multiple Reinforcers
3 Arrow-Sen Impossibility Theorems for RLHF
4 Implications for AI Governance and Policy
5 Conclusion - A Comprehensive Review of
AI-enabled Unmanned Aerial Vehicle:
Trends, Vision , and Challenges / 2310.16360 / ISBN:https://doi.org/10.48550/arXiv.2310.16360 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
IV. Artificial Intelligence Embedded UAV
VI. Review Summary
VII. Conclusion
References - Unpacking the Ethical Value Alignment in Big Models / 2310.17551 / ISBN:https://doi.org/10.48550/arXiv.2310.17551 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Risks and Ethical Issues of Big Model
3 Investigating the Ethical Values of Large Language Models
4 Equilibrium Alignment: A Prospective Paradigm for Ethical Value Alignmen
References - Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
- 2 Causal Models
3 The BvH and HK Definitions
4 The Causal Condition
6 Degree of Responsibility
References - AI for Open Science: A Multi-Agent Perspective for
Ethically Translating Data to Knowledge / 2310.18852 / ISBN:https://doi.org/10.48550/arXiv.2310.18852 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background and Related Work
3 A Formal Language of AI for Open Science
4 Optimizing an Openness Metric in AI for Science
5 Why Openness in AI for Science
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
Focus Group Protocol and Recruitment
AI tool-specific educational concerns
Conclusion
References - Human Participants in AI Research: Ethics and Transparency in Practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Contextual Concerns: Why AI Research Needs its Own Guidelines
3 Ethical Principles for AI Research with Human Participants
4 Principles in Practice: Guidelines for AI Research with Human Participants
References
A Evaluating Current Practices for Human-Participants Research
B Placing Research Ethics for Human Participants in Historical Context - LLMs grasp morality in concept / 2311.02294 / ISBN:https://doi.org/10.48550/arXiv.2311.02294 / Published by ArXiv / on (web) Publishing site
- 2 A General Theory of Meaning
4 The Moral Model
A Supplementary Material
References - Educating for AI Cybersecurity Work and Research: Ethics, Systems Thinking, and
Communication Requirements / 2311.04326 / ISBN:https://doi.org/10.48550/arXiv.2311.04326 / Published by ArXiv / on (web) Publishing site
- Literature Review
Research questions
References - Towards Effective Paraphrasing for Information
Disguise / 2311.05018 / ISBN:https://doi.org/10.1007/978-3-031-28238-6_22 / Published by ArXiv / on (web) Publishing site
- 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
- 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
- Abstract
1 Introduction
2 Overview of ChatGPT and its capabilities
3 Transformers and pre-trained language models
4 Applications of ChatGPT in real-world scenarios
5 Advantages of ChatGPT in natural language processing
7 Ethical considerations when using ChatGPT
10 Future directions for ChatGPT in vision domain
11 Conclusion
References - Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies / 2304.07683 / ISBN:https://doi.org/10.48550/arXiv.2304.07683 / Published by ArXiv / on (web) Publishing site
- Abstract
III. Impacts of bias in AI
IV. Mitigation strategies for bias in AI
V. Fairness in AI
VI. Mitigation strategies for fairness in AI
VII. Conclusions
References - Towards ethical multimodal systems / 2304.13765 / ISBN:https://doi.org/10.48550/arXiv.2304.13765 / Published by ArXiv / on (web) Publishing site
- 3 Crafting an Ethical Dataset
References - A Brief History of Prompt: Leveraging Language Models. (Through Advanced Prompting) / 2310.04438 / ISBN:https://doi.org/10.48550/arXiv.2310.04438 / Published by ArXiv / on (web) Publishing site
- Abstract
II. Introduction
III. Prehistoric prompting: pre NN-era
IV. History of NLP between 2010 and 2015: the pre-attention mechanism era
VI. 2015: birth of the transformer
VII. The second wave in 2017: rise of RL
VIII. The third wave 2018: the rise of transformers
IX. 2019: THE YEAR OF CONTROL
X. 2020-2021: the rise of LLMS
XI. 2022-current: beyond language generation
XII. Conclusions
References - Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agents / 2310.15065 / ISBN:https://doi.org/10.48550/arXiv.2310.15065 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related work
