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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 4 The Economy and Education
Chapter 5 AI Policy and Governance
Appendix - Exciting, Useful, Worrying, Futuristic:
Public Perception of Artificial Intelligence in 8 Countries / 2001.00081 / ISBN:https://doi.org/10.48550/arXiv.2001.00081 / Published by ArXiv / on (web) Publishing site
- 2 Background
4 Findings
5 Discussion
References - 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
- Abstract
1 Introduction
2 Background
3 Research Method
5 Detail results and analysis
6 Threats to validity
7 Conclusions and future directions
References
9 Appendices - 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
- Abstract
1Introduction
2 Related Work
4 Results
5 Discussion - 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
- Abstract
1 Introduction
2 Related Work
3 Study Methodology
4 Evaluation of Ethical AI Principles
5 Evaluation of Ethical Principle Implementations
6 Gap Mitigation
8 Conclusion
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
1. Problems with AI
2. Defining ethical AI
3. Implementing ethical AI
Conclusion - 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
- 1 Introduction
2 Related Work
3 Methodology
4 Results
5 Discussion - 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
- 4 A Clearer Account of Research Priorities and Disagreements
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
- 2 Related Work
4 Deployment and Evaluation
7 Acknowledgments
A Appendix: Interview Protocol
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
2 The Need forEthical AI in Finance
3 Practical Challengesof Ethical AI
4 Conclusions & Outlook
References - A primer on AI ethics via arXiv- focus 2020-2023 / Kaggle / Published by Kaggle / on (web) Publishing site
- Section 1: Introduction and concept
Section 2: History and prospective
Section 3: Current trends 2020-2023
Section 4: Considerations and conclusions
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
- Abstract
1 Introduction
2 Background
3 Methodology
4 Proposed competency framework for responsible AI practitioners
5 Discussion
References
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
- Abstract
Introduction
Results
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 - 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
- 1 Introduction
2 The Question Bank: QB4AIRA
3 Evaluation - 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
3. International and National Governance
4. Corporate Self-Governance
5. AI Literacy and Governance by Citizen
6. Psychology of Trust
7. Propensity to Trust
8. Ethics and Trust Lenses in the Multilevel Framework
9. Virtue Ethics
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
2. Method
References - The Ethics of AI Value Chains / 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
5. Future Directions for Research, Practice, & Policy - 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
Results
References - 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
3 Enhancing Protection for the General Public and Vulnerable Groups
4 Conclusion
References - 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
What is Generative Artificial Intelligence?
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
- System-role
Generation-related
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
2 Background
3 Policy scope
4 Centralized regulation in the US context
6 The dual governance framework
7 Limitations - 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
References
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
- Abstract
Introduction
Responsibility in War
Computers, Autonomy and Accountability
Moral Injury
Human Factors
AI Workplace Health and Safety Framework
Discussion
Conclusion
References - The Future of ChatGPT-enabled Labor Market: A Preliminary Study / 2304.09823 / ISBN:https://doi.org/10.48550/arXiv.2304.09823 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Results
3 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
- Abstract
1 Introduction
2 Large Language Models
3 Vulnerabilities, Attack, and Limitations
5 Falsification and Evaluation
6 Verification
7 Runtime Monitor
8 Regulations and Ethical Use
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
- 5 A vision of AI-augmented pen-testing
References - 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
- Abstract
1 Introduction
2 Results
3 Discussion
4 Conclusions
5 Supplementary material
References - Targeted Data Augmentation for bias mitigation / 2308.11386 / ISBN:https://doi.org/10.48550/arXiv.2308.11386 / Published by ArXiv / on (web) Publishing site
- 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
- 2 Advancements in AI and Web-Based Programming
