Why_this_webapp Bibliography

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

Chapter 2 Technical Performance
Chapter 3 Technical AI Ethics
Appendix

Exciting, Useful, Worrying, Futuristic: Public Perception of Artificial Intelligence in 8 Countries / 2001.00081 / on (web) Publishing site

3 Methodology

Ethics of AI: A Systematic Literature Review of Principles and Challenges / 2109.07906 / on (web) Publishing site

3 Research Method

AI Ethics Issues in Real World: Evidence from AI Incident Database / 2206.07635 / on (web) Publishing site

4 Results

Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance / 2206.11922 / on (web) Publishing site

5 Discussion

On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services / 2111.01306 / on (web) Publishing site

3 Practical Challengesof Ethical AI
References

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

Section 2: History and prospective

What does it mean to be a responsible AI practitioner: An ontology of roles and skills / 2205.03946 / on (web) Publishing site

References

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

II. Underlying Aspects
III. Interactions between Aspects
References

The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance / 2307.16787 / on (web) Publishing site

4. Ethical Implications of AI Value Chains

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

What is Generative Artificial Intelligence?

Ethical Considerations and Policy Implications for Large Language Models: Guiding Responsible Development and Deployment / 2308.02678 / on (web) Publishing site

Introduction

The Future of ChatGPT-enabled Labor Market: A Preliminary Study / 2304.09823 / on (web) Publishing site

5 Methods

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

2 Large Language Models
3 Vulnerabilities, Attack, and Limitations
5 Falsification and Evaluation
6 Verification
7 Runtime Monitor
Reference

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

1 Introduction
2 Related works
4 Experiments

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

4 Published Annotation Tasks and Datasets
5 Results
References

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

II. Methods and training process of LLMs

Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? / 2308.15399 / on (web) Publishing site

2 Related works
4 Experiment
B Experimental details

The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / on (web) Publishing site

2 Key AI technology in financial services

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

2 Black box and lack of transparency

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 / on (web) Publishing site

3. ChatGPT Training Process