Why_this_webapp Bibliography

The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site

Report highlights
Chapter 3 Technical AI Ethics
Chapter 4 The Economy and Education
Chapter 5 AI Policy and Governance
Appendix

Ethics of AI: A Systematic Literature Review of Principles and Challenges / 2109.07906 / ISBN:https://doi.org/10.48550/arXiv.2109.07906 / Published by ArXiv / on (web) Publishing site

2 Background
3 Research Method
5 Detail results and analysis

AI Ethics Issues in Real World: Evidence from AI Incident Database / 2206.07635 / ISBN:https://doi.org/10.48550/arXiv.2206.07635 / Published by ArXiv / on (web) Publishing site

1Introduction

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

3 Study Methodology
4 Evaluation of Ethical AI Principles
5 Evaluation of Ethical Principle Implementations
References

A Framework for Ethical AI at the United Nations / 2104.12547 / ISBN:https://doi.org/10.48550/arXiv.2104.12547 / Published by ArXiv / on (web) Publishing site

Introductionn
2. Defining ethical AI

Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance / 2206.11922 / ISBN:https://doi.org/10.48550/arXiv.2206.11922 / Published by ArXiv / on (web) Publishing site

2 Related Work
3 Methodology

Beyond Near- and Long-Term: Towards a Clearer Account of Research Priorities in AI Ethics and Society / 2001.04335 / ISBN:https://doi.org/10.48550/arXiv.2001.04335 / Published by ArXiv / on (web) Publishing site

References

ESR: Ethics and Society Review of Artificial Intelligence Research / 2106.11521 / ISBN:https://doi.org/10.48550/arXiv.2106.11521 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related Work
4 Deployment and Evaluation
5 Discussion
References

On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services / 2111.01306 / ISBN:https://doi.org/10.48550/arXiv.2111.01306 / Published by ArXiv / on (web) Publishing site

1 Introduction
3 Practical Challengesof Ethical AI

A primer on AI ethics via arXiv- focus 2020-2023 / Kaggle / on (web) Publishing site

Section 1: Introduction and concept
Appendix A: Bibliographical references

What does it mean to be a responsible AI practitioner: An ontology of roles and skills / 2205.03946 / ISBN:https://doi.org/10.48550/arXiv.2205.03946 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Background
3 Methodology
5 Discussion
Appendix A supplementary material

GPT detectors are biased against non-native English writers / 2304.02819 / ISBN:https://doi.org/10.48550/arXiv.2304.02819 / Published by ArXiv / on (web) Publishing site

Introduction
Discussion

Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects / 2304.08275 / ISBN:https://doi.org/10.48550/arXiv.2304.08275 / Published by ArXiv / on (web) Publishing site

I. Introduction
III. Interactions between Aspects
IV. Concluding Remarks

QB4AIRA: A Question Bank for AI Risk Assessment / 2305.09300 / ISBN:https://doi.org/10.48550/arXiv.2305.09300 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 The Question Bank: QB4AIRA
4 Conclusion

A multilevel framework for AI governance / 2307.03198 / ISBN:https://doi.org/10.48550/arXiv.2307.03198 / Published by ArXiv / on (web) Publishing site

1. Introductioon
4. Corporate Self-Governance

Perceptions of the Fourth Industrial Revolution and Artificial Intelligence Impact on Society / 2308.02030 / ISBN:https://doi.org/10.48550/arXiv.2308.02030 / Published by ArXiv / on (web) Publishing site

Introduction
Literature Review

Regulating AI manipulation: Applying Insights from behavioral economics and psychology to enhance the practicality of the EU AI Act / 2308.02041 / ISBN:https://doi.org/10.48550/arXiv.2308.02041 / Published by ArXiv / on (web) Publishing site

1 Introduction
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 / ISBN:https://doi.org/10.48550/arXiv.2308.02448 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
GREAT PLEA Ethical Principles for Generative AI in Healthcare
References

Ethical Considerations and Policy Implications for Large Language Models: Guiding Responsible Development and Deployment / 2308.02678 / ISBN:https://doi.org/10.48550/arXiv.2308.02678 / Published by ArXiv / on (web) Publishing site

Introduction
Hallucination
Conclusion

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
3 Policy scope
4 Centralized regulation in the US context
7 Limitations
8 Conclusion

Normative Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions / 2208.12616 / ISBN:https://doi.org/10.48550/arXiv.2208.12616 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Methodology
3 Taxonomy of ethical principles
4 Previous operationalisation of ethical principles
5 Gaps in operationalising ethical principles
6 Conclusion
A Methodology

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

Computers, Autonomy and Accountability

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

1 Introduction
6 Verification
7 Runtime Monitor
8 Regulations and Ethical Use

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

3 LLM-based penetration testing

Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust / 2308.09979 / ISBN:https://doi.org/10.48550/arXiv.2308.09979 / Published by ArXiv / on (web) Publishing site

1 Introduction
3 Discussion

Targeted Data Augmentation for bias mitigation / 2308.11386 / ISBN:https://doi.org/10.48550/arXiv.2308.11386 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
3 Targeted data augmentation

Exploring the Power of Creative AI Tools and Game-Based Methodologies for Interactive Web-Based Programming / 2308.11649 / ISBN:https://doi.org/10.48550/arXiv.2308.11649 / Published by ArXiv / on (web) Publishing site

2 Advancements in AI and Web-Based Programming
7 Navigating Constraints: Limitations of Creative AI and GameBased Techniques
8 Real-World Applications: Showcasing Innovative Implementations
11 Bias Awareness: Navigating AI-Generated Content in Education
14 Conclusion & Discussion

