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

Chapter 3 Technical AI Ethics
Appendix

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

3 Methodology

On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services / 2111.01306 / ISBN:https://doi.org/10.48550/arXiv.2111.01306 / Published by ArXiv / on (web) Publishing site

3 Practical Challengesof Ethical AI

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

2 Related works

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

3 Analysis and Findings

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

4. A Holistic Framework

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

3 Investigating the Ethical Values of Large Language Models

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

IV. Mitigation strategies for bias in AI

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

IX. 2019: THE YEAR OF CONTROL

She had Cobalt Blue Eyes: Prompt Testing to Create Aligned and Sustainable Language Models / 2310.18333 / ISBN:https://doi.org/10.48550/arXiv.2310.18333 / Published by ArXiv / on (web) Publishing site

2 Related Works

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

4 Fairness and equity

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

Contents / List of figures / List of tables / Acronyms
II Mitigating bias - 5 Fairness mitigation
9 Towards fairness through time

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

4 Framework for FAIR Data Principles Integration in LLM Development

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

1 The “Triple-Too” problem of AI ethics
3 Five specific goals and action-guiding strategies for ethical AI use in research practices

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

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

4 Safe, Secure and Trustworthy AI

Legally Binding but Unfair? Towards Assessing Fairness of Privacy Policies / 2403.08115 / ISBN:https://doi.org/10.48550/arXiv.2403.08115 / Published by ArXiv / on (web) Publishing site

5 Representational Fairness

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
A Appendices

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

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

S1 Additional Analyses on Engagement Analysis

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

Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives / 2407.14962 / ISBN:https://doi.org/10.48550/arXiv.2407.14962 / Published by ArXiv / on (web) Publishing site

IV. Challenges of Generative AI and LLMs

VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative Adversary / 2407.19524 / ISBN:https://doi.org/10.48550/arXiv.2407.19524 / Published by ArXiv / on (web) Publishing site

Abstract
I Introduction
2 Related Works
3 Method
4 Experiment
5 Limitation and Future Work
6 Conclusion

Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site

6 Fairness (F)

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

5 Trustworthy and Responsible AI in Human-centric Applications

Recent Advances in Hate Speech Moderation: Multimodality and the Role of Large Models / 2401.16727 / ISBN:https://doi.org/10.48550/arXiv.2401.16727 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Hate Speech
3 Methodology

Navigating LLM Ethics: Advancements, Challenges, and Future Directions / 2406.18841 / ISBN:https://doi.org/10.48550/arXiv.2406.18841 / Published by ArXiv / on (web) Publishing site

IV. Findings and Resultant Themes

The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships / 2410.20130 / ISBN:https://doi.org/10.48550/arXiv.2410.20130 / Published by ArXiv / on (web) Publishing site

1 Introduction
5 Discussion

Web Scraping for Research: Legal, Ethical, Institutional, and Scientific Considerations / 2410.23432 / ISBN:https://doi.org/10.48550/arXiv.2410.23432 / Published by ArXiv / on (web) Publishing site

4 Recommendations

A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions / 2406.03712 / ISBN:https://doi.org/10.48550/arXiv.2406.03712 / Published by ArXiv / on (web) Publishing site

VI. Trustworthiness and Safety

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

1. Introduction
5. Bias Mitigation
7. Conclusion

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

5 Technical Foundations for LLM Applications in Political Science

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

Appendices

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

1 Introduction
3 Track: Against Bias in Robots

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

5 Misuse
8 Interpretability for LLM Safety

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

1 Introduction
3 Conclusion

Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations / 2501.10685 / ISBN:https://doi.org/10.48550/arXiv.2501.10685 / Published by ArXiv / on (web) Publishing site

8- Ethical Considerations in Marketing AI

Development of Application-Specific Large Language Models to Facilitate Research Ethics Review / 2501.10741 / ISBN:https://doi.org/10.48550/arXiv.2501.10741 / Published by ArXiv / on (web) Publishing site

V. Discussion: Potential Benefits, Risks, and Replies

DebiasPI: Inference-time Debiasing by Prompt Iteration of a Text-to-Image Generative Model / 2501.18642 / ISBN:https://doi.org/10.48550/arXiv.2501.18642 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
3 Method

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.2502.03826 / Published by ArXiv / on (web) Publishing site

1. Introduction
4. Methodologies
5. Experimental Protocol
6. Results
7. Discussions and Conclusions

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

7 Benchmarking Vision-Language Models

Gender and content bias in Large Language Models: a case study on Google Gemini 2.0 Flash Experimental / 2503.16534 / ISBN:https://doi.org/10.48550/arXiv.2503.16534 / Published by ArXiv / on (web) Publishing site

4 Discussion

AI-Driven Healthcare: A Review on Ensuring Fairness and Mitigating Bias / 2407.19655 / ISBN:https://doi.org/10.48550/arXiv.2407.19655 / Published by ArXiv / on (web) Publishing site

3 Addressing and Mitigating Unfairness in AI
4 Research gaps and Future directions

Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room / 2504.16148 / ISBN:https://doi.org/10.48550/arXiv.2504.16148 / Published by ArXiv / on (web) Publishing site

4. Hybrid human-AI methods for responsible AI for education

A Design Framework for operationalizing Trustworthy Artificial Intelligence in Healthcare: Requirements, Tradeoffs and Challenges for its Clinical Adoption / 2504.19179 / ISBN:https://doi.org/10.48550/arXiv.2504.19179 / Published by ArXiv / on (web) Publishing site

5. Tradeoffs between TAI principles and requirements

The EU AI Act in Development Practice: A Pro-justice Approach / 2504.20075 / ISBN:https://doi.org/10.48550/arXiv.2504.20075 / Published by ArXiv / on (web) Publishing site

3. Applying our Pro-Justice Lens

Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room / 2504.16148 / ISBN:https://doi.org/10.48550/arXiv.2504.16148 / Published by ArXiv / on (web) Publishing site

4 AI Awareness and AI Capabilities

AI Awareness / 2504.20084 / ISBN:https://doi.org/10.48550/arXiv.2504.20084 / Published by ArXiv / on (web) Publishing site

4 AI Awareness and AI Capabilities

Generative AI in Financial Institution: A Global Survey of Opportunities, Threats, and Regulation / 2504.21574 / ISBN:https://doi.org/10.48550/arXiv.2504.21574 / Published by ArXiv / on (web) Publishing site

5. Ethical Concerns and Governance

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

Appendices

WorldView-Bench: A Benchmark for Evaluating Global Cultural Perspectives in Large Language Models / 2505.09595 / ISBN:https://doi.org/10.48550/arXiv.2505.09595 / Published by ArXiv / on (web) Publishing site

2 Background

Can we Debias Social Stereotypes in AI-Generated Images? Examining Text-to-Image Outputs and User Perceptions / 2505.20692 / ISBN:https://doi.org/10.48550/arXiv.2505.20692 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
6 Discussion