Why_this_webapp Bibliography

The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis / 2206.03225 / ISBN:https://doi.org/10.48550/arXiv.2206.03225 / Published by ArXiv / on (web) Publishing site

5 Evaluation of Ethical Principle Implementations

Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AI / 2308.04448 / ISBN:https://doi.org/10.48550/arXiv.2308.04448 / Published by ArXiv / on (web) Publishing site

5 Crowdsourced safety mechanism

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

Responsibility in War
Moral Injury

A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation / 2305.11391 / ISBN:https://doi.org/10.48550/arXiv.2305.11391 / Published by ArXiv / on (web) Publishing site

2 Large Language Models
5 Falsification and Evaluation
Reference

Getting pwn'd by AI: Penetration Testing with Large Language Models / 2308.00121 / ISBN:https://doi.org/10.48550/arXiv.2308.00121 / Published by ArXiv / on (web) Publishing site

1 Introduction

The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward / 2308.14253 / ISBN:https://doi.org/10.48550/arXiv.2308.14253 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
4 Integrating red teaming, blue teaming, and ethics with violet teaming
5 Research directions in AI safety and violet teaming
6 A pathway for balanced AI innovation
7 Violet teaming to address dual-use risks of AI in biotechnology
8 Macrostrategy for responsible technology trajectories
9 The path forward
10 Supplemental & additional details
References

A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics / 2310.05694 / ISBN:https://doi.org/10.48550/arXiv.2310.05694 / Published by ArXiv / on (web) Publishing site

References

Ethics of Artificial Intelligence and Robotics in the Architecture, Engineering, and Construction Industry / 2310.05414 / ISBN:https://doi.org/10.48550/arXiv.2310.05414 / Published by ArXiv / on (web) Publishing site

References

Who to Trust, How and Why: Untangling AI Ethics Principles, Trustworthiness and Trust / 2309.10318 / ISBN:https://doi.org/10.48550/arXiv.2309.10318 / Published by ArXiv / on (web) Publishing site

References

Specific versus General Principles for Constitutional AI / 2310.13798 / ISBN:https://doi.org/10.48550/arXiv.2310.13798 / Published by ArXiv / on (web) Publishing site

4 Reinforcement Learning with Good-for-Humanity Preference Models
References

Unpacking the Ethical Value Alignment in Big Models / 2310.17551 / ISBN:https://doi.org/10.48550/arXiv.2310.17551 / Published by ArXiv / on (web) Publishing site

2 Risks and Ethical Issues of Big Model
References

Human participants in AI research: Ethics and transparency in practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site

References

Safety, Trust, and Ethics Considerations for Human-AI Teaming in Aerospace Control / 2311.08943 / ISBN:https://doi.org/10.48550/arXiv.2311.08943 / Published by ArXiv / on (web) Publishing site

Abstract
II. Humans In, On, and Out-of-the-Loop
III. Safety
IV. Trust
V. Ethics
References

How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site

2 Related Work
3 Methodology
References

Practical Cybersecurity Ethics: Mapping CyBOK to Ethical Concerns / 2311.10165 / ISBN:https://doi.org/10.48550/arXiv.2311.10165 / Published by ArXiv / on (web) Publishing site

4 Findings

Ethics and Responsible AI Deployment / 2311.14705 / ISBN:https://doi.org/10.48550/arXiv.2311.14705 / Published by ArXiv / on (web) Publishing site

4. Addressing bias, transparency, and accountability

Control Risk for Potential Misuse of Artificial Intelligence in Science / 2312.06632 / ISBN:https://doi.org/10.48550/arXiv.2312.06632 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
3 Control the Risks of AI Models in Science
References

Beyond principlism: Practical strategies for ethical AI use in research practices / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site

1 The “Triple-Too” problem of AI ethics
3 Five specific goals and action-guiding strategies for ethical AI use in research practices

Detecting Multimedia Generated by Large AI Models: A Survey / 2402.00045 / ISBN:https://doi.org/10.48550/arXiv.2402.00045 / Published by ArXiv / on (web) Publishing site

References

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

Abstract
1 Introduction
4 Recommendations to address threats posed by crossover AI technology
References

(A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice / 2402.01864 / ISBN:https://doi.org/10.48550/arXiv.2402.01864 / Published by ArXiv / on (web) Publishing site

5 Discussion
References

I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench / 2401.17882 / ISBN:https://doi.org/10.48550/arXiv.2401.17882 / Published by ArXiv / on (web) Publishing site