Collect, Measure, Repeat: Reliability Factors for Responsible AI Data Collection / 2308.12885 / ISBN:https://doi.org/10.48550/arXiv.2308.12885 / Published by ArXiv / 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 / ISBN:https://doi.org/10.48550/arXiv.2308.13534 / Published by ArXiv / on (web) Publishing site

I. Introduction
II. Methods and training process of LLMs
IV. Applied and technology implications for LLMs
V. Market analysis of LLMs and cross-industry use cases
VI. Solution architecture for privacy-aware and trustworthy conversational AI
VII. Discussions
VIII. Conclusion
Appendix A industry-wide LLM usecases

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
7 Violet teaming to address dual-use risks of AI in biotechnology

Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? / 2308.15399 / ISBN:https://doi.org/10.48550/arXiv.2308.15399 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related works

The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / ISBN:https://doi.org/10.48550/arXiv.2308.16538 / Published by ArXiv / on (web) Publishing site

Executive summary
1 Introduction
4 Threaths & potential pitfalls
5 Challenges
6 Regulation of AI and regulating through AI
7 Recommendations

Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / ISBN:https://doi.org/10.48550/arXiv.2309.00064 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Black box and lack of transparency
3 Bias and fairness
4 Human-centric AI
5 Ethical concerns and value alignment
6 Way forward
7 Conclusion

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 / ISBN:https://doi.org/10.48550/arXiv.2309.02029 / Published by ArXiv / on (web) Publishing site

1. Introduction
2. Related work
3. ChatGPT Training Process
6. Conclusion
References

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

Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data
Part 2 - 2 Motion Caputer Technologies and Motion Data
Part 3 - 2 Machine Artist Models
Part 4 NFTs and the Future Art Economy
Part 5 Ethical AI and Machine Artist

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging / 2109.09658 / ISBN:https://doi.org/10.48550/arXiv.2109.09658 / Published by ArXiv / on (web) Publishing site

1. Introduction
3. Universality - For Standardised AI in Medical Imaging
4. Traceability - For Transparent and Dynamic AI in Medical Imaging
5. Usability - For Effective and Beneficial AI in Medical Imaging
7. Explainability - For Enhanced Understanding of AI in Medical Imaging
References

The Cambridge Law Corpus: A Corpus for Legal AI Research / 2309.12269 / ISBN:https://doi.org/10.48550/arXiv.2309.12269 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 The Cambridge Law Corpus
4 Experiments
Cambridge Law Corpus: Datasheet

EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval / 2310.00970 / ISBN:https://doi.org/10.48550/arXiv.2310.00970 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Related Work
References

Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities / 2310.08565 / ISBN:https://doi.org/10.48550/arXiv.2310.08565 / Published by ArXiv / on (web) Publishing site

Abstract
I. Introduction and Motivation
IV. Attack Surfaces
V. Ethical & Legal Concerns
VI. Human-Robot Interaction (HRI) Security Studies
VII. Future Research & Discussion

If our aim is to build morality into an artificial agent, how might we begin to go about doing so? / 2310.08295 / ISBN:https://doi.org/10.48550/arXiv.2310.08295 / Published by ArXiv / on (web) Publishing site

Abstract
3 Proposing a Hybrid Approach

Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks / 2310.07879 / ISBN:https://doi.org/10.48550/arXiv.2310.07879 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Background and Related Work
4 Taxonomy of AI Privacy Risks
5 Discussion
6 Conclusion
References

ClausewitzGPT Framework: A New Frontier in Theoretical Large Language Model Enhanced Information Operations / 2310.07099 / ISBN:https://doi.org/10.48550/arXiv.2310.07099 / Published by ArXiv / on (web) Publishing site

Nation-State Advances in AI-driven Information Operations

The AI Incident Database as an Educational Tool to Raise Awareness of AI Harms: A Classroom Exploration of Efficacy, Limitations, & Future Improvements / 2310.06269 / ISBN:https://doi.org/10.48550/arXiv.2310.06269 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Research Design and Methodology
3 Analysis and Findings
A Consent and Data Collection Processes
B Pre-class Questionnaire (Verbatim)
C In-class Activity
D Post-Activity Questionnaire (Verbatim)

A Review of the Ethics of Artificial Intelligence and its Applications in the United States / 2310.05751 / ISBN:https://doi.org/10.48550/arXiv.2310.05751 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
2. Literature Review
3. AI Ethical Principles
4. Implementing the Practical Use of Ethical AI Applications
5. Conclusions and Recommendations
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

I. Introduction
II. WHAT LLMS CAN DO FOR HEALTHCARE? FROM FUNDAMENTAL TASKS TO ADVANCED APPLICATIONS
III. FROM PLMS TO LLMS FOR HEALTHCARE
IV. TRAIN AND USE LLM FOR HEALTHCARE
V. EVALUATION METHOD
VI. IMPROVING FAIRNESS, ACCOUNTABILITY, TRANSPARENCY, AND ETHICS
VII. FUTURE WORK AND CONCLUSION

STREAM: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models / 2310.05563 / ISBN:https://doi.org/10.48550/arXiv.2310.05563 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction

Regulation and NLP (RegNLP): Taming Large Language Models / 2310.05553 / ISBN:https://doi.org/10.48550/arXiv.2310.05553 / Published by ArXiv / on (web) Publishing site

2 Regulation: A Short Introduction
3 LLMs: Risk and Uncertainty

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

3. Ethics of AI and Robotics
4. Systematic Review and Scientometric Analysis
5. Ethical Issues of AI and Robotics in AEC Industry
6. Discussion
7. Future Research Direction
References

