Why_this_webapp Bibliography

The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site

Appendix

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

2 Related Work
4 Results

A Framework for Ethical AI at the United Nations / 2104.12547 / ISBN:https://doi.org/10.48550/arXiv.2104.12547 / Published by ArXiv / on (web) Publishing site

1. Problems with AI

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

4 Results

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

4 Deployment and Evaluation

The Ethics of AI Value Chains / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site

4. Ethical Implications of AI Value Chains

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

4 Centralized regulation in the US context

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

5 Methods

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

5 Ethical concerns and value alignment
References

Pathway to Future Symbiotic Creativity / 2209.02388 / ISBN:https://doi.org/10.48550/arXiv.2209.02388 / Published by ArXiv / on (web) Publishing site

Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging / 2109.09658 / ISBN:https://doi.org/10.48550/arXiv.2109.09658 / Published by ArXiv / on (web) Publishing site

1. Introduction
2. Fairness - For Equitable AI in Medical Imaging
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

4 Experiments

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

Appendix

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

3. AI Ethical Principles

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
6 Discussion

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

4 Towards solving key ethical challenges in Medical AI
5 Ethical guidelines for medical AI model deployment

Human participants in AI research: Ethics and transparency in practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site

II. Contextual Concerns: Why AI Research Needs its Own Guidelines

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

IV. Comparative results

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

4. Addressing bias, transparency, and accountability

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

Appendix B Details of Risks Demonstration in Chemical Science

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

IV. Results

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

B Extended Guiding Principles

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
References

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

Results
Discussion

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

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
Bibliography

Beyond principlism: Practical strategies for ethical AI use in research practices / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site

3 Five specific goals and action-guiding strategies for ethical AI use in research practices

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

5 Findings

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

Discussion
Reference

Mapping the Ethics of Generative AI: A Comprehensive Scoping Review / 2402.08323 / ISBN:https://doi.org/10.48550/arXiv.2402.08323 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction

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

4 Current Taxonomy

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

3 Model of Civilization Evolution

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

METRIC-framework for medical training data
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

V. Review of Existing Research and Use Cases

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 4. Model evaluation
Part 5. Interpretability of generative models

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

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

3. Findings

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

5 Ways to mitigate bias and promote Fairness

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

4 Practical challenges for compliance
A Appendix

Not a Swiss Army Knife: Academics' Perceptions of Trade-Offs Around Generative Artificial Intelligence Use / 2405.00995 / ISBN:https://doi.org/10.48550/arXiv.2405.00995 / Published by ArXiv / on (web) Publishing site

Abstract

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

6 Ethics

Responsible AI: Portraits with Intelligent Bibliometrics / 2405.02846 / ISBN:https://doi.org/10.48550/arXiv.2405.02846 / Published by ArXiv / on (web) Publishing site

II. Conceptualization: Responsible AI

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

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

References

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

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

VII. Challenges and Future Research Directions

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

4 Discussion
Appendix

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

2 RQ1: What Happens When AI Eats Itself ?

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

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

IV. Network Security

Towards Clinical AI Fairness: Filling Gaps in the Puzzle / 2405.17921 / ISBN:https://doi.org/10.48550/arXiv.2405.17921 / Published by ArXiv / on (web) Publishing site

Methods in clinical AI fairness research
Discussion
Reference

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

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
3. Discussion

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

5 Maintaining Scientific Excellence, Open Data, and Guiding AI Usage Based on Ethical Principles in EO

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

6 Risk analysis via BRIO for the German Credit Dataset

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

2. A Case Study on DAIC-WoZ Depression Research

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

3 Potential Misuse and Security Concerns

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

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

4 RESULTS

Staying vigilant in the Age of AI: From content generation to content authentication / 2407.00922 / ISBN:https://doi.org/10.48550/arXiv.2407.00922 / Published by ArXiv / on (web) Publishing site

Introduction
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

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

IV. Proposing an Alternative 3C Framework

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

4 Generative AI and Humans: Risks and Mitigation

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

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

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

Related Work
Discussion

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

3 Challenges

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

6 Discussions of Current Studies

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

4 Biases
6 Open Challenges

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

2 Fairness Debt

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

6 Results

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

Why business adoption of quantum and AI technology must be ethical / 2312.10081 / ISBN:https://doi.org/10.48550/arXiv.2312.10081 / Published by ArXiv / on (web) Publishing site

