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You are now here: AI Ethics Primer - search within the bibliography - version 0.3 of 2023-08-13 > (tag cloud) >tag_selected: country

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The AI Index 2022 Annual Report / 2205.03468 / on (web) Publishing site
Report highlights
Chapter 1 Reseach and Development
Chapter 4 The Economy and Education
Chapter 5 AI Policy and Governance
Appendix


Exciting, Useful, Worrying, Futuristic: Public Perception of Artificial Intelligence in 8 Countries / 2001.00081 / on (web) Publishing site
2 Background
3 Methodology
4 Findings
5 Discussion
6 Conclusions
References
A Questionnaire - Selected Questions


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


The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis / 2206.03225 / on (web) Publishing site
1 Introduction
2 Related Work
3 Study Methodology
4 Evaluation of Ethical AI Principles
5 Evaluation of Ethical Principle Implementations


A Framework for Ethical AI at the United Nations / 2104.12547 / on (web) Publishing site
2. Defining ethical AI


Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance / 2206.11922 / on (web) Publishing site
1 Introduction
3 Methodology
4 Results
References


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


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
Appendix B: Data and charts from arXiv


From OECD to India: Exploring cross-cultural differences in perceived trust, responsibility and reliance of AI and human experts / 2307.15452 / on (web) Publishing site
1. Introduction
References


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


Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AI / 2308.04448 / on (web) Publishing site
4 Centralized regulation in the US context


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


Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust / 2308.09979 / on (web) Publishing site
1 Introduction
2 Results
4 Conclusions


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


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


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
III. Comprehensive review of state-of-the-art LLMs
VI. Solution architecture for privacy-aware and trustworthy conversational AI