Compromise in Multilateral Negotiations and the Global Regulation of Artificial Intelligence / 2309.17158 / ISBN:https://doi.org/10.48550/arXiv.2309.17158 / Published by ArXiv / on (web) Publishing site

1. Introduction
2. The practice of multilateral negotiation and the mechanisms of compromises
3. The liberal-sovereigntist multiplicity
4. Towards a compromise: drafting the normative hybridity
Notes

Towards A Unified Utilitarian Ethics Framework for Healthcare Artificial Intelligence / 2309.14617 / ISBN:https://doi.org/10.48550/arXiv.2309.14617 / Published by ArXiv / on (web) Publishing site

Utilitarian Ethics
Theory and Practical Implications

Risk of AI in Healthcare: A Comprehensive Literature Review and Study Framework / 2309.14530 / ISBN:https://doi.org/10.48550/arXiv.2309.14530 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
2. Methods for Comprehensive Review
3. Clinical Risks
4. Technical Risks
5. Conclusion

Autonomous Vehicles an overview on system, cyber security, risks, issues, and a way forward / 2309.14213 / ISBN:https://doi.org/10.48550/arXiv.2309.14213 / Published by ArXiv / on (web) Publishing site

1. Introduction
2. Autonomous vehicles
5. Cybersecurity Risks

The Return on Investment in AI Ethics: A Holistic Framework / 2309.13057 / ISBN:https://doi.org/10.48550/arXiv.2309.13057 / Published by ArXiv / on (web) Publishing site

1. Introduction
4. A Holistic Framework
5. Discussion

An Evaluation of GPT-4 on the ETHICS Dataset / 2309.10492 / ISBN:https://doi.org/10.48550/arXiv.2309.10492 / Published by ArXiv / on (web) Publishing site

4 Discussion

In Consideration of Indigenous Data Sovereignty: Data Mining as a Colonial Practice / 2309.10215 / ISBN:https://doi.org/10.48550/arXiv.2309.10215 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Definitions of Terms
3 Objectives
4 Methodology
5 Relating Case Studies to Indigenous Data Sovereignty and CARE Principles
6 Discussion

The Glamorisation of Unpaid Labour: AI and its Influencers / 2308.02399 / ISBN:https://doi.org/10.48550/arXiv.2308.02399 / Published by ArXiv / on (web) Publishing site

3 Ethical Data Collection, Responsible AI Development, and the Path Forward
4 Conclusion

Toward an Ethics of AI Belief / 2304.14577 / ISBN:https://doi.org/10.48550/arXiv.2304.14577 / Published by ArXiv / on (web) Publishing site

4. Proposed Novel Topics in an Ethics of AI Belief

Ensuring Trustworthy Medical Artificial Intelligence through Ethical and Philosophical Principles / 2304.11530 / ISBN:https://doi.org/10.48550/arXiv.2304.11530 / Published by ArXiv / on (web) Publishing site

Abstract
Ethical concerns of AI in medicine
Ethical datasets and algorithm development guidelines
Towards solving key ethical challenges in Medical AI
References

Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineering / 2209.04963 / ISBN:https://doi.org/10.48550/arXiv.2209.04963 / Published by ArXiv / on (web) Publishing site

1 Introduction
3 Governance Patterns
4 Process Patterns
5 Product Patterns
6 Related Work
7 Threats to Validity
References

The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site

Bibliography

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare / 2309.12325 / ISBN:https://doi.org/10.48550/arXiv.2309.12325 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
3 FUTURE-AI Guideline
4 Discussion
Appendix A Tables

Language Agents for Detecting Implicit Stereotypes in Text-to-Image Models at Scale / 2310.11778 / ISBN:https://doi.org/10.48550/arXiv.2310.11778 / Published by ArXiv / on (web) Publishing site

Abstract

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

1 Introduction
2 AI feedback on specific problematic AI traits
3 Generalization from a Simple Good for Humanity Principle
5 Related Work
6 Discussion
H Samples
I Responses on Prompts from PALMS, LaMDA, and InstructGPT

The Self 2.0: How AI-Enhanced Self-Clones Transform Self-Perception and Improve Presentation Skills / 2310.15112 / ISBN:https://doi.org/10.48550/arXiv.2310.15112 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related Work
3 Method
5 Discussion

A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges / 2310.16360 / ISBN:https://doi.org/10.48550/arXiv.2310.16360 / Published by ArXiv / on (web) Publishing site

I. Introduction
IV. Artificial Intelligence Embedded UAV
V. Challenges and Future Aspect on AI Enabled UAV
VI. Review Summary

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

Abstract
1 Introduction
2 Risks and Ethical Issues of Big Model
3 Investigating the Ethical Values of Large Language Models
4 Equilibrium Alignment: A Prospective Paradigm for Ethical Value Alignmen

AI for Open Science: A Multi-Agent Perspective for Ethically Translating Data to Knowledge / 2310.18852 / ISBN:https://doi.org/10.48550/arXiv.2310.18852 / Published by ArXiv / on (web) Publishing site

1 Introduction
4 Optimizing an Openness Metric in AI for Science

Artificial Intelligence Ethics Education in Cybersecurity: Challenges and Opportunities: a focus group report / 2311.00903 / ISBN:https://doi.org/10.48550/arXiv.2311.00903 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
AI Ethics in Cybersecurity

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

Abstract
1 Introduction
5 Discussion
B Placing Research Ethics for Human Participants in Historical Context

LLMs grasp morality in concept / 2311.02294 / ISBN:https://doi.org/10.48550/arXiv.2311.02294 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction

