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Tag: blame
Bibliography items where occurs: 40
- From OECD to India: Exploring cross-cultural differences in perceived trust, responsibility and reliance of AI and human experts / 2307.15452 / ISBN:https://doi.org/10.48550/arXiv.2307.15452 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
4. Discussion and conclusion
References - Bad, mad, and cooked: Moral responsibility for civilian harms in human-AI military teams / 2211.06326 / ISBN:https://doi.org/10.48550/arXiv.2211.06326 / Published by ArXiv / on (web) Publishing site
- Introduction
Responsibility in War
Computers, Autonomy and Accountability
Moral Injury
Conclusion - Pathway to Future Symbiotic Creativity / 2209.02388 / ISBN:https://doi.org/10.48550/arXiv.2209.02388 / Published by ArXiv / on (web) Publishing site
- Part 5 - 1 Authorship and Ownership of AI-generated Works of Artt
- Toward an Ethics of AI Belief / 2304.14577 / ISBN:https://doi.org/10.48550/arXiv.2304.14577 / Published by ArXiv / on (web) Publishing site
- 3. Proposed Novel Topics in an Ethics of AI Belief
References - Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 The Causal Condition
6 Degree of Responsibility
7 Conclusion and Future Work
References - Survey on AI Ethics: A Socio-technical Perspective / 2311.17228 / ISBN:https://doi.org/10.48550/arXiv.2311.17228 / Published by ArXiv / on (web) Publishing site
- 5 Responsiblity, accountability, and regulations
- Intelligence Primer / 2008.07324 / ISBN:https://doi.org/10.48550/arXiv.2008.07324 / Published by ArXiv / on (web) Publishing site
- 13 Legal implications
- Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health / 2312.11803 / ISBN:https://doi.org/10.48550/arXiv.2312.11803 / Published by ArXiv / on (web) Publishing site
- 4 Results
B Extended Guiding Principles - Commercial AI, Conflict, and Moral Responsibility: A theoretical analysis and practical approach to the moral responsibilities associated with dual-use AI technology / 2402.01762 / ISBN:https://doi.org/10.48550/arXiv.2402.01762 / Published by ArXiv / on (web) Publishing site
- References
- Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist / 2311.02107 / ISBN:https://doi.org/10.48550/arXiv.2311.02107 / Published by ArXiv / on (web) Publishing site
- Reference
- Mapping the Ethics of Generative AI: A Comprehensive Scoping Review / 2402.08323 / ISBN:https://doi.org/10.48550/arXiv.2402.08323 / Published by ArXiv / on (web) Publishing site
- References
- Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications / 2402.12216 / ISBN:https://doi.org/10.48550/arXiv.2402.12216 / Published by ArXiv / on (web) Publishing site
- 6 Implications and Recommendations
- Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness Metrics / 2311.05227 / ISBN:https://doi.org/10.48550/arXiv.2311.05227 / Published by ArXiv / on (web) Publishing site
- References
- Moral Sparks in Social Media Narratives / 2310.19268 / ISBN:https://doi.org/10.48550/arXiv.2310.19268 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Related Work
3. Data
4. Methods
5. Results
6. Discussion and Conclusion
References - The Pursuit of Fairness in Artificial Intelligence Models A Survey / 2403.17333 / ISBN:https://doi.org/10.48550/arXiv.2403.17333 / Published by ArXiv / on (web) Publishing site
- 4 Practical cases of unfairness in real-world setting
- Power and Play Investigating License to Critique in Teams AI Ethics Discussions / 2403.19049 / ISBN:https://doi.org/10.48550/arXiv.2403.19049 / Published by ArXiv / on (web) Publishing site
- 5 Discussion
- Epistemic Power in AI Ethics Labor: Legitimizing Located Complaints / 2402.08171 / ISBN:https://doi.org/10.1145/3630106.3658973 / Published by ArXiv / on (web) Publishing site
- 4 Grey Skin as Technofix: Failures to
Lodge Located Complaints
- From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap / 2404.13131 / ISBN:https://doi.org/10.1145/3630106.3658951 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 How Claim Replicability Helps Bridge the Responsiblity Gap
References - Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis / 2404.13861 / ISBN:https://doi.org/10.48550/arXiv.2404.13861 / Published by ArXiv / on (web) Publishing site
- 2 Mechanistic Agency: A Common View in AI Practice
- How Ethical Should AI Be? How AI Alignment Shapes the Risk Preferences of LLMs / 2406.01168 / ISBN:https://doi.org/10.48550/arXiv.2406.01168 / Published by ArXiv / on (web) Publishing site