Argument for acknowledging complexity: the case for individual ethos, regulation is not enough

Views on AI aren't binary -- they're plural / 2312.14230 / ISBN:https://doi.org/10.48550/arXiv.2312.14230 / Published by ArXiv / on (web) Publishing site

The false binary: Ethics (the stereotype
The false binary: Ethics’s discontents with Alignment

Data-Centric Foundation Models in Computational Healthcare: A Survey / 2401.02458 / ISBN:https://doi.org/10.48550/arXiv.2401.02458 / Published by ArXiv / on (web) Publishing site

10 Conclusions
References

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

2 Previous studies

Data Defenses Against Large Language Models / 2410.13138 / ISBN:https://doi.org/10.48550/arXiv.2410.13138 / Published by ArXiv / on (web) Publishing site

2 Ethics of Resisting LLM Inference

A Simulation System Towards Solving Societal-Scale Manipulation / 2410.13915 / ISBN:https://doi.org/10.48550/arXiv.2410.13915 / Published by ArXiv / on (web) Publishing site

6 Social Impact Statement

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

Ethical Challenges Presented by AI

Standardization Trends on Safety and Trustworthiness Technology for Advanced AI / 2410.22151 / ISBN:https://doi.org/10.48550/arXiv.2410.22151 / Published by ArXiv / on (web) Publishing site

3 Trends in advanced AI safety and trustworthiness standardization

Democratizing Reward Design for Personal and Representative Value-Alignment / 2410.22203 / ISBN:https://doi.org/10.48550/arXiv.2410.22203 / Published by ArXiv / on (web) Publishing site

4 Study Design & Methodology

Examining Human-AI Collaboration for Co-Writing Constructive Comments Online / 2411.03295 / ISBN:https://doi.org/10.48550/arXiv.2411.03295 / Published by ArXiv / on (web) Publishing site

4 Findings

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

Appendices

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

4. Bias Evaluation

GPT versus Humans: Uncovering Ethical Concerns in Conversational Generative AI-empowered Multi-Robot Systems / 2411.14009 / ISBN:https://doi.org/10.48550/arXiv.2411.14009 / Published by ArXiv / on (web) Publishing site

4 Results

Privacy-Preserving Video Anomaly Detection: A Survey / 2411.14565 / ISBN:https://doi.org/10.48550/arXiv.2411.14565 / Published by ArXiv / on (web) Publishing site

I. Introduction
VI. Evaluation Benchmarks and Metrics

Political-LLM: Large Language Models in Political Science / 2412.06864 / ISBN:https://doi.org/10.48550/arXiv.2412.06864 / Published by ArXiv / on (web) Publishing site

2 Preliminaries
4 Classical Political Science Functions and Modern Transformations
References

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

4 AI Ethics from User Requirements' Perspective
5 AI Ethics from Technology's Perspective

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

Our Response

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

3 Track: Against Bias in Robots

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

IV. Applications

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

3 Value Misalignment

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

3 The Psychology of Confiding and Self-Disclosure

Uncovering Bias in Foundation Models: Impact, Testing, Harm, and Mitigation / 2501.10453 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

1 Introduction
4 Method
References

Bias in Decision-Making for AI's Ethical Dilemmas: A Comparative Study of ChatGPT and Claude / 2501.10484 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

Discussion and Conclusion

Governance of Generative AI in Creative Work: Consent, Credit, Compensation, and Beyond / 2501.11457 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

5 Discussion

A Critical Field Guide for Working with Machine Learning Datasets / 2501.15491 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

7. Cautions & Reflections from the Field

Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline / 2501.18493 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

4 Findings

Meursault as a Data Point / 2502.01364 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

V. Results

FairT2I: Mitigating Social Bias in Text-to-Image Generation via Large Language Model-Assisted Detection and Attribute Rebalancing / 2502.03826 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

4. Methodologies

Safety at Scale: A Comprehensive Survey of Large Model Safety / 2502.05206 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

2 Vision Foundation Model Safety
8 Open Challenges

Position: We Need An Adaptive Interpretation of Helpful, Honest, and Harmless Principles / 2502.06059 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