Educating for AI Cybersecurity Work and Research: Ethics, Systems Thinking, and Communication Requirements / 2311.04326 / ISBN:https://doi.org/10.48550/arXiv.2311.04326 / Published by ArXiv / on (web) Publishing site

Introduction
Literature Review
Research questions

Towards Effective Paraphrasing for Information Disguise / 2311.05018 / ISBN:https://doi.org/10.1007/978-3-031-28238-6_22 / Published by ArXiv / on (web) Publishing site

References

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

1 Introduction
2 Overview of Kantian Deontology
3 Measuring Fairness Metrics
6 Conclusion

Unlocking the Potential of ChatGPT A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing / 2304.02017 / ISBN:https://doi.org/10.48550/arXiv.2304.02017 / Published by ArXiv / on (web) Publishing site

4 Applications of ChatGPT in real-world scenarios
6 Limitations and potential challenges
8 Prompt engineering and generation
9 Future directions for ChatGPT and natural language processing
11 Conclusion

Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies / 2304.07683 / ISBN:https://doi.org/10.48550/arXiv.2304.07683 / Published by ArXiv / on (web) Publishing site

Abstract
II. Sources of bias in AI
III. Impacts of bias in AI
IV. Mitigation strategies for bias in AI
V. Fairness in AI
VI. Mitigation strategies for fairness in AI
VII. Conclusions
References

Towards ethical multimodal systems / 2304.13765 / ISBN:https://doi.org/10.48550/arXiv.2304.13765 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related Work
3 Crafting an Ethical Dataset

A Brief History of Prompt: Leveraging Language Models. (Through Advanced Prompting) / 2310.04438 / ISBN:https://doi.org/10.48550/arXiv.2310.04438 / Published by ArXiv / on (web) Publishing site

Abstract
IV. History of NLP between 2010 and 2015: the pre-attention mechanism era
VII. The second wave in 2017: rise of RL
IX. 2019: THE YEAR OF CONTROL
X. 2020-2021: the rise of LLMS
XI. 2022-current: beyond language generation
XII. Conclusions

Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agents / 2310.15065 / ISBN:https://doi.org/10.48550/arXiv.2310.15065 / Published by ArXiv / on (web) Publishing site

1 Introduction
3 Method
4 Findings
5 Discussion

She had Cobalt Blue Eyes: Prompt Testing to Create Aligned and Sustainable Language Models / 2310.18333 / ISBN:https://doi.org/10.48550/arXiv.2310.18333 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related Works
4 Empirical Evaluation and Outcomes

Revolutionizing Customer Interactions: Insights and Challenges in Deploying ChatGPT and Generative Chatbots for FAQs / 2311.09976 / ISBN:https://doi.org/10.48550/arXiv.2311.09976 / Published by ArXiv / on (web) Publishing site

1. Introduction
2. Chatbots Background and Scope of Research
3. Chatbot approaches overview: Taxonomy of existing methods
4. ChatGPT
7. Future Research Directions

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

Abstract
2 Background
4 Findings
5 Discussion
7 Conclusion

First, Do No Harm: Algorithms, AI, and Digital Product Liability Managing Algorithmic Harms Though Liability Law and Market Incentives / 2311.10861 / ISBN:https://doi.org/10.48550/arXiv.2311.10861 / Published by ArXiv / on (web) Publishing site

Bloustein Local and the Center for Urban Policy Research
Executive Summary
Why Liability Law?
Harms, Risk, and Liability Practices
Conclusion
Appendix A - What is an Algorithmic Harm? And a Bibliography
Appendix E - A Sampling of References Addressing Liability and Digital Products

Responsible AI Considerations in Text Summarization Research: A Review of Current Practices / 2311.11103 / ISBN:https://doi.org/10.48550/arXiv.2311.11103 / Published by ArXiv / on (web) Publishing site

2 Background & Related Work
3 Methods
4 Findings
B Methodology

Assessing AI Impact Assessments: A Classroom Study / 2311.11193 / ISBN:https://doi.org/10.48550/arXiv.2311.11193 / Published by ArXiv / on (web) Publishing site

Abstract
3 Study Design
4 Findings
5 Discussion
B Study Materials

GPT in Data Science: A Practical Exploration of Model Selection / 2311.11516 / ISBN:https://doi.org/10.48550/arXiv.2311.11516 / Published by ArXiv / on (web) Publishing site

I. Introduction
II. Background
III. Approach: capturing and representing heuristics behind GPT's decision-making process
V. Conclusion and future work
VI. Future work

Responsible AI Research Needs Impact Statements Too / 2311.11776 / ISBN:https://doi.org/10.48550/arXiv.2311.11776 / Published by ArXiv / on (web) Publishing site

Requiring adverse impact statements for RAI research is long overdue

Large Language Models in Education: Vision and Opportunities / 2311.13160 / ISBN:https://doi.org/10.48550/arXiv.2311.13160 / Published by ArXiv / on (web) Publishing site

II. Education and LLMS
III. Key technologies for EDULLMS
V. Key points in LLMSEDU
VI. Challenges and future directions

The Rise of Creative Machines: Exploring the Impact of Generative AI / 2311.13262 / ISBN:https://doi.org/10.48550/arXiv.2311.13262 / Published by ArXiv / on (web) Publishing site

Abstract
I. Introduction
IV. Risks of generative AI
V. Additional thoughts

Towards Auditing Large Language Models: Improving Text-based Stereotype Detection / 2311.14126 / ISBN:https://doi.org/10.48550/arXiv.2311.14126 / Published by ArXiv / on (web) Publishing site

