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- 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 1 Reseach and Development
Chapter 2 Technical Performance
Chapter 3 Technical AI Ethics
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
- 3 Research Method
- 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
- References
- 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
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
- 1. Problems with AI
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
- 3 Methodology
- 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
- 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
- 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
Section 2: History and prospective
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
- 4 Proposed competency framework for responsible AI practitioners
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
- Discussion
References - 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
- Abstract
I. Introduction
II. Underlying Aspects
III. Interactions between Aspects
IV. Concluding Remarks
References - 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
- 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
- 2. Theory
4. Ethical Implications of AI Value Chains - 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
- 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
- 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
- What is Generative Artificial Intelligence?
Identifying Ethical Concerns and Risks
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
- References
- 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
- 1 Introduction
4 Centralized regulation in the US context
5 Crowdsourced safety mechanism
6 The dual governance framework
7 Limitations - 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
AI Workplace Health and Safety Framework
Discussion - 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
3 Vulnerabilities, Attack, and Limitations
5 Falsification and Evaluation
6 Verification
7 Runtime Monitor
9 Discussions
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
- 4 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
2 Related works
3 Targeted data augmentation
4 Experiments
5 Conclusions
References - 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
- 3 Emergence of Creative AI Tools and Game-Based Methodologies
11 Bias Awareness: Navigating AI-Generated Content in Education
12 The Future Landscape: Creative AI Tools and Game-Based Methodologies in Education - 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
- Abstract
1 Introduction
2 Related Work on Data Excellence
3 Reliability and Reproducibility Metrics for Responsible Data Collection
4 Published Annotation Tasks and Datasets
5 Results
6 Discussion
7 Conclusions
References
C Power analysis
D Stability analysis - 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
V. Market analysis of LLMs and cross-industry use cases
VI. Solution architecture for privacy-aware and trustworthy conversational AI
VII. Discussions
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
- 3 Emerging dual-use risks and vulnerabilities in AI systems
- Artificial Intelligence in Career Counseling: A Test Case with ResumAI / 2308.14301 / ISBN:https://doi.org/10.48550/arXiv.2308.14301 / Published by ArXiv / on (web) Publishing site
- 4 Results and discussion
- 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
- Abstract
1 Introduction
3 Theory and method
4 Experiment
5 Conclusion
A Details of datasets
B Experimental details - 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
- 2 Key AI technology in financial services
3 Benefits of AI use in the finance sector
4 Threaths & potential pitfalls
5 Challenges
6 Regulation of AI and regulating through AI
References - 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
- 2 Black box and lack of transparency
3 Bias and fairness
4 Human-centric AI
5 Ethical concerns and value alignment - 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
- 3. ChatGPT Training Process
- Pathway to Future Symbiotic Creativity / 2209.02388 / ISBN:https://doi.org/10.48550/arXiv.2209.02388 / Published by ArXiv / on (web) Publishing site
- Part 1 - 1 Generatives Systems: Mimicking Artifacts
Part 2 Art Data and Human–Machine Interaction in Art Creation
Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data
Part 2 - 2 Motion Caputer Technologies and Motion Data
Part 2 - 4 Aesthetic Descriptor: Labelling Artefacts with Emotion
Part 3 - 4 Demonstration of the Proposed Framework
Part 4 NFTs and the Future Art Economy
Part 5 - 2 Algorithmics Bias in Art Generation
References - 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
2. Fairness - For Equitable AI in Medical Imaging
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
6. Robustness - For Reliable AI in Medical Imaging
8. FUTURE-AI Quality Check
9. Discussion and Conclusion
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
- 1 Introduction
2 The Cambridge Law Corpus
3 Legal and Ethical Considerations
4 Experiments
General References
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
3 Dataset Construction
5 Experiments
6 Conclusions
Appendix - 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
- I. Introduction and Motivation
- 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
- 3 Method
4 Taxonomy of AI Privacy Risks
5 Discussion
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
Theoretical Impact of LLMs on 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
3 Analysis and Findings
References - 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
- 2. Literature Review
3. AI Ethical Principles
4. Implementing the Practical Use of Ethical AI Applications
5. Conclusions and Recommendations - 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
- Abstract
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
References - 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
2 STREAM: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models
4 Conclusion and Future Work - 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
- 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
- 5. Ethical Issues of AI and Robotics in AEC Industry
6. Discussion
References - 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
- 3. Clinical Risks
4. Technical Risks - 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
- 2. Autonomous vehicles
5. Cybersecurity Risks
6. Risk management - 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
- 3. Return on Investment (ROI)
- 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
- 1 Introduction
2 Datasets and Methods
4 Discussion - 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
- Introduction
Trust and AI Ethics Principles - Toward an Ethics of AI Belief / 2304.14577 / ISBN:https://doi.org/10.48550/arXiv.2304.14577 / Published by ArXiv / on (web) Publishing site
- 5. Nascent Extant Work that Falls Within the 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
- Ethical datasets and algorithm development guidelines
Towards solving key ethical challenges in Medical AI
Ethical guidelines for medical AI model deployment
Discussion
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
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
- 3 FUTURE-AI Guideline