3 Emergence of Creative AI Tools and Game-Based Methodologies
5 Engaging Web-Based Programming with Game-Based Approaches
7 Navigating Constraints: Limitations of Creative AI and GameBased Techniques
8 Real-World Applications: Showcasing Innovative Implementations
9 Ethical Considerations in Integrating AI and Game Elements
10 Privacy Concerns in Interactive Web-Based Programming for Education
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
- Abstract
1 Introduction
2 Related Work on Data Excellence
4 Published Annotation Tasks and Datasets
5 Results
7 Conclusions
References
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
- Abstract
I. Introduction
II. Methods and training process of LLMs
III. Comprehensive review of state-of-the-art 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
- 2 The evolution of artificial intelligence: from theory to general capabilities
4 Integrating red teaming, blue teaming, and ethics with violet teaming
5 Research directions in AI safety and violet teaming
6 A pathway for balanced AI innovation
7 Violet teaming to address dual-use risks of AI in biotechnology
10 Supplemental & additional details
References - 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
2 Related Works
3 Theory and Method
4 Experiment
References - 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
- Table of contents and index
Executive summary
1 Introduction
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
7 Recommendations
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
- 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
References - 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
- 2. Related work
3. ChatGPT Training Process
4. Methods
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
- Introduction
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 2 - 5 Immersive Visualisation: Machine to Human Manifestations
Part 3 - 4 Demonstration of the Proposed Framework
Part 4 NFTs and the Future Art Economy
Part 5 - 1 Authorship and Ownership of AI-generated Works of Artt
Part 5 - 2 Algorithmics Bias in Art Generation
Part 5 - 3 Democratization of Art with new Technologies
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
- Abstract
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
7. Explainability - For Enhanced Understanding of AI in Medical Imaging
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
4 Experiments
E Topic Model Top Words
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
- 1 Introduction
3 Dataset Construction
5 Experiments
6 Conclusions
Appendix
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
III. Survey Approach & Taxonomy
IV. Attack Surfaces
VI. Human-Robot Interaction (HRI) Security Studies
VII. Future Research & Discussion
VIII. Conclusion
References - 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
4 AI Governance Principles
5 Towards Moral AI
References - 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
- 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
- Introduction
Nation-State Advances in AI-driven Information Operations
Mathematical Foundations
Ethical and Strategic Considerations: AI Mediators in the Age of LLMs
Integrating Computational Social Science, Computational Ethics, Systems Engineering, and AI Ethics in LLMdriven Operations
Looking Forward: ClausewitzGPT
Conclusion - 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
- Abstract
1 Introduction
3 Analysis and Findings
4 Discussion
5 Conclusion
References
A Consent and Data Collection Processes
B Pre-class Questionnaire (Verbatim)
D Post-Activity Questionnaire (Verbatim)
G Statistical Tests - 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
Authors - 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
I. INTRODUCTION
II. WHAT LLM S CAN DO FOR HEALTHCARE ? FROM FUNDAMENTAL TASKS TO ADVANCED APPLICATIONS
III. FROM PLM S TO LLM S 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
- 1 Introduction
2 STREAM: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models
References - 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
- 1 Introduction
2 Regulation: A Short Introduction
3 LLMs: Risk and Uncertainty
4 Scientific Expertise, Social Media and Regulatory Capture
5 Regulation and NLP (RegNLP): A New Field
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
- Abstract
3. Ethics of AI and Robotics
4. Systematic Review and Scientometric Analysis
5. Ethical Issues of AI and Robotics in AEC Industry
7. Future Research Direction
References - Commercialized Generative AI: A Critical Study of the Feasibility and Ethics of Generating Native Advertising Using Large Language Models in Conversational Web Search / 2310.04892 / ISBN:https://doi.org/10.48550/arXiv.2310.04892 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Background and Related Work