2 Related Works
3 Methodology
4 Results and Discussion

Ethical implications of ChatGPT in higher education: A scoping review / 2311.14378 / ISBN:https://doi.org/10.48550/arXiv.2311.14378 / Published by ArXiv / on (web) Publishing site

Findings
Discussion and conclusion

Potential Societal Biases of ChatGPT in Higher Education: A Scoping Review / 2311.14381 / ISBN:https://doi.org/10.48550/arXiv.2311.14381 / Published by ArXiv / on (web) Publishing site

Introduction
Discussion
Conclusion

RAISE -- Radiology AI Safety, an End-to-end lifecycle approach / 2311.14570 / ISBN:https://doi.org/10.48550/arXiv.2311.14570 / Published by ArXiv / on (web) Publishing site

Abstract
4. Post-market surveillance phase
5. Conclusion

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

Abstract
1. Introduction: The Role of Algorithms in Protecting Privacy
3. Ethical considerations in AI decision-making
4. Addressing bias, transparency, and accountability
5. Ethical AI design principles and guidelines
8. AI in sensitive domains: healthcare, finance, criminal justice, defence, and human resources
9. Discussion on engaging stakeholders: fostering dialogue and collaboration between developers, users, and affected communities.
10. Conclusion

From deepfake to deep useful: risks and opportunities through a systematic literature review / 2311.15809 / ISBN:https://doi.org/10.48550/arXiv.2311.15809 / Published by ArXiv / on (web) Publishing site

References

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

II. US Patent law

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

Abstract
1 Introduction
3 Transparency and explainability
5 Responsiblity, accountability, and regulations
6 Environmental impact
7 Conclusion

Deepfakes, Misinformation, and Disinformation in the Era of Frontier AI, Generative AI, and Large AI Models / 2311.17394 / ISBN:https://doi.org/10.48550/arXiv.2311.17394 / Published by ArXiv / on (web) Publishing site

Abstract
VII. Ethical considerations
VIII. Proposed integrated defense framework
IX. Discussion
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

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

Integrating AI into CCTV Systems: A Comprehensive Evaluation of Smart Video Surveillance in Community Space / 2312.02078 / ISBN:https://doi.org/10.48550/arXiv.2312.02078 / Published by ArXiv / on (web) Publishing site

I. Introduction
II. Related works
V. Real-world results and evaluation
VII. Conclusion
References
Biography

Understanding Teacher Perspectives and Experiences after Deployment of AI Literacy Curriculum in Middle-school Classrooms / 2312.04839 / ISBN:https://doi.org/10.48550/arXiv.2312.04839 / Published by ArXiv / on (web) Publishing site

1 Introduction
3 Results
4 Conclusions

Generative AI in Higher Education: Seeing ChatGPT Through Universities' Policies, Resources, and Guidelines / 2312.05235 / ISBN:https://doi.org/10.48550/arXiv.2312.05235 / Published by ArXiv / on (web) Publishing site

3. Literature review
4. Method
5. Results
6. Discussion

Contra generative AI detection in higher education assessments / 2312.05241 / ISBN:https://doi.org/10.48550/arXiv.2312.05241 / Published by ArXiv / on (web) Publishing site

3. Detectors are not useful

Intelligence Primer / 2008.07324 / ISBN:https://doi.org/10.48550/arXiv.2008.07324 / Published by ArXiv / on (web) Publishing site

11 Control of intelligence

RE-centric Recommendations for the Development of Trustworthy(er) Autonomous Systems / 2306.01774 / ISBN:https://doi.org/10.48550/arXiv.2306.01774 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Related work
3 Methodology
4 Results & analysis
5 Discussion
6 Conclusion & future work

Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site

Abstract
II. Background
IV. Guidelines for promoting ethical responsibility
V. Implications whit future directions

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

1 Introduction
2 Risks of Misuse for Artificial Intelligence in Science
3 Control the Risks of AI Models in Science
5 Discussion
6 Related Works
Appendix C Detailed Implementation of SciGuard

Disentangling Perceptions of Offensiveness: Cultural and Moral Correlates / 2312.06861 / ISBN:https://doi.org/10.48550/arXiv.2312.06861 / Published by ArXiv / on (web) Publishing site

A Appendix

Navigating the generative AI era: Introducing the AI assessment scale for ethical GenAI assessment / 2312.07086 / ISBN:https://doi.org/10.48550/arXiv.2312.07086 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
The AI Assessment Scale
References

Culturally Responsive Artificial Intelligence -- Problems, Challenges and Solutions / 2312.08467 / ISBN:https://doi.org/10.48550/arXiv.2312.08467 / Published by ArXiv / on (web) Publishing site

Abstract
Introduction
Artificial intelligence – concept and ethical background
Recommendations

Investigating Responsible AI for Scientific Research: An Empirical Study / 2312.09561 / ISBN:https://doi.org/10.48550/arXiv.2312.09561 / Published by ArXiv / on (web) Publishing site

II. Background and motivation
III. Research methodology
IV. Results
V. Discussion

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

2 Background and significance
4 Results
B Extended Guiding Principles

The Economics of Human Oversight: How Norms and Incentives Affect Costs and Performance of AI Workers / 2312.14565 / ISBN:https://doi.org/10.48550/arXiv.2312.14565 / Published by ArXiv / on (web) Publishing site

II. Theoretical background and hypotheses
V. Discussion
References

Culturally-Attuned Moral Machines: Implicit Learning of Human Value Systems by AI through Inverse Reinforcement Learning / 2312.17479 / ISBN:https://doi.org/10.48550/arXiv.2312.17479 / Published by ArXiv / on (web) Publishing site

