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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: observed

Selected tag: observed

The AI Index 2022 Annual Report / 2205.03468 / on (web) Publishing site
Chapter 1 Reseach and Development
Chapter 3 Technical AI Ethics


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


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


A Framework for Ethical AI at the United Nations / 2104.12547 / on (web) Publishing site
1. Problems with AI


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


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


GPT detectors are biased against non-native English writers / 2304.02819 / on (web) Publishing site
Results
Discussion
Materials and Methods


Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects / 2304.08275 / on (web) Publishing site
I. Introduction
II. Underlying Aspects
III. Interactions between Aspects
IV. Concluding Remarks


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
Abstract
3. Results


The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance / 2307.16787 / on (web) Publishing site
1. Introduction
2. Value Chains
4. Ethical Implications of AI Value Chains


Normative Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions / 2208.12616 / on (web) Publishing site
4 Previous operationalisation of ethical principles


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
3 Vulnerabilities, Attack, and Limitations
5 Falsification and Evaluation
8 Regulations and Ethical Use


Getting pwn'd by AI: Penetration Testing with Large Language Models / 2308.00121 / on (web) Publishing site
4 Discussion


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


Targeted Data Augmentation for bias mitigation / 2308.11386 / on (web) Publishing site
4 Experiments
5 Conclusions


Collect, Measure, Repeat: Reliability Factors for Responsible AI Data Collection / 2308.12885 / on (web) Publishing site
2 Related Work on Data Excellence
3 Reliability and Reproducibility Metrics for Responsible Data Collection
5 Results
6 Discussion
B Variability Analysis


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
III. Comprehensive review of state-of-the-art LLMs


Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / on (web) Publishing site
1 Introduction
2 Black box and lack of transparency
3 Bias and fairness