3 Method
4 Findings
5 Discussion
References - She had Cobalt Blue Eyes: Prompt Testing to Create Aligned and Sustainable Language Models / 2310.18333 / ISBN:https://doi.org/10.48550/arXiv.2310.18333 / Published by ArXiv / on (web) Publishing site
- 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
- III. Safety
IV. Trust
V. Ethics
VI. Conclusion
References - How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
3 Methodology
Limitations
Ethical Considerations
References - Prudent Silence or Foolish Babble? Examining Large Language Models' Responses to the Unknown / 2311.09731 / ISBN:https://doi.org/10.48550/arXiv.2311.09731 / Published by ArXiv / on (web) Publishing site
- 4 Related Work
References - Revolutionizing Customer Interactions: Insights and Challenges in Deploying ChatGPT and Generative Chatbots for FAQs / 2311.09976 / ISBN:https://doi.org/10.48550/arXiv.2311.09976 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Chatbots Background and Scope of Research
3. Chatbot approaches overview: Taxonomy of existing methods
4. ChatGPT
5. Applications
7. Future Research Directions
References - Practical Cybersecurity Ethics: Mapping CyBOK to Ethical Concerns / 2311.10165 / ISBN:https://doi.org/10.48550/arXiv.2311.10165 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background
3 Methodology
4 Findings
5 Discussion
7 Conclusion
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
Harms, Risk, and Liability Practices
Appendix A - What is an Algorithmic Harm? And a Bibliography
Appendix B – Common AI Harms as Described by EPIC10
Appendix C - List of General Harms Created by Digital Products Provided by Claude.AI - 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
- 2 Proposed Process
3 Related Work and Discussion
References - Responsible AI Considerations in Text Summarization Research: A Review of Current Practices / 2311.11103 / ISBN:https://doi.org/10.48550/arXiv.2311.11103 / Published by ArXiv / on (web) Publishing site
- 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
- 4 Findings
Acknowledgments and Disclosure of Funding
References
A Overview of AIIA Instruments
B Study Materials - GPT in Data Science: A Practical Exploration of Model Selection / 2311.11516 / ISBN:https://doi.org/10.48550/arXiv.2311.11516 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Background
III. Approach: capturing and representing heuristics behind GPT's decision-making process
IV. Comparative results
V. Conclusion and future work
VI. Future work - Responsible AI Research Needs Impact Statements Too / 2311.11776 / ISBN:https://doi.org/10.48550/arXiv.2311.11776 / Published by ArXiv / on (web) Publishing site
- Requiring adverse impact statements for RAI research is long overdue
What do RAI venues do?
Suggestions for More Meaningful Engagement with the Impact of RAI Research
References - Large Language Models in Education: Vision and Opportunities / 2311.13160 / ISBN:https://doi.org/10.48550/arXiv.2311.13160 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Education and LLMS
III. Key technologies for EDULLMS
IV. LLM-empowered education
VI. Challenges and future directions
References - The Rise of Creative Machines: Exploring the Impact of Generative AI / 2311.13262 / ISBN:https://doi.org/10.48550/arXiv.2311.13262 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Extent and impact of generative AI
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
- 1 Introduction
2 Related Works
3 Methodology
References
6 Appendix - Ethical implications of ChatGPT in higher education: A scoping review / 2311.14378 / ISBN:https://doi.org/10.48550/arXiv.2311.14378 / Published by ArXiv / on (web) Publishing site
- Introduction
Findings
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
- Findings
Discussion - RAISE -- Radiology AI Safety, an End-to-end lifecycle approach / 2311.14570 / ISBN:https://doi.org/10.48550/arXiv.2311.14570 / Published by ArXiv / on (web) Publishing site
- Abstract
2. Pre-Deployment phase
3. Production deployment monitoring phase
5. Conclusion
Funding/Disclosures
Bibliography - Ethics and Responsible AI Deployment / 2311.14705 / ISBN:https://doi.org/10.48550/arXiv.2311.14705 / Published by ArXiv / on (web) Publishing site
- 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.