Introduction

Autonomous Threat Hunting: A Future Paradigm for AI-Driven Threat Intelligence / 2401.00286 / ISBN:https://doi.org/10.48550/arXiv.2401.00286 / Published by ArXiv / on (web) Publishing site

1. Introduction
2. Foundations of AI-driven threat intelligence
3. Autonomous threat hunting: conceptual framework
4. State-of-the-art AI techniques in autonomous threat hunting
5. Challenges in autonomous threat hunting
7. Evaluation metrics and performance benchmarks
8. Future directions and emerging trends
References

Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
3. LLMs in clinical and counseling psychology
7. Challenges and future directions

Synthetic Data in AI: Challenges, Applications, and Ethical Implications / 2401.01629 / ISBN:https://doi.org/10.48550/arXiv.2401.01629 / Published by ArXiv / on (web) Publishing site

1. Introduction
2. The generation of synthetic data
3. The usage of synthetic data
5. Conclusions

MULTI-CASE: A Transformer-based Ethics-aware Multimodal Investigative Intelligence Framework / 2401.01955 / ISBN:https://doi.org/10.48550/arXiv.2401.01955 / Published by ArXiv / on (web) Publishing site

Abstract
II. Related work
IV. System design
V. Evaluation
VII. Conclusion
References

AI Ethics Principles in Practice: Perspectives of Designers and Developers / 2112.07467 / ISBN:https://doi.org/10.48550/arXiv.2112.07467 / Published by ArXiv / on (web) Publishing site

III. Methods
IV. Results
V. Discussion and suggestions
VI. Support mechanisms

Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models / 2310.19917 / ISBN:https://doi.org/10.48550/arXiv.2310.19917 / Published by ArXiv / on (web) Publishing site

Abstract
Materials and methods
Results
Discussion
References

Resolving Ethics Trade-offs in Implementing Responsible AI / 2401.08103 / ISBN:https://doi.org/10.48550/arXiv.2401.08103 / Published by ArXiv / on (web) Publishing site

Abstract
I. Introduction
II. Approaches for Resolving Trade-offs
III. Discussion and Recommendations
IV. Concluding Remarks

Towards Responsible AI in Banking: Addressing Bias for Fair Decision-Making / 2401.08691 / ISBN:https://doi.org/10.48550/arXiv.2401.08691 / Published by ArXiv / on (web) Publishing site

Abstract
Contents / List of figures / List of tables / Acronyms
1 Introduction
4 Fairness metrics landscape in machine learning
II Mitigating bias - 5 Fairness mitigation
6 FFTree: a flexible tree to mitigate multiple fairness criteria
III Accounting for bias - 7 Addressing fairness in the banking sector
8 Fairview: an evaluative AI support for addressing fairness
9 Towards fairness through time
IV Conclusions
Bibliography

Business and ethical concerns in domestic Conversational Generative AI-empowered multi-robot systems / 2401.09473 / ISBN:https://doi.org/10.48550/arXiv.2401.09473 / Published by ArXiv / on (web) Publishing site

2 Background
6 Conclusion

FAIR Enough How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training? / 2401.11033 / ISBN:https://doi.org/10.48550/arXiv.2401.11033 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 FAIR Data Principles: Theoretical Background and Significance
3 Data Management Challenges in Large Language Models
4 Framework for FAIR Data Principles Integration in LLM Development
5 Discussion
References
Appendices

Enabling Global Image Data Sharing in the Life Sciences / 2401.13023 / ISBN:https://doi.org/10.48550/arXiv.2401.13023 / Published by ArXiv / on (web) Publishing site

Abstract
2. Background
3. Use cases representing different image data types and their challenges and status for sharing

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

Principle 1: Understand model training and output
Principle 2: Respect privacy, confidentiality, and copyright

A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations / 2401.17486 / ISBN:https://doi.org/10.48550/arXiv.2401.17486 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related work
3 Methods
4 RAI tool evaluation practices
5 Towards evaluation of RAI tool effectiveness
7 Conclusion
References

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

Abstract
1 Introduction
3 Detection
5 Discussion
6 Conclusion

Responsible developments and networking research: a reflection beyond a paper ethical statement / 2402.00442 / ISBN:https://doi.org/10.48550/arXiv.2402.00442 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Networking research today
3 Beyond technical dimensions
4 Sense of engagement and responsibility
5 Possible next steps
6 Concluding remarks
References

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

2. Related literature
4. Findings

Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube / 2402.01760 / ISBN:https://doi.org/10.48550/arXiv.2402.01760 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
2. Literature review
4. Discussion
5. Conclusion
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

1 Introduction
2 Establishing the novel aspect of AI as a crossover technology
3 Moral and ethical obligations when developing crossover AI technology
4 Recommendations to address threats posed by crossover AI technology
5 Conclusion

(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

1 Introduction
3 Methods: case-based expert deliberation
4 Results
5 Discussion

POLARIS: A framework to guide the development of Trustworthy AI systems / 2402.05340 / ISBN:https://doi.org/10.48550/arXiv.2402.05340 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Background
3 State of the practice
4 The POLARIS framework
5 POLARIS framework application

A Framework for Assessing Proportionate Intervention with Face Recognition Systems in Real-Life Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
4. Proposed framework
6. Conclusions and future work

Ethics in AI through the Practitioner's View: A Grounded Theory Literature Review / 2206.09514 / ISBN:https://doi.org/10.48550/arXiv.2206.09514 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Background
5 Findings
6 Discussion and Recommendations
8 Conclusion
A List of Included Studies
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