Pilot Study: Text SERPs with Ads
Evaluation of the Pilot Study
Ethics of GEnerating Native Ads
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
3. The liberal-sovereigntist multiplicity
4. Towards a compromise: drafting the normative hybridity
5. Text negotiations as normative testing
Notes
Bibliography
Annex 1. Text amendments and ambiguity - 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
- Introduction
Why Ethics
Utilitarian Ethics
Principal Ethics in Healthcare
Results and Discussion
A Unified Utilitarian Ethics Framework
Theory and Practical Implications
Conclusion - 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
- 4. Technical Risks
References - 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
4. Traffic Flow prediction in Autonomous vehicles
5. Cybersecurity Risks
6. Risk management
9. References - 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
2. AI Ethics
3. Return on Investment (ROI)
4. A Holistic Framework
5. Discussion
6. References - 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
- 3 Results
A GPT-4’s Training Set Personality Profile - 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
- Abstract
Introduction
Trust
Trust in AI
Different Types of Trust
Trust and AI Ethics Principles
Trust in AI as Socio-Technical Systems
Conclusion
References - 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
- 3 Objectives
7 Conclusions and Recommendations
References - 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
- Abstract
1 Introduction
3 Ethical Data Collection, Responsible AI Development, and the Path Forward
References - AI & Blockchain as sustainable teaching and learning tools to cope with the 4IR / 2305.01088 / ISBN:https://doi.org/10.48550/arXiv.2305.01088 / Published by ArXiv / on (web) Publishing site
- Authors
Abstract
1. Introduction
4. Blockchain-based credentialing and certification
5. AI-powered assessment and evaluation
6. Blockchain-based decentralized learning networks
8. Case studies: AI and blockchain in education - Toward an Ethics of AI Belief / 2304.14577 / ISBN:https://doi.org/10.48550/arXiv.2304.14577 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
3. Proposed Novel Topics in an Ethics of AI Belief
4. Nascent Extant Work that Falls Within the Ethics of AI Belief
References - 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 concerns of AI in medicine
Ethical datasets and algorithm development guidelines
Towards solving key ethical challenges in Medical AI
Ethical guidelines for medical AI model deployment - 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
- Abstract
1 Introduction
2 Methodology
3 Governance Patterns
4 Process Patterns
5 Product Patterns
6 Related Work
8 Conclusion
References - The Ethics of AI Value Chains / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site
- Bibliography
Appendix A: Integrated Inventory of Ethical Concerns, Value Chains Actors, Resourcing Activities, & Sampled Sources - 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
INTRODUCTION
METHODS
FUTURE-AI GUIDELINE
DISCUSSION - 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
4 Agent Performance
6 Conclusion and Future Work
References - Specific versus General Principles for Constitutional AI / 2310.13798 / ISBN:https://doi.org/10.48550/arXiv.2310.13798 / Published by ArXiv / on (web) Publishing site
- Contents
1 Introduction
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
5 Related Work
6 Discussion
7 Contribution Statement
References
A Model Glossary
B Trait Preference Modeling
D Generalization to Other Traits
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
4 Findings
5 Discussion
6 Conclusion
References
Annexed tables - Systematic AI Approach for AGI:
Addressing Alignment, Energy, and AGI Grand Challenges / 2310.15274 / ISBN:https://doi.org/10.48550/arXiv.2310.15274 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Trifecta of AI Challenges
5 System Design for AI Alignment
6 System Insights from the Brain
References - AI Alignment and Social Choice: Fundamental
Limitations and Policy Implications / 2310.16048 / ISBN:https://doi.org/10.48550/arXiv.2310.16048 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Arrow-Sen Impossibility Theorems for RLHF
4 Implications for AI Governance and Policy
5 Conclusion
References - 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
II. Review Methodology
IV. Artificial Intelligence Embedded UAV
V. Challenges and Future Aspect on AI Enabled UAV
VI. Review Summary
VII. Conclusion
Authors Bios - 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
4 Equilibrium Alignment: A Prospective Paradigm for Ethical Value Alignmen
References - Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 The BvH and HK Definitions