10. Conclusion
11. References - From deepfake to deep useful: risks and opportunities through a systematic literature review / 2311.15809 / ISBN:https://doi.org/10.48550/arXiv.2311.15809 / Published by ArXiv / on (web) Publishing site
- 5. Conclusion
- 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
VI. Conclusion
References - Survey on AI Ethics: A Socio-technical Perspective / 2311.17228 / ISBN:https://doi.org/10.48550/arXiv.2311.17228 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 Transparency and explainability
4 Fairness and equity
5 Responsiblity, accountability, and regulations
6 Environmental impact
7 Conclusion
References - Deepfakes, Misinformation, and Disinformation in the Era of Frontier AI, Generative AI, and Large AI Models / 2311.17394 / ISBN:https://doi.org/10.48550/arXiv.2311.17394 / Published by ArXiv / on (web) Publishing site
- II. Background
III. The rise of large AI models
V. Technical defense mechanisms
VI. Cross-platform strategies
VII. Ethical considerations
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
- 2 Legal Basis of Privacy and Copyright Concerns over Generative AI
3 Mapping Challenges throughout the Data Lifecycle
References - Integrating AI into CCTV Systems: A Comprehensive Evaluation of Smart Video Surveillance in Community Space / 2312.02078 / ISBN:https://doi.org/10.48550/arXiv.2312.02078 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Related works
III. System features
V. Real-world results and evaluation
VI. Physical-cyber-physical evaluation (anomaly detection)
References
Biography - Understanding Teacher Perspectives and Experiences after Deployment of AI Literacy Curriculum in Middle-school Classrooms / 2312.04839 / ISBN:https://doi.org/10.48550/arXiv.2312.04839 / Published by ArXiv / on (web) Publishing site
- 2 Methodology
3 Results - Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines / 2312.05235 / ISBN:https://doi.org/10.48550/arXiv.2312.05235 / Published by ArXiv / on (web) Publishing site
- 5. Results
- 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
- 3. Detectors are not useful
4. Teach critical usage of AI
References - Intelligence Primer / 2008.07324 / ISBN:https://doi.org/10.48550/arXiv.2008.07324 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Human intelligence
5 System design of intelligence
7 Mathematically modeling intelligence
9 Augmenting human intelligence
10 Exceeding human intelligence
11 Control of intelligence
12 Large language models and Generative AI
14 Wrong numbers
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
- 1 Introduction
2 Related work
3 Methodology
4 Results & analysis
References - Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site
- Abstract
III. Ethics: a primer
IV. Guidelines for promoting ethical responsibility
V. Implications whit future directions
References - Control Risk for Potential Misuse of Artificial Intelligence in Science / 2312.06632 / ISBN:https://doi.org/10.48550/arXiv.2312.06632 / Published by ArXiv / on (web) Publishing site
- 2 Risks of Misuse for Artificial Intelligence in
Science
4 Call for Responsible AI for Science
6 Related Works
References
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
- References
- Navigating the generative AI era: Introducing the AI assessment scale for ethical GenAI assessment / 2312.07086 / ISBN:https://doi.org/10.48550/arXiv.2312.07086 / Published by ArXiv / on (web) Publishing site
- Abstract
Problematizing The View Of GenAI Content As Academic Misconduct
The AI Assessment Scale
Conclusion
References - Culturally Responsive Artificial Intelligence -- Problems, Challenges and Solutions / 2312.08467 / ISBN:https://doi.org/10.48550/arXiv.2312.08467 / Published by ArXiv / on (web) Publishing site
- The concept of multiculturalism and its importance
Culturally responsive AI – current landscape
Recommendations
References - Investigating Responsible AI for Scientific Research: An Empirical Study / 2312.09561 / ISBN:https://doi.org/10.48550/arXiv.2312.09561 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Background and motivation
III. Research methodology
IV. Results
V. Discussion
References
Appendix 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
- 1 Objective
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
- 2 The Reign of Algorithmic Fairness
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
4. Experiments on Human Data using Language Models
References