References
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
1 Introduction
3 Agent Benchmark
5 Related Work
References
Appendix A Data Details - 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
- 2 AI feedback on specific problematic AI traits
3 Generalization from a Simple Good for Humanity Principle
4 Reinforcement Learning with Good-for-Humanity Preference Models
References
D Generalization to Other Traits
E Response Diversity and the Size of the Generating Model
F Scaling Trends for GfH PMs - 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
- 2 Related Work
- 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 - 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
3 Investigating the Ethical Values of Large Language Models - 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
- 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
- 2 Background and Related Work
3 A Formal Language of AI for Open Science
4 Optimizing an Openness Metric in AI for Science
5 Why Openness in AI for Science
References - 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
- AI tool-specific educational concerns
- 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
- A Evaluating Current Practices for Human-Participants Research
- LLMs grasp morality in concept / 2311.02294 / ISBN:https://doi.org/10.48550/arXiv.2311.02294 / Published by ArXiv / on (web) Publishing site
- 3 The Meaning Model
4 The Moral Model
References - 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
- Abstract
Conclusions - 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
- 1 Introduction
- 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
- 2 Overview of ChatGPT and its capabilities
4 Applications of ChatGPT in real-world scenarios
6 Limitations and potential challenges
10 Future directions for ChatGPT in vision domain
References - 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
IV. Mitigation strategies for bias 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
- 2 Related Work
- 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
- II. Introduction
VIII. The third wave 2018: the rise of transformers
X. 2020-2021: the rise of LLMS - 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
- Abstract
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
- 2 Related Works
4 Empirical Evaluation and Outcomes
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
- 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
- 3 Methodology
4 Experiments - Prudent Silence or Foolish Babble? Examining Large Language Models' Responses to the Unknown / 2311.09731 / ISBN:https://doi.org/10.48550/arXiv.2311.09731 / Published by ArXiv / on (web) Publishing site
- 2 UnknownBench: Evaluating LLMs on
the Unknown
3 Experiments
4 Related Work
References - 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
- 3. Chatbot approaches overview: Taxonomy of existing methods
4. ChatGPT
5. Applications
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
- 4 Findings
- 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
- Mitigation Tools
- 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
References
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
- 4 Findings
A Overview of AIIA Instruments - 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
- Abstract
I. Introduction
III. Approach: capturing and representing heuristics behind GPT's decision-making process
IV. Comparative results
V. Conclusion and future work
VI. Future work
References - 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
- Suggestions for More Meaningful Engagement with the Impact of RAI
Research
References - 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
References - 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
- IV. Risks of generative AI
- 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
- 1 Introduction
2 Related Works
3 Methodology
References - 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
- References
- 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
- Findings
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
- 1. Introduction
2. Pre-Deployment phase
4. Post-market surveillance phase - Ethics and Responsible AI Deployment / 2311.14705 / ISBN:https://doi.org/10.48550/arXiv.2311.14705 / Published by ArXiv / on (web) Publishing site
- 1. Introduction: The Role of Algorithms in Protecting Privacy
3. Ethical considerations in AI decision-making
4. Addressing bias, transparency, and accountability - 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
- 2. Material and methods
- 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
- V. Potential harms and mitigation
- 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
- 2 Privacy and data protection
4 Fairness and equity
5 Responsiblity, accountability, and regulations
6 Environmental impact
References - 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
- III. The rise of large AI models
- 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
3 Mapping Challenges throughout the Data Lifecycle
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
III. System features
V. Real-world results and evaluation - 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
- 3 Results
- 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
- 2. The pitfalls in detecting generative AI output
- Intelligence Primer / 2008.07324 / ISBN:https://doi.org/10.48550/arXiv.2008.07324 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
12 Large language models and Generative AI - Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site
- II. Background
- 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
- 2 Risks of Misuse for Artificial Intelligence in
Science
5 Discussion
Appendix B Details of Risks Demonstration in Chemical Science
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
- Data Collection
Study 3: Implications for Responsible AI
General Discussion
References - 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
- Literature
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
- Artificial intelligence – concept and ethical background
- 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
- IV. Results
- 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 - Beyond Fairness: Alternative Moral Dimensions for Assessing Algorithms and Designing Systems / 2312.12559 / ISBN:https://doi.org/10.48550/arXiv.2312.12559 / Published by ArXiv / on (web) Publishing site
- References
- Learning Human-like Representations to Enable Learning Human Values / 2312.14106 / ISBN:https://doi.org/10.48550/arXiv.2312.14106 / Published by ArXiv / on (web) Publishing site
- 4. Experiments on Human Data using
Language Models
5. Discussion - 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
- I. Introduction
V. Discussion
VI. Conclusion
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
- Results
Discussion
Methods - 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
6. Case studies and applications
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
- 2. LLMs in cognitive and behavioral psychology
3. LLMs in clinical and counseling psychology
6. LLMs as research tools in 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
4. Risks and Challenges in Utilizing Synthetic Datasets for AI
5. Conclusions
References - 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