4 The Causal Condition
5 The Epistemic Condition
6 Degree of Responsibility
7 Conclusion and Future Work
References
Appendix - 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
- Abstract
1 Introduction
4 Optimizing an Openness Metric in AI for Science
5 Why Openness in AI for Science
6 Conclusion and Future Work
Acknowledgements - 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 Ethics in Cybersecurity
Educational Challenges of Teaching AI Ethics in Cybersecurity and Core Ethical Principles
Technical Issues
AI tool-specific educational concerns
Broader educational preparedness for work in AI Cybersecurity
Conclusion
References - Human participants in AI research: Ethics and transparency in practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site
- III. Ethical Principles for AI Research with Human Participants
IV. Principles in Practice: Guidelines for AI Research with Human Participants
References - 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
2 A General Theory of Meaning
3 The Meaning Model
4 The Moral Model
5 Conclusion
A Supplementary Material
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
Introduction
Literature Review
Research questions
Conclusions
References - 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
- Abstract
2 Related Work
4 Evaluation
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
- Abstract
1 Introduction
2 Overview of Kantian Deontology
3 Measuring Fairness Metrics
4 Deontological AI Alignment
5 Aligning with Deontological Principles: Use Cases
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
- 2 Overview of ChatGPT and its capabilities
3 Transformers and pre-trained language models
4 Applications of ChatGPT in real-world scenarios
5 Advantages of ChatGPT in natural language processing
6 Limitations and potential challenges
7 Ethical considerations when using ChatGPT
9 Future directions for ChatGPT and natural language processing
10 Future directions for ChatGPT in vision domain
11 Conclusion
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
I. Introduction
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
Acknowledgements
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
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
II. Introduction
III. Prehistoric prompting: pre NN-era
IV. History of NLP between 2010 and 2015: the pre-attention mechanism era
VI. 2015: birth of the transformer
VIII. The third wave 2018: the rise of transformers
IX. 2019: THE YEAR OF CONTROL
X. 2020-2021: the rise of LLMS
XI. 2022-current: beyond language generation
XII. Conclusions
References - 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
2 Related work
3 Method
4 Findings
5 Discussion
References - 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
3 ReFLeCT: Robust, Fair, and Safe LLM Construction Test Suite
4 Empirical Evaluation and Outcomes
5 Conclusion
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
- I. Introduction
III. Safety
IV. Trust
V. Ethics
References - How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 Methodology
4 Experiments
5 Conclusion
Limitations
Ethical Considerations
References - 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
- 1 Introduction
2 UnknownBench: Evaluating LLMs on the Unknown
3 Experiments
References
E Prompt Templates - 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
5. Applications
6. Open chanllenges
7. Future Research Directions
8. Conclusion
References - Practical Cybersecurity Ethics: Mapping CyBOK to Ethical Concerns / 2311.10165 / ISBN:https://doi.org/10.48550/arXiv.2311.10165 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background
3 Methodology
4 Findings
5 Discussion
6 Limitations
References
A Ethics of the cyber security profession: interview guide - 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
Appendix A - What is an Algorithmic Harm? And a Bibliography
Appendix B – Common AI Harms as Described by EPIC10
Appendix C - List of General Harms Created by Digital Products Provided by Claude.AI - Case Repositories: Towards Case-Based Reasoning for AI Alignment / 2311.10934 / ISBN:https://doi.org/10.48550/arXiv.2311.10934 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Proposed Process
3 Related Work and Discussion
References - 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
5 Discussion and Recommendations
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
- Abstract
1 Introduction
2 Background
4 Findings
5 Discussion
References
A Overview of AIIA Instruments
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
- Abstract
II. Background
III. Approach: capturing and representing heuristics behind GPT's decision-making process
IV. Comparative results
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
What do RAI venues do?