References

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

3 Results
References

Taking Training Seriously: Human Guidance and Management-Based Regulation of Artificial Intelligence / 2402.08466 / ISBN:https://doi.org/10.48550/arXiv.2402.08466 / Published by ArXiv / on (web) Publishing site

2 Emerging Management-based AI Regulation
4 Techniques of Human-Guided Training

Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence / 2402.09880 / ISBN:https://doi.org/10.48550/arXiv.2402.09880 / Published by ArXiv / on (web) Publishing site

VII. Discussions

The Minimum Information about CLinical Artificial Intelligence Checklist for Generative Modeling Research (MI-CLAIM-GEN) / 2403.02558 / ISBN:https://doi.org/10.48550/arXiv.2403.02558 / Published by ArXiv / on (web) Publishing site

References

Towards an AI-Enhanced Cyber Threat Intelligence Processing Pipeline / 2403.03265 / ISBN:https://doi.org/10.48550/arXiv.2403.03265 / Published by ArXiv / on (web) Publishing site

IV. Challenges and Considerations

A Survey on Human-AI Teaming with Large Pre-Trained Models / 2403.04931 / ISBN:https://doi.org/10.48550/arXiv.2403.04931 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 AI Model Improvements with Human-AI Teaming
3 Effective Human-AI Joint Systems
4 Safe, Secure and Trustworthy AI
5 Applications
6 Conclusion
References

The Journey to Trustworthy AI- Part 1 Pursuit of Pragmatic Frameworks / 2403.15457 / ISBN:https://doi.org/10.48550/arXiv.2403.15457 / Published by ArXiv / on (web) Publishing site

5 Risk

AI Alignment: A Comprehensive Survey / 2310.19852 / ISBN:https://doi.org/10.48550/arXiv.2310.19852 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Learning from Feedback
3 Learning under Distribution Shift
4 Assurance
5 Governance
References

Large Language Model Supply Chain: A Research Agenda / 2404.12736 / ISBN:https://doi.org/10.48550/arXiv.2404.12736 / Published by ArXiv / on (web) Publishing site

References

The Necessity of AI Audit Standards Boards / 2404.13060 / ISBN:https://doi.org/10.48550/arXiv.2404.13060 / Published by ArXiv / on (web) Publishing site

1 Introduction
3 3 Governance for safety
4 4 Auditing standards body, not standard audits
References

AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance / 2404.14660 / ISBN:https://doi.org/10.48550/arXiv.2404.14660 / Published by ArXiv / on (web) Publishing site

1 Technical assessments require an AI expert to complete — and we don’t have enough experts

War Elephants: Rethinking Combat AI and Human Oversight / 2404.19573 / ISBN:https://doi.org/10.48550/arXiv.2404.19573 / Published by ArXiv / on (web) Publishing site

3 Lessons from History: War Elephants
5 Conclusions

AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research / 2405.01859 / ISBN:https://doi.org/10.48550/arXiv.2405.01859 / Published by ArXiv / on (web) Publishing site

1. Introduction
4. Policy Recommendations
References

Trustworthy AI-Generative Content in Intelligent 6G Network: Adversarial, Privacy, and Fairness / 2405.05930 / ISBN:https://doi.org/10.48550/arXiv.2405.05930 / Published by ArXiv / on (web) Publishing site

References

A Comprehensive Overview of Large Language Models (LLMs) for Cyber Defences: Opportunities and Directions / 2405.14487 / ISBN:https://doi.org/10.48550/arXiv.2405.14487 / Published by ArXiv / on (web) Publishing site

IV. Network Security
VII. Cyber Security Operations Automation
VIII. Ethical LLMs
References

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

References

The Ethics of Interaction: Mitigating Security Threats in LLMs / 2401.12273 / ISBN:https://doi.org/10.48550/arXiv.2401.12273 / Published by ArXiv / on (web) Publishing site

References

AI Alignment through Reinforcement Learning from Human Feedback? Contradictions and Limitations / 2406.18346 / ISBN:https://doi.org/10.48550/arXiv.2406.18346 / Published by ArXiv / on (web) Publishing site

References

A Blueprint for Auditing Generative AI / 2407.05338 / ISBN:https://doi.org/10.48550/arXiv.2407.05338 / Published by ArXiv / on (web) Publishing site