- III. Methodology: model development
V. Evaluation - 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
- II. Related work
IV. Results
V. Discussion and suggestions
VI. Support mechanisms
References - 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
- Results
Discussion - 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
- I. Introduction
- 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
- Contents / List of figures / List of tables / Acronyms
1 Introduction
3 Bias on demand: a framework for generating synthetic data with bias
4 Fairness metrics landscape in machine learning
II Mitigating bias - 5 Fairness mitigation
6 FFTree: a flexible tree to mitigate multiple fairness criteria
8 Fairview: an evaluative AI support for addressing fairness
9 Towards fairness through time
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
- 3 Method
References - 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
6 Conclusion
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
4. Towards global image data sharing
Towards Global Image Data Sharing: A to-do list for various stakeholders - 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 5: Use AI transparently and reproducibly
References - 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
- 2 Related work
3 Methods
4 RAI tool evaluation practices
5 Towards evaluation of RAI tool effectiveness
References
A List of RAI tools, with their primary publication
B RAI tools listed by target stage of AI development
D Summary of themes and codes - 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
2 Generation
3 Detection
4 Tools
5 Discussion
6 Conclusion
References - 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
- 2 Networking research today
- 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
- 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
- 1. Introduction
C. ROSE: Tool and Data ResOurces to Explore the Instability of SEntiment Analysis Systems - 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
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
- 2 Related work and our approach
6 Conclusion - 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
- 2 Background
5 POLARIS framework application - 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
- 2 Background
5 Findings - 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
- Data availability
- 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
- 2 Related Work
4 Awareness Dataset: AWAREEVAL
5 Experiments
Ethical Statement
References
A AWAREEVAL Dataset Details
B Experimental Settings & Results - 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
- 4 Techniques of Human-Guided
Training
- 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
- 1 Introduction
4 Current Taxonomy
References - 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
- I. Introduction
III. Unified Evaluation Framework For LLM Benchmarks
VII. Discussions
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
- 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
- 3. Enhanced Performance of Free-Formed AI
Collectives
- 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
- Abstract
3 CosmoAgent Simulation Setting
4 CosmoAgent Architecture
8 Conclusion
A CosmoAgent Prompt - 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
- Abstract
Results
METRIC-framework for medical training data
Discussion
Methods
References - 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
- 1 Introduction
2 Background
6 Discussion - 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
- II. The AI-Powered Development Life-Cycle in
Autonomous Vehicles
VI. AI and Learning Algorithms Statistics for Autonomous Vehicles - Envisioning the Applications and Implications of Generative AI for News Media / 2402.18835 / ISBN:https://doi.org/10.48550/arXiv.2402.18835 / Published by ArXiv / on (web) Publishing site
- 2 The Suitability of Generative AI for Newsroom Tasks
- 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
3 Methodology
5 Discussion
References - 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
- References
- 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
- Part 1A. Study design for generative modeling
Part 1B. Best practices for cohort selection
Part 1C. Bias, privacy, and harm assessments
Part 2. A new train-test split for prompt development and few-shot learning
Part 3. Updates to baseline selection
Part 4A. Automated model evaluation
Part 5. Interpretability of generative models
Table 1. Updated MI-CLAIM checklist for generative AI clinical studies. - 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
- I. Introduction & Motivation
II. Background & Literature Review
III. The AI-Enhanced CTI Processing Pipeline
IV. Challenges and Considerations
References - 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
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
- 4. Ethical Issues and Concerns
- 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
- 1. Introduction
2. Related Work
3. Data
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
- 2. Research Methodology
3. Analysis
References - 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
- 1 Introduction
- 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
- 1 Introduction
2 Attacking GenAI
4 Cyber Defence - 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
- 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
- 3. Findings
4. Discussion - 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
- 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
Data
Results - 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
- 3 Complexities and Challenges
4 AI Regulation: Current Global Landscape
5 Risk
A Appendix - 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
5 Ways to mitigate bias and promote Fairness
7 Challenges and Limitations
References - Domain-Specific Evaluation Strategies for AI in Journalism / 2403.17911 / ISBN:https://doi.org/10.48550/arXiv.2403.17911 / Published by ArXiv / on (web) Publishing site
- 2 Existing AI Evaluation Approaches
3 Blueprints for AI Evaluation in Journalism
4 Future Directions and 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
- 1 Introduction and Related Work
References - 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
- 3 Implications of the AI Act
4 Practical challenges for compliance
References
A Appendix - 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
- 3. The definition of artificial intelligence systems
5. Human Oversight - 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
3 Fine-Tuned Large Language Models in Various Countries and Regions
5 Data Resources for Large Language Models in Law
References - 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
- 4 Specific Large Language Models
5 Vision Models and Multi-Modal Large Language Models
6 Model Tuning - 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
- 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
II. Preliminaries
III. Proposed Design: IBIS
IV. Detailed Construction
V. Implementation on DAML
VI. Evaluation - Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Generative Agents / 2404.06750 / ISBN:https://arxiv.org/abs/2404.06750 / Published by ArXiv / on (web) Publishing site
- 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
- A Appendices