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You are now here: AI Ethics Primer - search within the bibliography - version 0.3 of 2023-08-13
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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
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 5. Directions for Future Research & Governance References
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
1 Introduction References
From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence / 2308.02448 / on (web) Publishing site
GREAT PLEA Ethical Principles for Generative AI in
Healthcare 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 6 The dual governance framework
Normative Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions / 2208.12616 / on (web) Publishing site
3 Taxonomy of ethics principles
Bad, mad, and cooked: Moral responsibility for civilian harms in human-AI military teams / 2211.06326 / on (web) Publishing site
Introduction Moral Injury AI Workplace Health and Safety Framework
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation / 2305.11391 / on (web) Publishing site
1 Introduction 5 Falsification and Evaluation Reference
Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust / 2308.09979 / on (web) Publishing site
References
AIxArtist: A First-Person Tale of Interacting with Artificial Intelligence to Escape Creative Block / 2308.11424 / on (web) Publishing site
References
Exploring the Power of Creative AI Tools and Game-Based Methodologies for Interactive Web-Based Programming / 2308.11649 / on (web) Publishing site
8 Real-World Applications: Showcasing Innovative
Implementations 10 Privacy Concerns in Interactive Web-Based Programming for Education 11 Bias Awareness: Navigating AI-Generated Content in Education 12 The Future Landscape: Creative AI Tools and Game-Based
Methodologies in Education 13 Case Study Example: Learning Success with Creative AI and
Game-Based Techniques
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 6 Discussion 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
Appendix A industry-wide LLM usecases
The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward / 2308.14253 / on (web) Publishing site
4 Integrating red teaming, blue teaming, and ethics with violet teaming 6 A pathway for balanced AI innovation 7 Violet teaming to address dual-use risks of AI in biotechnology 10 Supplemental & additional details References
The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / on (web) Publishing site
Executive summary 3 Benefits of AI use in the finance sector 4 Threaths & potential pitfalls 6 Regulation of AI and regulating through AI 7 Recommendations References
Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / on (web) Publishing site
1 Introduction 3 Bias and fairness 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
2. Related work 3. ChatGPT Training Process 6. Conclusion References