Introduction
Discussion
Data sharing

How do machines learn? Evaluating the AIcon2abs method / 2401.07386 / ISBN:https://doi.org/10.48550/arXiv.2401.07386 / Published by ArXiv / on (web) Publishing site

4. Results

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

1 Introduction

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
4 Discussion
Appendix A

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

Abstract
2 Emerging Management-based AI Regulation
7 Conclusion

User Modeling and User Profiling: A Comprehensive Survey / 2402.09660 / ISBN:https://doi.org/10.48550/arXiv.2402.09660 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
4 Current Taxonomy
5 Discussion and Future Research Directions

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

II. Background and Related Work
III. Unified Evaluation Framework For LLM Benchmarks
IV. Technological Aspects
VII. Discussions
VIII. Conclusion
Appendix A Examples of Benchmark Inadequacies in Technological Aspects
Appendix B Examples of Benchmark Inadequacies in Processual Elements
Appendix C Examples of Benchmark Inadequacies in Human Dynamics

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

3 The AIGC Copyright Dilemma: A What-if Analysis
References

Evolving AI Collectives to Enhance Human Diversity and Enable Self-Regulation / 2402.12590 / ISBN:https://doi.org/10.48550/arXiv.2402.12590 / Published by ArXiv / on (web) Publishing site

Abstract
3. Enhanced Performance of Free-Formed AI Collectives
5. Open Challenges for Free-Formed AI Collectives
Impact Statements

What if LLMs Have Different World Views: Simulating Alien Civilizations with LLM-based Agents / 2402.13184 / ISBN:https://doi.org/10.48550/arXiv.2402.13184 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related Work
3 CosmoAgent Simulation Setting
5 Evaluation

The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review / 2402.13635 / ISBN:https://doi.org/10.48550/arXiv.2402.13635 / Published by ArXiv / on (web) Publishing site

Results
METRIC-framework for medical training data

The European Commitment to Human-Centered Technology: The Integral Role of HCI in the EU AI Act's Success / 2402.14728 / ISBN:https://doi.org/10.48550/arXiv.2402.14728 / Published by ArXiv / on (web) Publishing site

1 The increasing importance of AI
3 There is no reliable AI regulation without a sound theory of human-AI interaction
4 There is no trustworthy AI without HCI
6 Conclusion: Navigating the future of AI and HCI within the EU AI Act framework

Multi-stakeholder Perspective on Responsible Artificial Intelligence and Acceptability in Education / 2402.15027 / ISBN:https://doi.org/10.48550/arXiv.2402.15027 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Background
6 Discussion
References

Autonomous Vehicles: Evolution of Artificial Intelligence and Learning Algorithms / 2402.17690 / ISBN:https://doi.org/10.48550/arXiv.2402.17690 / Published by ArXiv / on (web) Publishing site

Abstract
I. Introduction
II. The AI-Powered Development Life-Cycle in Autonomous Vehicles
III. Ethical Considerations and Bias in AI-Driven Software Development for Autonomous Vehicles
IV. AI’S Role in the Emerging Trend of Internet of Things (IOT) Ecosystem for Autonomous Vehicles
V. Review of Existing Research and Use Cases
VII. Conclusion

FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics / 2402.19071 / ISBN:https://doi.org/10.48550/arXiv.2402.19071 / Published by ArXiv / on (web) Publishing site

Abstract
1. Introduction
2. Background
3. Methods
5. Discussion
6. Conclusion

Guidelines for Integrating Value Sensitive Design in Responsible AI Toolkits / 2403.00145 / ISBN:https://doi.org/10.48550/arXiv.2403.00145 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Background and Related Work
5 Discussion
6 Conclusion
References
B Toolkits Considered for Inclusion

Implications of Regulations on the Use of AI and Generative AI for Human-Centered Responsible Artificial Intelligence / 2403.00148 / ISBN:https://doi.org/10.48550/arXiv.2403.00148 / Published by ArXiv / on (web) Publishing site

Abstract
1 Motivation & Background

Updating the Minimum Information about CLinical Artificial Intelligence (MI-CLAIM) checklist for generative modeling research / 2403.02558 / ISBN:https://doi.org/10.48550/arXiv.2403.02558 / Published by ArXiv / on (web) Publishing site

Abstract
Part 1C. Bias, privacy, and harm assessments

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

Abstract
I. Introduction & Motivation
II. Background & Literature Review
III. The AI-Enhanced CTI Processing Pipeline
IV. Challenges and Considerations
V. Conclusions & Future Research

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

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

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

AGI Artificial General Intelligence for Education / 2304.12479 / ISBN:https://doi.org/10.48550/arXiv.2304.12479 / Published by ArXiv / on (web) Publishing site

2. What is AGI
3. The Potentials of AGI in Transforming Future Education
4. Ethical Issues and Concerns
5. Discussion
6. Conclusion
References

Moral Judgments in Narratives on Reddit Investigating Moral Sparks via Social Commonsense and Linguistic Signals / 2310.19268 / ISBN:https://doi.org/10.48550/arXiv.2310.19268 / Published by ArXiv / on (web) Publishing site

4. Methods
5. Results
6. Discussion and Conclusion

Responsible Artificial Intelligence: A Structured Literature Review / 2403.06910 / ISBN:https://doi.org/10.48550/arXiv.2403.06910 / Published by ArXiv / on (web) Publishing site

1. Introduction
3. Analysis
5. Research Limitations
6. Conclusion

Legally Binding but Unfair? Towards Assessing Fairness of Privacy Policies / 2403.08115 / ISBN:https://doi.org/10.48550/arXiv.2403.08115 / Published by ArXiv / on (web) Publishing site