A. Appendix - The Economics of Human Oversight: How Norms and Incentives Affect Costs and Performance of AI Workers / 2312.14565 / ISBN:https://doi.org/10.48550/arXiv.2312.14565 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Theoretical background and hypotheses
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
Methods - Autonomous Threat Hunting: A Future Paradigm for AI-Driven Threat Intelligence / 2401.00286 / ISBN:https://doi.org/10.48550/arXiv.2401.00286 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Foundations of AI-driven threat intelligence
5. Challenges in autonomous threat hunting
6. Case studies and applications
7. Evaluation metrics and performance benchmarks
8. Future directions and emerging trends
9. Conclusion
References - Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. LLMs in cognitive and behavioral psychology
3. LLMs in clinical and counseling psychology
4. LLMs in educational and developmental psychology
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
- 2. The generation of synthetic data
4. Risks and Challenges in Utilizing Synthetic Datasets for AI
5. Conclusions
References - MULTI-CASE: A Transformer-based Ethics-aware Multimodal Investigative Intelligence Framework / 2401.01955 / ISBN:https://doi.org/10.48550/arXiv.2401.01955 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Related work
III. Methodology: model development
IV. System design
V. Evaluation
VI. Discussion and future work
VII. Conclusion
References - AI Ethics Principles in Practice: Perspectives of Designers and Developers / 2112.07467 / ISBN:https://doi.org/10.48550/arXiv.2112.07467 / Published by ArXiv / on (web) Publishing site
- Abstract
II. Related work
III. Methods
IV. Results
V. Discussion and suggestions
VI. Support mechanisms
VII. Conclusion
References - Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models / 2310.19917 / ISBN:https://doi.org/10.48550/arXiv.2310.19917 / Published by ArXiv / on (web) Publishing site
- Abstract
Results
Discussion
PRISMA 2020 flow diagram and bias handling workflow
References - Resolving Ethics Trade-offs in Implementing Responsible AI / 2401.08103 / ISBN:https://doi.org/10.48550/arXiv.2401.08103 / Published by ArXiv / on (web) Publishing site
- 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
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
8 Fairview: an evaluative AI support for addressing fairness
IV Conclusions
Bibliography - Business and ethical concerns in domestic Conversational Generative AI-empowered multi-robot systems / 2401.09473 / ISBN:https://doi.org/10.48550/arXiv.2401.09473 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background
3 Method
5 Discussion
6 Conclusion
References - FAIR Enough How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training? / 2401.11033 / ISBN:https://doi.org/10.48550/arXiv.2401.11033 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 FAIR Data Principles: Theoretical Background and Significance
3 Data Management Challenges in Large Language Models
4 Framework for FAIR Data Principles Integration in LLM Development
References
Appendices - Enabling Global Image Data Sharing in the Life Sciences / 2401.13023 / ISBN:https://doi.org/10.48550/arXiv.2401.13023 / Published by ArXiv / on (web) Publishing site
- 1. Motivation for White Paper
2. Background
3. Use cases representing different image data types and their challenges and status for sharing
4. Towards global image data sharing
Towards Global Image Data Sharing: A to-do list for various stakeholders
International Working Group Members who contributed to the discussion and writing of the white paper (in alphabetical order) - Five ethical principles for generative AI in scientific research / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Principle 1: Understand model training and output
Principle 2: Respect privacy, confidentiality, and copyright
Principle 4: Apply AI beneficially
Principle 5: Use AI transparently and reproducibly
Concluding remarks
References - A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations / 2401.17486 / ISBN:https://doi.org/10.48550/arXiv.2401.17486 / Published by ArXiv / on (web) Publishing site
- 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
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
- 2 Generation
3 Detection
5 Discussion
References