3 How to audit generative AI systems?
8 Conclusion

Bridging the Global Divide in AI Regulation: A Proposal for a Contextual, Coherent, and Commensurable Framework / 2303.11196 / ISBN:https://doi.org/10.48550/arXiv.2303.11196 / Published by ArXiv / on (web) Publishing site

II. Global Divide in AI Regulation: Horizontally. Context-Specific

Generative AI for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations / 2407.11054 / ISBN:https://doi.org/10.48550/arXiv.2407.11054 / Published by ArXiv / on (web) Publishing site

Limitations of generative AI in HTA applications
References

Thorns and Algorithms: Navigating Generative AI Challenges Inspired by Giraffes and Acacias / 2407.11360 / ISBN:https://doi.org/10.48550/arXiv.2407.11360 / Published by ArXiv / on (web) Publishing site

4 Generative AI and Humans: Risks and Mitigation

Prioritizing High-Consequence Biological Capabilities in Evaluations of Artificial Intelligence Models / 2407.13059 / ISBN:https://doi.org/10.48550/arXiv.2407.13059 / Published by ArXiv / on (web) Publishing site

Introduction

Mapping the individual, social, and biospheric impacts of Foundation Models / 2407.17129 / ISBN:https://doi.org/10.48550/arXiv.2407.17129 / Published by ArXiv / on (web) Publishing site

References

Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework / 2408.00965 / ISBN:https://doi.org/10.48550/arXiv.2408.00965 / Published by ArXiv / on (web) Publishing site

References

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources / 2406.16746 / ISBN:https://doi.org/10.48550/arXiv.2406.16746 / Published by ArXiv / on (web) Publishing site

8 Model Evaluation
References

Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives / 2407.14962 / ISBN:https://doi.org/10.48550/arXiv.2407.14962 / Published by ArXiv / on (web) Publishing site

V. Bridging Research Gaps and Future Directions

Neuro-Symbolic AI for Military Applications / 2408.09224 / ISBN:https://doi.org/10.48550/arXiv.2408.09224 / Published by ArXiv / on (web) Publishing site

VII. Conclusion
References

Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site

8 Safety and Robustness (SR)
10 Transparency and Explainability (T)

Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems / 2408.15550 / ISBN:https://doi.org/10.48550/arXiv.2408.15550 / Published by ArXiv / on (web) Publishing site

References

Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site

13 Ethical requirements at a glance
References

Navigating LLM Ethics: Advancements, Challenges, and Future Directions / 2406.18841 / ISBN:https://doi.org/10.48550/arXiv.2406.18841 / Published by ArXiv / on (web) Publishing site

IV. Findings and Resultant Themes

ValueCompass: A Framework of Fundamental Values for Human-AI Alignment / 2409.09586 / ISBN:https://doi.org/10.48550/arXiv.2409.09586 / Published by ArXiv / on (web) Publishing site

6 Discussion

From human-centered to social-centered artificial intelligence: Assessing ChatGPT's impact through disruptive events / 2306.00227 / ISBN:https://doi.org/10.48550/arXiv.2306.00227 / Published by ArXiv / on (web) Publishing site

The multiple levels of AI impact

Trust or Bust: Ensuring Trustworthiness in Autonomous Weapon Systems / 2410.10284 / ISBN:https://doi.org/10.48550/arXiv.2410.10284 / Published by ArXiv / on (web) Publishing site

Abstract
II. Related Work
III. Research Methodology
IV. Challenges of AWS
V. Opportunities of AWS
References

Data Defenses Against Large Language Models / 2410.13138 / ISBN:https://doi.org/10.48550/arXiv.2410.13138 / Published by ArXiv / on (web) Publishing site

2 Ethics of Resisting LLM Inference
References
Appendices

Do LLMs Have Political Correctness? Analyzing Ethical Biases and Jailbreak Vulnerabilities in AI Systems / 2410.13334 / ISBN:https://doi.org/10.48550/arXiv.2410.13334 / Published by ArXiv / on (web) Publishing site

Abstract
Refefences

Jailbreaking and Mitigation of Vulnerabilities in Large Language Models / 2410.15236 / ISBN:https://doi.org/10.48550/arXiv.2410.15236 / Published by ArXiv / on (web) Publishing site

II. Background and Concepts
III. Jailbreak Attack Methods and Techniques
V. Evaluation and Benchmarking
VI. Research Gaps and Future Directions
References

Standardization Trends on Safety and Trustworthiness Technology for Advanced AI / 2410.22151 / ISBN:https://doi.org/10.48550/arXiv.2410.22151 / Published by ArXiv / on (web) Publishing site