II. Related Work
III. Problem Statement
V. Representational Fairness

Towards a Privacy and Security-Aware Framework for Ethical AI: Guiding the Development and Assessment of AI Systems / 2403.08624 / ISBN:https://doi.org/10.48550/arXiv.2403.08624 / Published by ArXiv / on (web) Publishing site

2 Theoretical Background
3 Research Methodology
4 Results of the Systematic Literature Review
5 Towards Privacy- and Security-Aware Framework for Ethical AI
6 Discussion and Limitations

Review of Generative AI Methods in Cybersecurity / 2403.08701 / ISBN:https://doi.org/10.48550/arXiv.2403.08701 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Attacking GenAI
3 Cyber Offense
4 Cyber Defence
5 Implications of Generative AI in Social, Legal, and Ethical Domains

Evaluation Ethics of LLMs in Legal Domain / 2403.11152 / ISBN:https://doi.org/10.48550/arXiv.2403.11152 / Published by ArXiv / on (web) Publishing site

Abstract
4 Experiment
6 Limitations
__ The present study possesses certain limitations, specifically including the following: • Sole reliance on Chinese datasets without validation of feasibility on other languages. • Exclusive use of legal cases from the PRC, without addressing applicability in other legal systems. • The evaluation aspects may not be comprehensive, given the vast scope of legal ethics, with only a partial coverage attempted. • There is potential for expanding the number of LLM evaluated.

Trust in AI: Progress, Challenges, and Future Directions / 2403.14680 / ISBN:https://doi.org/10.48550/arXiv.2403.14680 / Published by ArXiv / on (web) Publishing site

1. Introduction
3. Findings
4. Discussion
5. Concluding Remarks and Future Directions
Reference

AI Ethics: A Bibliometric Analysis, Critical Issues, and Key Gaps / 2403.14681 / ISBN:https://doi.org/10.48550/arXiv.2403.14681 / Published by ArXiv / on (web) Publishing site

AI Ethics Development Phases Based on Keyword Analysis
Key AI Ethics Issues

Safeguarding Marketing Research: The Generation, Identification, and Mitigation of AI-Fabricated Disinformation / 2403.14706 / ISBN:https://doi.org/10.48550/arXiv.2403.14706 / Published by ArXiv / on (web) Publishing site

Introduction
Methodology
Results
Conclusion
Web Appendix A: Analysis of the Disinformation Manipulations

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

Abstract
1 Context
2 Trustworthy AI Too Many Definitions or Lack Thereof?
3 Complexities and Challenges
4 AI Regulation: Current Global Landscape
6 Bias and Fairness
7 Explainable AI as an Enabler of Trustworthy AI
A Appendix

Analyzing Potential Solutions Involving Regulation to Escape Some of AI's Ethical Concerns / 2403.15507 / ISBN:https://doi.org/10.48550/arXiv.2403.15507 / Published by ArXiv / on (web) Publishing site

Various AI Ethical Concerns
A Possible Solution to These Concerns With Government Regulation
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

Abstract
1 Introduction
4 Practical cases of unfairness in real-world setting
5 Ways to mitigate bias and promote Fairness
6 How Users can be affected by unfair ML Systems
7 Challenges and Limitations
8 Conclusion
References

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

Abstract
1 Introduction and Related Work
2 Methods
3 RQ1: What Factors Influence Members’ “Licens to Critique” when Discussing AI Ethics with their Team?
5 Discussion
6 Conclusion

Implications of the AI Act for Non-Discrimination Law and Algorithmic Fairness / 2403.20089 / ISBN:https://doi.org/10.48550/arXiv.2403.20089 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Non-discrimination law vs. algorithmic fairness

AI Act and Large Language Models (LLMs): When critical issues and privacy impact require human and ethical oversight / 2404.00600 / ISBN:https://doi.org/10.48550/arXiv.2404.00600 / Published by ArXiv / on (web) Publishing site

Abstract
5. Human Oversight
6. Large Language Models (LLMs) - Introduction
7. Artificial intelligence Liability

Exploring the Nexus of Large Language Models and Legal Systems: A Short Survey / 2404.00990 / ISBN:https://doi.org/10.48550/arXiv.2404.00990 / Published by ArXiv / on (web) Publishing site

Abstract
1 Introduction
2 Applications of Large Language Models in Legal Tasks
3 Fine-Tuned Large Language Models in Various Countries and Regions
4 Legal Problems of Large Languge Models
5 Data Resources for Large Language Models in Law
6 Conclusion and Future Directions

A Review of Multi-Modal Large Language and Vision Models / 2404.01322 / ISBN:https://doi.org/10.48550/arXiv.2404.01322 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 What is a Language Model?
3 Proprietary vs. Open Source LLMs
4 Specific Large Language Models
5 Vision Models and Multi-Modal Large Language Models
6 Model Tuning
8 Conclusions

Balancing Progress and Responsibility: A Synthesis of Sustainability Trade-Offs of AI-Based Systems / 2404.03995 / ISBN:https://doi.org/10.48550/arXiv.2404.03995 / Published by ArXiv / on (web) Publishing site

II. Background and Related Work
III. Study Design
VII. Conclusion

Designing for Human-Agent Alignment: Understanding what humans want from their agents / 2404.04289 / ISBN:https://doi.org/10.1145/3613905.3650948 / Published by ArXiv / on (web) Publishing site

4 Findings
6 Limitations

Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage / 2404.06077 / ISBN:https://doi.org/10.48550/arXiv.2404.06077 / Published by ArXiv / on (web) Publishing site

Abstract
I. Introduction
III. Proposed Design: IBIS
IV. Detailed Construction

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

A Appendices