Authors' bios - Responsible developments and networking research: a reflection beyond a paper ethical statement / 2402.00442 / ISBN:https://doi.org/10.48550/arXiv.2402.00442 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Networking research today
4 Sense of engagement and responsibility
6 Concluding remarks - 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
4. Findings
References - Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube / 2402.01760 / ISBN:https://doi.org/10.48550/arXiv.2402.01760 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Literature review
3. Methodology
4. Discussion
References - 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
- 4 Recommendations to address threats posed by crossover AI technology
References - (A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice / 2402.01864 / ISBN:https://doi.org/10.48550/arXiv.2402.01864 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related work and our approach
3 Methods: case-based expert deliberation
4 Results
5 Discussion
6 Conclusion
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
- Abstract
1 Introduction
2 Background - A Framework for Assessing Proportionate Intervention with Face Recognition Systems in Real-Life Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
- 2. Background
3. Intervention models from other fields
References - Ethics in AI through the Practitioner's View: A Grounded Theory Literature Review / 2206.09514 / ISBN:https://doi.org/10.48550/arXiv.2206.09514 / Published by ArXiv / on (web) Publishing site
- 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
- Abstract
Methods
Results
Discussion
Reference
Appendix - How do machines learn? Evaluating the AIcon2abs method / 2401.07386 / ISBN:https://doi.org/10.48550/arXiv.2401.07386 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
4. Results
References - I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench / 2401.17882 / ISBN:https://doi.org/10.48550/arXiv.2401.17882 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
Ethical Statement
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
- 1 Introduction
3 Results
6 Conclusion
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
- 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
3 Paradigm Shifts and New Trends
4 Current Taxonomy
5 Discussion and Future Research Directions
References - Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence / 2402.09880 / ISBN:https://doi.org/10.48550/arXiv.2402.09880 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Background and Related Work
IV. Technological Aspects
VII. Discussions
References - Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications / 2402.12216 / ISBN:https://doi.org/10.48550/arXiv.2402.12216 / Published by ArXiv / on (web) Publishing site
- 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
- References
- What if LLMs Have Different World Views: Simulating Alien Civilizations with LLM-based Agents / 2402.13184 / ISBN:https://doi.org/10.48550/arXiv.2402.13184 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 CosmoAgent Simulation Setting
4 CosmoAgent Architecture
5 Evaluation
6 Experimental Design
7 Results
8 Conclusion
A CosmoAgent Prompt
B Secretary Agent 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
Results
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
- Abstract
1 The increasing importance of AI
2 The EU AI Act
3 There is no reliable AI regulation without a sound theory of human-AI interaction
4 There is no trustworthy AI without HCI
5 There is no community without common language and communication
6 Conclusion: Navigating the future of AI and HCI within the EU AI Act framework
References - Multi-stakeholder Perspective on Responsible Artificial Intelligence and Acceptability in Education / 2402.15027 / ISBN:https://doi.org/10.48550/arXiv.2402.15027 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background
3 Materials and Methods
4 Analysis
6 Discussion
References
Appendix 1 Scenarios - Autonomous Vehicles: Evolution of Artificial Intelligence and Learning Algorithms / 2402.17690 / ISBN:https://doi.org/10.48550/arXiv.2402.17690 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
III. Ethical Considerations and Bias in AI-Driven Software Development for Autonomous Vehicles
IV. AI’S Role in the Emerging Trend of Internet of Things (IOT) Ecosystem for Autonomous Vehicles
V. Review of Existing Research and Use Cases
VI. AI and Learning Algorithms Statistics for Autonomous Vehicles
VII. Conclusion
References