- IV. Impact of Alignments on Corporate Investment Forecasts
- A Blueprint for Auditing Generative AI / 2407.05338 / ISBN:https://doi.org/10.48550/arXiv.2407.05338 / Published by ArXiv / on (web) Publishing site
- 4 Governance audits
- Challenges and Best Practices in Corporate AI Governance:Lessons from the Biopharmaceutical Industry / 2407.05339 / ISBN:https://doi.org/10.48550/arXiv.2407.05339 / Published by ArXiv / on (web) Publishing site
- 4 Discussion | Best practices and lessons learned
- Operationalising AI governance through ethics-based auditing: An industry case study / 2407.06232 / Published by ArXiv / on (web) Publishing site
- 6. Lessons learned from AstraZeneca’s 2021 AI audit
- The Problems with Proxies: Making Data Work Visible through Requester Practices / 2408.11667 / ISBN:https://doi.org/10.48550/arXiv.2408.11667 / Published by ArXiv / on (web) Publishing site
- Introduction
- Why business adoption of quantum and AI technology must be ethical / 2312.10081 / ISBN:https://doi.org/10.48550/arXiv.2312.10081 / Published by ArXiv / on (web) Publishing site
- Argument from a holistic and humanistic perspective
- Investigating Labeler Bias in Face Annotation for Machine Learning / 2301.09902 / ISBN:https://doi.org/10.48550/arXiv.2301.09902 / Published by ArXiv / on (web) Publishing site
- References
- Vernacularizing Taxonomies of Harm is Essential for Operationalizing Holistic AI Safety / 2410.16562 / ISBN:https://doi.org/10.48550/arXiv.2410.16562 / Published by ArXiv / on (web) Publishing site
- Overgeneral Taxonomies Can Compound Potential Harms
- Nteasee: A mixed methods study of expert and general population perspectives on deploying AI for health in African countries / 2409.12197 / ISBN:https://doi.org/10.48550/arXiv.2409.12197 / Published by ArXiv / on (web) Publishing site
- 3 Results
- Good intentions, unintended consequences: exploring forecasting harms
/ 2411.16531 / ISBN:https://doi.org/10.48550/arXiv.2411.16531 / Published by ArXiv / on (web) Publishing site
- 2 Harms in forecasting
5 Discussion
Appendices - Bots against Bias: Critical Next Steps for Human-Robot Interaction / 2412.12542 / ISBN:https://doi.org/10.1017/9781009386708.023 / Published by ArXiv / on (web) Publishing site
- 2 Track: Robots against Bias
- Development of Application-Specific Large Language Models to Facilitate Research Ethics Review / 2501.10741 / ISBN:https://doi.org/10.48550/arXiv.2501.10741 / Published by ArXiv / on (web) Publishing site
- References
- Agentic AI: Expanding the Algorithmic Frontier of Creative Problem Solving / 2502.00289 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site
- Liability, Consent, and Accountability
- Relational Norms for Human-AI Cooperation / 2502.12102 / ISBN:https://doi.org/10.48550/arXiv.2502.12102 / Published by ArXiv / on (web) Publishing site
- Section 2: Distinctive Characteristics of AI and Implications for Relational Norms
References - Multi-Agent Risks from Advanced AI / 2502.14143 / ISBN:https://doi.org/10.48550/arXiv.2502.14143 / Published by ArXiv / on (web) Publishing site
- 3 Risk Factors
4 Implications
References - On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective / 2502.14296 / ISBN:https://doi.org/10.48550/arXiv.2502.14296 / Published by ArXiv / on (web) Publishing site
- 6 Benchmarking Large Language Models
10 Further Discussion
References - Why do we do this?: Moral Stress and the Affective Experience of Ethics in Practice / 2502.18395 / ISBN:https://doi.org/10.48550/arXiv.2502.18395 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
References - Digital Dybbuks and Virtual Golems: AI, Memory, and the Ethics of Holocaust Testimony / 2503.01369 / ISBN:https://doi.org/10.48550/arXiv.2503.01369 / Published by ArXiv / on (web) Publishing site
- The permissibility of digital duplicates in Holocaust remembrance and education
References - AI Automatons: AI Systems Intended to Imitate Humans / 2503.02250 / ISBN:https://doi.org/10.48550/arXiv.2503.02250 / Published by ArXiv / on (web) Publishing site
- References
- Mapping out AI Functions in Intelligent Disaster (Mis)Management and AI-Caused Disasters / 2502.16644 / ISBN:https://doi.org/10.48550/arXiv.2502.16644 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
4. Discussion - Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents
/ 2504.01029 / ISBN:https://doi.org/10.48550/arXiv.2504.01029 / Published by ArXiv / on (web) Publishing site
- 4. Taxonomy of AI Privacy and Ethical Incidents