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
- Abstract
I. Introduction
II. Education and LLMS
IV. LLM-empowered education
VI. Challenges and future directions
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
- Abstract
I. Introduction
II. Extent and impact of generative AI
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
- 1 Introduction
4 Results and Discussion
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
- Introduction
Results
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
- INTRODUCTION
OVERVIEW OF SOCIETAL BIASES IN GAI MODELS
ANALYTICAL FRAMEWORK
FINDINGS
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
1. Introduction
2. Pre-Deployment phase
4. Post-market surveillance phase
5. Conclusion
Bibliography - 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
7. Establishing responsible AI governance and oversight
10. Conclusion
11. References - 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
4. Discussion - 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
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
- Abstract
1 Introduction
2 Privacy and data protection
3 Transparency and explainability
4 Fairness and equity
5 Responsiblity, accountability, and regulations
6 Environmental impact
7 Conclusion
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
- Abstract
I. Introduction
IV. Societal implications
V. Technical defense mechanisms
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
- 3 Mapping Challenges throughout the Data Lifecycle
4 Lifecycle Approaches
References - From Lab to Field: Real-World Evaluation of an AI-Driven Smart Video Solution to Enhance Community Safety / 2312.02078 / ISBN:https://doi.org/10.48550/arXiv.2312.02078 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Related works
Applications and Visualizations
System Evaluation and Results
Conclusion
References - 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
2 Methodology
3 Results
References - 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
- 2. Research questions
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
- Abstract
1. Introduction
2. The pitfalls in detecting generative AI output
3. Detectors are not useful
4. Teach critical usage of AI
References - Intelligence Primer / 2008.07324 / ISBN:https://doi.org/10.48550/arXiv.2008.07324 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Human intelligence
3 Reasoning
6 Measuring intelligence
8 Consciousness
9 Augmenting human intelligence
10 Exceeding human intelligence
12 Large language models and Generative AI
15 Final thoughts
References - 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
References - Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site
- II. Background
III. Ethics: a primer
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
- Abstract
1 Introduction
2 Risks of Misuse for Artificial Intelligence in Science
3 Control the Risks of AI Models in Science
4 Call for Responsible AI for Science
5 Discussion
Appendix A Assessing the Risks of AI Misuse in Scientific Research
Appendix B Details of Risks Demonstration in Chemical Science
Appendix C Detailed Implementation of SciGuard
Appendix D Details of Benchmark Results - 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
- Abstract
...
Data Collection
Study 1: Geo-cultural Differences in Offensiveness
Study 2: Moral Foundations of Offensiveness
Study 3: Implications for Responsible AI
General Discussion
Geo-Cultural Factors
Moral Factors
References
A Appendix - The AI Assessment Scale (AIAS): A Framework for Ethical Integration of Generative AI in Educational Assessment / 2312.07086 / ISBN:https://doi.org/10.48550/arXiv.2312.07086 / Published by ArXiv / on (web) Publishing site
- Problematizing The View Of GenAI Content As Academic Misconduct
The AI Assessment Scale
Conclusion
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
- Introduction
Recommendations
References - 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
- Abstract
I. Introduction
II. Background and motivation
IV. Results
V. Discussion
VI. Conclusion and future work
References
Appendix A – Survey Questionnaire
Appendix B – Interview Questionnaire
Author’s Biographies - Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health / 2312.11803 / ISBN:https://doi.org/10.48550/arXiv.2312.11803 / Published by ArXiv / on (web) Publishing site
- 4 Results
References
A Extended Survey Results
B Extended Guiding Principles
C Full survey questions - 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
- Abstract
1 Introduction
2 The Reign of Algorithmic Fairness
3 Taking a Step Forward
5 Conclusion
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
- Abstract
1 Introduction
2 Related Work
References - Improving Task Instructions for Data Annotators: How Clear Rules and Higher Pay Increase Performance in Data Annotation in the AI Economy / 2312.14565 / ISBN:https://doi.org/10.48550/arXiv.2312.14565 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Theoretical background and hypotheses
III. Method
IV. Results
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
Experimental Study
Results
References - 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
- Abstract
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
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
- 2. LLMs in cognitive and behavioral psychology
3. LLMs in clinical and counseling psychology
5. LLMs in social and cultural psychology
7. Challenges and future directions
8. Conclusion - 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
- I. Introduction
IV. System design
V. Evaluation
VI. Discussion and future work
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
- Abstract
III. Methods
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
- Abstract
Materials and methods
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
II. Approaches for Resolving Trade-offs
References - 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
I Understanding bias - 2 Bias and moral framework in AI-based decision making
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
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