Authors - Envisioning the Applications and Implications of Generative AI for News Media / 2402.18835 / ISBN:https://doi.org/10.48550/arXiv.2402.18835 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 The Suitability of Generative AI for Newsroom Tasks
References - FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics / 2402.19071 / ISBN:https://doi.org/10.48550/arXiv.2402.19071 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Background
3. Methods
4. Results
5. Discussion
6. Conclusion
References - Guidelines for Integrating Value Sensitive Design in Responsible AI Toolkits / 2403.00145 / ISBN:https://doi.org/10.48550/arXiv.2403.00145 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background and Related Work
3 Methodology
5 Discussion
References - Implications of Regulations on the Use of AI and Generative AI for Human-Centered Responsible Artificial Intelligence / 2403.00148 / ISBN:https://doi.org/10.48550/arXiv.2403.00148 / Published by ArXiv / on (web) Publishing site
- 1 Motivation & Background
References - Updating the Minimum Information about CLinical Artificial Intelligence (MI-CLAIM) checklist for generative modeling research / 2403.02558 / ISBN:https://doi.org/10.48550/arXiv.2403.02558 / Published by ArXiv / on (web) Publishing site
- Abstract
Part 1C. Bias, privacy, and harm assessments
Part 4B. Human model evaluation
Part 6. End-to-end pipeline replication
Conclusions
Table 1. Updated MI-CLAIM checklist for generative AI clinical studies.
References - Towards an AI-Enhanced Cyber Threat Intelligence Processing Pipeline / 2403.03265 / ISBN:https://doi.org/10.48550/arXiv.2403.03265 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction & Motivation
II. Background & Literature Review
III. The AI-Enhanced CTI Processing Pipeline
IV. Challenges and Considerations
V. Conclusions & Future Research
References - A Survey on Human-AI Teaming with Large Pre-Trained Models / 2403.04931 / ISBN:https://doi.org/10.48550/arXiv.2403.04931 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 AI Model Improvements with Human-AI Teaming
3 Effective Human-AI Joint Systems
4 Safe, Secure and Trustworthy AI
5 Applications
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
- D More Results
- Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site
- References
- AGI Artificial General Intelligence for Education / 2304.12479 / ISBN:https://doi.org/10.48550/arXiv.2304.12479 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. What is AGI
3. The Potentials of AGI in Transforming Future Education
4. Ethical Issues and Concerns
5. Discussion
6. Conclusion
References - Moral Judgments in Narratives on Reddit Investigating Moral Sparks via Social Commonsense and Linguistic Signals / 2310.19268 / ISBN:https://doi.org/10.48550/arXiv.2310.19268 / Published by ArXiv / on (web) Publishing site
- 3. Data
4. Methods
5. Results
References - Responsible Artificial Intelligence: A Structured Literature Review / 2403.06910 / ISBN:https://doi.org/10.48550/arXiv.2403.06910 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
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
- Abstract
I. Introduction
II. Related Work
III. Problem Statement
IV. Informational Fairness
V. Representational Fairness
VI. Ethics and Morality
VIII. Conclusion
References
Appendix - Towards a Privacy and Security-Aware Framework for Ethical AI: Guiding the Development and Assessment of AI Systems / 2403.08624 / ISBN:https://doi.org/10.48550/arXiv.2403.08624 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Theoretical Background
3 Research Methodology
4 Results of the Systematic Literature Review
5 Towards Privacy- and Security-Aware Framework for Ethical AI
7 Conclusion
References - Review of Generative AI Methods in Cybersecurity / 2403.08701 / ISBN:https://doi.org/10.48550/arXiv.2403.08701 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Cyber Defence
5 Implications of Generative AI in Social, Legal, and Ethical Domains
6 Discussion - 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
- 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
- Abstract
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
Conclusion
Web Appendix A: Analysis of the Disinformation Manipulations - The Journey to Trustworthy AI- Part 1 Pursuit of Pragmatic Frameworks / 2403.15457 / ISBN:https://doi.org/10.48550/arXiv.2403.15457 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Context