5 Trade-off or Synergy? Relationship Between Different Dimensions

Comprehensive Framework for Evaluating Conversational AI Chatbots / 2502.06105 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

III. Proposed Framework

Integrating Generative Artificial Intelligence in ADRD: A Framework for Streamlining Diagnosis and Care in Neurodegenerative Diseases / 2502.06842 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

High Quality Data Collection

Fairness in Multi-Agent AI: A Unified Framework for Ethical and Equitable Autonomous Systems / 2502.07254 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

Paper

Relational Norms for Human-AI Cooperation / 2502.12102 / ISBN:https://doi.org/10.48550/arXiv.2502.12102 / Published by ArXiv / on (web) Publishing site

Section 2: Distinctive Characteristics of AI and Implications for Relational Norms

AI and the Transformation of Accountability and Discretion in Urban Governance / 2502.13101 / ISBN:https://doi.org/10.48550/arXiv.2502.13101 / Published by ArXiv / on (web) Publishing site

4. Guiding Principles for AI-Enhanced Governance in Urban Policy

Multi-Agent Risks from Advanced AI / 2502.14143 / ISBN:https://doi.org/10.48550/arXiv.2502.14143 / Published by ArXiv / on (web) Publishing site

3 Risk Factors

On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective / 2502.14296 / ISBN:https://doi.org/10.48550/arXiv.2502.14296 / Published by ArXiv / on (web) Publishing site

6 Benchmarking Large Language Models
10 Further Discussion
References

Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review / 2502.14886 / ISBN:https://doi.org/10.48550/arXiv.2502.14886 / Published by ArXiv / on (web) Publishing site

II. Background and Challenges
References

Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives / 2502.16841 / ISBN:https://doi.org/10.48550/arXiv.2502.16841 / Published by ArXiv / on (web) Publishing site

3 Data Documentation
5 Policymakers

Vision Language Models in Medicine / 2503.01863 / ISBN:https://doi.org/10.48550/arXiv.2503.01863 / Published by ArXiv / on (web) Publishing site

V. Challenges and Limitations

Medical Hallucinations in Foundation Models and Their Impact on Healthcare / 2503.05777 / ISBN:https://doi.org/10.48550/arXiv.2503.05777 / Published by ArXiv / on (web) Publishing site

3 Causes of Hallucinations

Mapping out AI Functions in Intelligent Disaster (Mis)Management and AI-Caused Disasters / 2502.16644 / ISBN:https://doi.org/10.48550/arXiv.2502.16644 / Published by ArXiv / on (web) Publishing site

References

AI Governance InternationaL Evaluation Index (AGILE Index) / 2502.15859 / ISBN:https://doi.org/10.48550/arXiv.2502.15859 / Published by ArXiv / on (web) Publishing site

Executive Summary
3. Analysis and Observations

Synthetic Data for Robust AI Model Development in Regulated Enterprises / 2503.12353 / ISBN:https://doi.org/10.48550/arXiv.2503.12353 / Published by ArXiv / on (web) Publishing site

Background
Synthetic Data Generation for Enterprise AI Development
Case Studies in Regulated Industries

A Peek Behind the Curtain: Using Step-Around Prompt Engineering to Identify Bias and Misinformation in GenAI Models / 2503.15205 / ISBN:https://doi.org/10.48550/arXiv.2503.15205 / Published by ArXiv / on (web) Publishing site

Step-Around Prompting: A Research Tool and Potential Threat

AI Family Integration Index (AFII): Benchmarking a New Global Readiness for AI as Family / 2503.22772 / ISBN:https://doi.org/10.48550/arXiv.2503.22772 / Published by ArXiv / on (web) Publishing site

4. AI-Family Integration (AFI) – Benchmarking with AI Policy Penetration and Traditional AI Index
5. Insights and Interpretation

A Framework for Developing University Policies on Generative AI Governance: A Cross-national Comparative Study / 2504.02636 / ISBN:https://doi.org/10.48550/arXiv.2504.02636 / Published by ArXiv / on (web) Publishing site

Methodology

Assessing employment and labour issues implicated by using AI / 2504.06322 / ISBN:https://doi.org/10.48550/arXiv.2504.06322 / Published by ArXiv / on (web) Publishing site

4. Discussion: Assessing Impact Using Approach 1 and 2