- Abstract
1 Introduction
2 Background
3 Method
4 Results
5 Discussion
6 Conclusion
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
- Abstract
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
- 3. Use cases representing different image data types and their challenges
and status for sharing
References - Beyond principlism: Practical strategies for ethical AI use in research practices / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site
- Abstract
1 The “Triple-Too” problem of AI ethics
2 A shift to user-centered realism in scientific contexts
3 Five specific goals and action-guiding strategies for ethical AI use in research practices
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
- Abstract
1 Introduction
2 Related work
3 Methods
4 RAI tool evaluation practices
5 Towards evaluation of RAI tool effectiveness
7 Conclusion
References
A List of RAI tools, with their primary publication
B RAI tools listed by target stage of AI development
C List of publications, with their associated RAI tools
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
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
- 1 Introduction
2 Networking research today
3 Beyond technical dimensions
4 Sense of engagement and responsibility
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
- 4. Findings
6. Conclusions, limitations, and future work
References - Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cubeà / 2402.01760 / ISBN:https://doi.org/10.48550/arXiv.2402.01760 / Published by ArXiv / on (web) Publishing site
- Abstract
2. Literature review
4. Discussion - 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
- 2 Establishing the novel aspect of AI as a crossover technology
3 Moral and ethical obligations when developing crossover AI technology - (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
3 Methods: case-based expert deliberation
4 Results
5 Discussion
6 Conclusion
References - 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
- 1 Introduction
2 Background
3 State of the practice
4 The POLARIS framework
5 POLARIS framework application
6 Limitations
7 Conclusion
References - Face Recognition: to Deploy or not to Deploy? A Framework for Assessing the Proportional Use of Face Recognition Systems in Real-World Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Background
3. Intervention models from other fields
4. Proposed framework
6. Compliance with International Regulations
7. 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
- Abstract
1 Introduction
2 Background
4 Challenges, Threats and Limitations
5 Findings
6 Discussion and Recommendations
8 Conclusion
A List of Included Studies
C Glossary of Terms
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
- Discussion
Reference
Appendix - 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
- Abstract
1. Introduction
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
- Abstract
1 Introduction
2 Related Work
3 Awareness in LLMs
4 Awareness Dataset: AWAREEVAL
5 Experiments
6 Conclusion
Limitation
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
- Abstract
3 Results
6 Conclusion
References
Appendix C - 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
4 Techniques of Human-Guided Training
5 Advantages of Human-Guided Training
6 Limitations
References - 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
3 Paradigm Shifts and New Trends
4 Current Taxonomy
5 Discussion and Future Research Directions
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
II. Background and Related Work
III. Unified Evaluation Framework For LLM Benchmarks
IV. Technological Aspects
V. Processual Elements
VI. Human Dynamics
VII. Discussions
References - Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications / 2402.12216 / ISBN:https://doi.org/10.48550/arXiv.2402.12216 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 The AIGC Copyright Dilemma: A What-if Analysis
5 Public Perception: A Survey Method
6 Implications and Recommendations
7 Conclusion
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
- 1. Introduction
2. Emergence of Free-Formed AI Collectives
3. Enhanced Performance of Free-Formed AI Collectives
4. Robustness of Free-Formed AI Collectives Against Risks
5. Open Challenges for Free-Formed AI Collectives
6. Conclusion
References
A. Cocktail Simulation
B. Sentence Making Simulation - 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
3 CosmoAgent Simulation Setting
4 CosmoAgent Architecture
6 Experimental Design
7 Results
A CosmoAgent Prompt
B Secretary Agent Prompt
References - 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
Introduction
Results
METRIC-framework for medical training data
Discussion
Methods
References - 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
2 The EU AI Act
3 There is no reliable AI regulation without a sound theory of human-AI interaction
4 There is no trustworthy AI without HCI
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
- Abstract
1 Introduction
2 Background
3 Materials and Methods
5 Results
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
- 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
VI. AI and Learning Algorithms Statistics for Autonomous Vehicles
VII. Conclusion
References - 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
- 1 Introduction
2 The Suitability of Generative AI for Newsroom Tasks
References - 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
4. Results
5. Discussion
6. Conclusion
References - 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
- Abstract
1 Introduction
2 Background and Related Work
3 Methodology
4 Results
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
- 1 Motivation & Background
References - The Minimum Information about CLinical Artificial Intelligence Checklist for Generative Modeling Research (MI-CLAIM-GEN) / 2403.02558 / ISBN:https://doi.org/10.48550/arXiv.2403.02558 / Published by ArXiv / on (web) Publishing site
- Part 2. A new train-test split for prompt development and few-shot learning
Part 4. Model evaluation
Part 5. Interpretability of generative models
Table 1. Updated MI-CLAIM checklist for generative AI clinical studies.
