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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: biased
The AI Index 2022 Annual Report / 2205.03468 / on (web) Publishing site
Report highlights Chapter 3 Technical AI Ethics
AI Ethics Issues in Real World: Evidence from AI Incident Database / 2206.07635 / on (web) Publishing site
2 Related Work 4 Results
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
Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance / 2206.11922 / on (web) Publishing site
3 Methodology References
ESR: Ethics and Society Review of Artificial Intelligence Research / 2106.11521 / on (web) Publishing site
2 Related Work 3 The ESR Process References
On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services / 2111.01306 / on (web) Publishing site
1 Introduction
Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects / 2304.08275 / on (web) Publishing site
II. Underlying Aspects
A multilevel framework for AI governance / 2307.03198 / on (web) Publishing site
6. Psychology of Trust
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
Regulating AI manipulation: Applying Insights from behavioral economics and psychology to enhance the practicality of the EU AI Act / 2308.02041 / on (web) Publishing site
2 Clarifying Terminologies of Article-5: Insights from Behavioral Economics and Psychology
From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence / 2308.02448 / on (web) Publishing site
What is Generative Artificial Intelligence? Identifying Ethical Concerns and Risks References
Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AI / 2308.04448 / on (web) Publishing site
2 Background 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
3 Vulnerabilities, Attack, and Limitations
Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust / 2308.09979 / on (web) Publishing site
3 Discussion
Targeted Data Augmentation for bias mitigation / 2308.11386 / on (web) Publishing site
2 Related works 3 Targeted data augmentation References
Exploring the Power of Creative AI Tools and Game-Based Methodologies for Interactive Web-Based Programming / 2308.11649 / on (web) Publishing site
11 Bias Awareness: Navigating AI-Generated Content in Education
Collect, Measure, Repeat: Reliability Factors for Responsible AI Data Collection / 2308.12885 / on (web) Publishing site
Abstract
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
IV. Applied and technology implications for LLMs
The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward / 2308.14253 / on (web) Publishing site
3 Emerging dual-use risks and vulnerabilities in AI systems 4 Integrating red teaming, blue teaming, and ethics with violet teaming
The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / on (web) Publishing site
4 Threaths & potential pitfalls 5 Challenges
Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / on (web) Publishing site
1 Introduction 3 Bias and fairness 4 Human-centric AI 6 Way forward References
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
1. Introduction 3. ChatGPT Training Process 4. Methods