Why_this_webapp Bibliography

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

2 Background

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

4 Discussion

Pathway to Future Symbiotic Creativity / 2209.02388 / ISBN:https://doi.org/10.48550/arXiv.2209.02388 / Published by ArXiv / on (web) Publishing site

Part 4 NFTs and the Future Art Economy

Generative AI and US Intellectual Property Law / 2311.16023 / ISBN:https://doi.org/10.48550/arXiv.2311.16023 / Published by ArXiv / on (web) Publishing site

III. US Copyright law
IV. Caveart emptor: no free ride for automation
References

Navigating Privacy and Copyright Challenges Across the Data Lifecycle of Generative AI / 2311.18252 / ISBN:https://doi.org/10.48550/arXiv.2311.18252 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Legal Basis of Privacy and Copyright Concerns over Generative AI
3 Mapping Challenges throughout the Data Lifecycle
4 Lifecycle Approaches

The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment / 2312.07086 / ISBN:https://doi.org/10.48550/arXiv.2312.07086 / Published by ArXiv / on (web) Publishing site

References

Five ethical principles for generative AI in scientific research / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site

Introduction
Principle 2: Respect privacy, confidentiality, and copyright

Generative Artificial Intelligence in Higher Education: Evidence from an Analysis of Institutional Policies and Guidelines / 2402.01659 / ISBN:https://doi.org/10.48550/arXiv.2402.01659 / Published by ArXiv / on (web) Publishing site

4. Findings

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

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

1 Introduction
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

4 AI Regulation: Current Global Landscape
5 Risk

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

2 Audit the process, not just the product
3 3 Governance for safety

Not a Swiss Army Knife: Academics' Perceptions of Trade-Offs Around Generative Artificial Intelligence Use / 2405.00995 / ISBN:https://doi.org/10.48550/arXiv.2405.00995 / Published by ArXiv / on (web) Publishing site

5 Discussion

The Impact of AI on Academic Research and Publishing / 2406.06009 / Published by ArXiv / on (web) Publishing site

AI Policies Among Publishers
References

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
III. Striking a Balance Betweeen the Two Approaches
IV. Proposing an Alternative 3C Framework

RogueGPT: dis-ethical tuning transforms ChatGPT4 into a Rogue AI in 158 Words / 2407.15009 / ISBN:https://doi.org/10.48550/arXiv.2407.15009 / Published by ArXiv / on (web) Publishing site

VI. Discussion

Exploring the Role of Social Support when Integrating Generative AI into Small Business Workflows / 2407.21404 / ISBN:https://doi.org/10.48550/arXiv.2407.21404 / Published by ArXiv / on (web) Publishing site

References

Between Copyright and Computer Science: The Law and Ethics of Generative AI / 2403.14653 / ISBN:https://doi.org/10.48550/arXiv.2403.14653 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
I. The Why and How Behind LLMs
III. A Guide for Data in LLM Research
IV. The Path Ahead
Conclusion

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

3 Data Sources
4 Data Preparation
8 Model Evaluation