References - Towards an AI-Enhanced Cyber Threat Intelligence Processing Pipeline / 2403.03265 / ISBN:https://doi.org/10.48550/arXiv.2403.03265 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction & Motivation
II. Background & Literature Review
III. The AI-Enhanced CTI Processing Pipeline
IV. Challenges and Considerations
V. Conclusions & Future Research
References
Authors - A Survey on Human-AI Teaming with Large Pre-Trained Models / 2403.04931 / ISBN:https://doi.org/10.48550/arXiv.2403.04931 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 AI Model Improvements with Human-AI Teaming
3 Effective Human-AI Joint Systems
4 Safe, Secure and Trustworthy AI
5 Applications
6 Conclusion
References - 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
- 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
- References
- 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
- 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
- A Internal Thoughts
B Baseline Setup
C Prompt Templates
D More Results - 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
- 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
- Abstract
1. Introduction
2. What is AGI
3. The Potentials of AGI in Transforming Future Education
4. Ethical Issues and Concerns
5. Discussion
References - Moral Sparks in Social Media Narratives / 2310.19268 / ISBN:https://doi.org/10.48550/arXiv.2310.19268 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
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
2. Research Methodology
3. Analysis
4. Discussion
References - 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
- Abstract
1 Introduction
2 Related Work
3 Problem Statement
4 Informational Fairness
5 Representational Fairness
6 Ethics and Morality
7 Use Cases and Applications
8 Conclusion
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
2 Theoretical Background
4 Results of the Systematic Literature Review
5 Towards Privacy- and Security-Aware Framework for Ethical AI
References - 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
3 Cyber Offense
4 Cyber Defence
5 Implications of Generative AI in Social, Legal, and Ethical Domains
References - 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
1 Introduction
2 Related Work
3 Method
4 Experiment
5 Conclusion & Future Work - 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
- Abstract
1. Introduction
2. Methodology
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
- Abstract
Introduction
Method
Results
AI Ethics Development Phases Based on Keyword Analysis
Key AI Ethics Issues
Limitations and Conclusion
References
Authors bios - 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
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
5 Risk
6 Bias and Fairness
7 Explainable AI as an Enabler of Trustworthy AI
8 Implementation Framework
9 A Few Suggestions for a Viable Path Forward
10 Summary and Next Steps
A Appendix
References - 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
- Abstract
Introduction
Various AI Ethical Concerns
A Possible Solution to These Concerns With Business Self-Regulation
Feasibility of Business Self-Regulation
A Possible Solution to These Concerns With Government Regulation
Feasibility of Government Regulation
Conclusion
References - The Pursuit of Fairness in Artificial Intelligence Models A Survey / 2403.17333 / ISBN:https://doi.org/10.48550/arXiv.2403.17333 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Survey
3 Conceptualizing Fairness and Bias in ML
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 - 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