2 Trustworthy AI Too Many Definitions or Lack Thereof?
3 Complexities and Challenges
4 AI Regulation: Current Global Landscape
5 Risk
6 Bias and Fairness
8 Implementation Framework
10 Summary and Next Steps
11 About the Authors
A Appendix
References - Analyzing Potential Solutions Involving Regulation to Escape Some of AI's Ethical Concerns / 2403.15507 / ISBN:https://doi.org/10.48550/arXiv.2403.15507 / Published by ArXiv / on (web) Publishing site
- Abstract
A Possible Solution to These Concerns With Government Regulation - 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
4 Practical cases of unfairness in real-world setting
5 Ways to mitigate bias and promote Fairness
6 How Users can be affected by unfair ML Systems
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
References - Power and Play Investigating License to Critique in Teams AI Ethics Discussions / 2403.19049 / ISBN:https://doi.org/10.48550/arXiv.2403.19049 / Published by ArXiv / on (web) Publishing site
- 1 Introduction and Related Work
2 Methods
4 RQ2: How Do AI Ethics Discussions Unfold while Playing a Game Oriented toward Speculative Critique?
5 Discussion
References - Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness / 2403.20089 / ISBN:https://doi.org/10.48550/arXiv.2403.20089 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 Implications of the AI Act
4 Practical challenges for compliance
References - AI Act and Large Language Models (LLMs): When critical issues and privacy impact require human and ethical oversight / 2404.00600 / ISBN:https://doi.org/10.48550/arXiv.2404.00600 / Published by ArXiv / on (web) Publishing site
- 6. Large Language Models (LLMs) - Introduction
7. Artificial intelligence Liability
8. Conclusions
9. References - Exploring the Nexus of Large Language Models and Legal Systems: A Short Survey / 2404.00990 / ISBN:https://doi.org/10.48550/arXiv.2404.00990 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Applications of Large Language Models in Legal Tasks
4 Legal Problems of Large Languge Models
6 Conclusion and Future Directions
References - A Review of Multi-Modal Large Language and Vision Models / 2404.01322 / ISBN:https://doi.org/10.48550/arXiv.2404.01322 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 What is a Language Model?
3 Proprietary vs. Open Source LLMs
4 Specific Large Language Models
5 Vision Models and Multi-Modal Large Language Models
6 Model Tuning
8 Conclusions
References - Balancing Progress and Responsibility: A Synthesis of Sustainability Trade-Offs of AI-Based Systems / 2404.03995 / ISBN:https://doi.org/10.48550/arXiv.2404.03995 / Published by ArXiv / on (web) Publishing site
- Abstract
II. Background and Related Work
III. Study Design
IV. Results
V. Discussion
VI. Threats to Validity
References - Designing for Human-Agent Alignment: Understanding what humans want from their agents / 2404.04289 / ISBN:https://doi.org/10.1145/3613905.3650948 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Method
4 Findings
5 Discussion
7 Conclusion
References - Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage / 2404.06077 / ISBN:https://doi.org/10.48550/arXiv.2404.06077 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Preliminaries
III. Proposed Design: IBIS
IV. Detailed Construction
V. Implementation on DAML
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
- A Primer
Polarised Responses
Rebooting Machine Ethics
Generative Agents in Society
References - Safeguarding Marketing Research: The Generation, Identification, and Mitigation of AI-Fabricated Disinformation / 2403.14706 / ISBN:https://doi.org/10.48550/arXiv.2403.14706 / Published by ArXiv / on (web) Publishing site
- Bibliography
- The Pursuit of Fairness in Artificial Intelligence Models A Survey / 2403.17333 / ISBN:https://doi.org/10.48550/arXiv.2403.17333 / Published by ArXiv / on (web) Publishing site
- A Appendices