3 Trends in advanced AI safety and trustworthiness standardization
References

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

Chat Bankman-Fried: an Exploration of LLM Alignment in Finance / 2411.11853 / ISBN:https://doi.org/10.48550/arXiv.2411.11853 / Published by ArXiv / on (web) Publishing site

References

GPT versus Humans: Uncovering Ethical Concerns in Conversational Generative AI-empowered Multi-Robot Systems / 2411.14009 / ISBN:https://doi.org/10.48550/arXiv.2411.14009 / Published by ArXiv / on (web) Publishing site

4 Results
References

Human-centred test and evaluation of military AI / 2412.01978 / ISBN:https://doi.org/10.48550/arXiv.2412.01978 / Published by ArXiv / on (web) Publishing site

Summary
Full Summary

Trustworthy artificial intelligence in the energy sector: Landscape analysis and evaluation framework / 2412.07782 / ISBN:https://doi.org/10.48550/arXiv.2412.07782 / Published by ArXiv / on (web) Publishing site

III. E-TAI – Methodological Framework for Trustworthy AI in the Energy Domain

Clio: Privacy-Preserving Insights into Real-World AI Use / 2412.13678 / ISBN:https://doi.org/10.48550/arXiv.2412.13678 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 High-level design of Clio
References

Large Language Model Safety: A Holistic Survey / 2412.17686 / ISBN:https://doi.org/10.48550/arXiv.2412.17686 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Taxonomy
4 Robustness to Attack
9 Technology Roadmaps / Strategies to LLM Safety in Practice
10 Governance
References

A Case Study in Acceleration AI Ethics: The TELUS GenAI Conversational Agent / 2501.18038 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

3. What is acceleration ethics?
5. Mapping overlaps between TELUS innovation and acceleration ethics in the area of privacy
References [Pending inclusion/exclusion and formatting]

Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline / 2501.18493 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

3 Methods
4 Findings
References

Towards Safe AI Clinicians: A Comprehensive Study on Large Language Model Jailbreaking in Healthcare / 2501.18632 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

References

The Human-AI Handshake Framework: A Bidirectional Approach to Human-AI Collaboration / 2502.01493 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

References

Safety at Scale: A Comprehensive Survey of Large Model Safety / 2502.05206 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

3 Large Language Model Safety
5 Vision-Language Model Safety
6 Diffusion Model Safety
References

Position: We Need An Adaptive Interpretation of Helpful, Honest, and Harmless Principles / 2502.06059 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

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

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

1 Introduction
2 Background
5 Benchmarking Text-to-Image Models
6 Benchmarking Large Language Models
7 Benchmarking Vision-Language Models
8 Other Generative Models
10 Further Discussion
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

DarkBench: Benchmarking Dark Patterns in Large Language Models / 2503.10728 / ISBN:https://doi.org/10.48550/arXiv.2503.10728 / Published by ArXiv / on (web) Publishing site

1 Introduction
Referemces

A Peek Behind the Curtain: Using Step-Around Prompt Engineering to Identify Bias and Misinformation in GenAI Models / 2503.15205 / ISBN:https://doi.org/10.48550/arXiv.2503.15205 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
Literature Review
Step-Around Prompting: A Research Tool and Potential Threat
Risks of Malicious Use of Step-Around Prompting
Discussion and Recommendations
References

Advancing Human-Machine Teaming: Concepts, Challenges, and Applications / 2503.16518 / ISBN:https://doi.org/10.48550/arXiv.2503.16518 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Taxonomies of HMT Systems
3 Empirical Studies to Promote Team Performance
4 Evaluation Methodologies of Human-Machine Teaming Systems (HMTSS)
5 Key Theoretical Approaches for Human-Machine Teaming
6 Concepts, Challenges, and Applications of Human-Machine Teaming
7 Conclusions & Future Work
References

Towards Adaptive AI Governance: Comparative Insights from the U.S., EU, and Asia / 2504.00652 / ISBN:https://doi.org/10.48550/arXiv.2504.00652 / Published by ArXiv / on (web) Publishing site

VI. Towards Adaptive AI Governance Frameworks

Bridging the Gap: Integrating Ethics and Environmental Sustainability in AI Research and Practice / 2504.00797 / ISBN:https://doi.org/10.48550/arXiv.2504.00797 / Published by ArXiv / on (web) Publishing site

4 Transversal Issues in AI Ethics and Sustainability
5 Establishing Best Practices for AI Ethics and Sustainability
References