Why_this_webapp Bibliography

The AI Index 2022 Annual Report / 2205.03468 / on (web) Publishing site

Report highlights
Chapter 2 Technical Performance
Appendix

The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis / 2206.03225 / on (web) Publishing site

5 Evaluation of Ethical Principle Implementations

Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society / 2001.04335 / on (web) Publishing site

Abstract

ESR: Ethics and Society Review of Artificial Intelligence Research / 2106.11521 / on (web) Publishing site

A Appendix: Interview Protocol

A primer on AI ethics via arXiv- focus 2020-2023 / Kaggle / on (web) Publishing site

Section 3: Current trends 2020-2023
Section 4: Considerations and conclusions

GPT detectors are biased against non-native English writers / 2304.02819 / on (web) Publishing site

Discussion

Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects / 2304.08275 / on (web) Publishing site

III. Interactions between Aspects
References

QB4AIRA: A Question Bank for AI Risk Assessment / 2305.09300 / on (web) Publishing site

2 The Question Bank: QB4AIRA

From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence / 2308.02448 / on (web) Publishing site

Applications in Military Versus Healthcare
Identifying Ethical Concerns and Risks

Normative Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions / 2208.12616 / on (web) Publishing site

2 Methodology
A Methodology

Bad, mad, and cooked: Moral responsibility for civilian harms in human-AI military teams / 2211.06326 / on (web) Publishing site

Responsibility in War

A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation / 2305.11391 / on (web) Publishing site

7 Runtime Monitor
Reference

Targeted Data Augmentation for bias mitigation / 2308.11386 / on (web) Publishing site

1 Introduction
3 Targeted data augmentation
4 Experiments

Collect, Measure, Repeat: Reliability Factors for Responsible AI Data Collection / 2308.12885 / on (web) Publishing site

3 Reliability and Reproducibility Metrics for Responsible Data Collection
4 Published Annotation Tasks and Datasets

Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph / 2308.13534 / on (web) Publishing site

I. Introduction
VI. Solution architecture for privacy-aware and trustworthy conversational AI
Appendix A industry-wide LLM usecases

Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / on (web) Publishing site

1 Introduction
6 Way forward
References