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
2 Methods
3 RQ1: What Factors Influence Members’ “Licens to Critique” when Discussing AI Ethics with their Team?
4 RQ2: How Do AI Ethics Discussions Unfold while Playing a Game Oriented toward Speculative Critique?
5 Discussion
6 Conclusion
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
- Abstract
1 Introduction
2 Non-discrimination law vs. algorithmic fairness
3 Implications of the AI Act
4 Practical challenges for compliance
5 Conclusion
References - 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
6. Large Language Models (LLMs) - Introduction
7. Artificial intelligence Liability
9. References - 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
- 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
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
- 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
7 Model Evaluation and Benchmarking
8 Conclusions
References - 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
- Abstract
I. Introduction
II. Background and Related Work
III. Study Design
IV. Results
V. Discussion
VII. Conclusion
References - 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
- 3 Method
4 Findings
5 Discussion
References - 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
- I. Introduction
III. Proposed Design: IBIS
References - Frontier AI Ethics: Anticipating and Evaluating the Societal Impacts of Language Model Agents / 2404.06750 / ISBN:https://arxiv.org/abs/2404.06750 / Published by ArXiv / on (web) Publishing site
- Introduction
A Primer
Rebooting Machine Ethics
Language Model Agents in Society
References - 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
- Bibliography
- 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
- A Critical Survey on Fairness Benefits of Explainable AI / 2310.13007 / ISBN:https://doi.org/10.1145/3630106.3658990 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background
3 Methodology
4 Critical Survey
5 Three Patterns of Critique
6 Conclusion and Outlook
References
A Methodologies of Surveyed Literature - AI Alignment: A Comprehensive Survey / 2310.19852 / ISBN:https://doi.org/10.48550/arXiv.2310.19852 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Learning from Feedback
3 Learning under Distribution Shift
4 Assurance
5 Governance
6 Conclusion
References - Regulating AI-Based Remote Biometric Identification. Investigating the Public Demand for Bans, Audits, and Public Database Registrations / 2401.13605 / ISBN:https://doi.org/10.48550/arXiv.2401.13605 / Published by ArXiv / on (web) Publishing site
- Abstract
2 The Need for Governance of AI
3 Remote Biometric Identification and the AI Act
4 Public Opinion on AI Governance
5 Research Questions
6 Results
7 Discussion
8 Conclusion
Ethics Statement
References - Generative Ghosts: Anticipating Benefits and Risks of AI Afterlives / 2402.01662 / ISBN:https://doi.org/10.48550/arXiv.2402.01662 / Published by ArXiv / on (web) Publishing site
- 4 Benefits and Risks of Generative Ghost
References - Epistemic Power in AI Ethics Labor: Legitimizing Located Complaints / 2402.08171 / ISBN:https://doi.org/10.1145/3630106.3658973 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 Automated Model Cards: Legitimacy via Quantified Objectivity
4 Grey Skin as Technofix: Failures to Lodge Located Complaints
6 Conclusions: Towards Humble Technical Practices
References - On the role of ethics and sustainability in business innovation / 2404.07678 / ISBN:https://doi.org/10.48550/arXiv.2404.07678 / Published by ArXiv / on (web) Publishing site
- Background
Ethical considera5ons
Sustainability considera5ons
Recommenda5ons
Conclusion
About the authors - PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Models / 2404.08699 / ISBN:https://doi.org/10.48550/arXiv.2404.08699 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background and Related Work
3 Methodology
5 Conclusion
References - Detecting AI Generated Text Based on NLP and Machine Learning Approaches / 2404.10032 / ISBN:https://doi.org/10.48550/arXiv.2404.10032 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Literature Review
IV. Results and Discussion - Debunking Robot Rights Metaphysically, Ethically, and Legally / 2404.10072 / ISBN:https://doi.org/10.48550/arXiv.2404.10072 / Published by ArXiv / on (web) Publishing site
- 3 The Robots at Issue
4 The Machines Like us Argument: Mistaking the Map for the Territory
5 Embodied Enactive (Post-Cartesian) Perspectives on Cognition
6 Posthumanism
7 The Legal Perspective
8 The Troubling Implications of Legal Rationales for Robot Rights
9 The Enduring Irresponsibility of AI Rights Talk
Notes
References - Characterizing and modeling harms from interactions with design patterns in AI interfaces / 2404.11370 / ISBN:https://doi.org/10.48550/arXiv.2404.11370 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Scoping Review of Design Patterns, Affordances, and Harms in AI Interfaces
6 Discussion
References - Taxonomy to Regulation: A (Geo)Political Taxonomy for AI Risks and Regulatory Measures in the EU AI Act / 2404.11476 / ISBN:https://doi.org/10.48550/arXiv.2404.11476 / Published by ArXiv / on (web) Publishing site
- 2 EU Public Policy Analysis
3 A Geo-Political AI Risk Taxonomy
4 European Union Artificial Intelligence Act
References - Just Like Me: The Role of Opinions and Personal Experiences in The Perception of Explanations in Subjective Decision-Making / 2404.12558 / ISBN:https://doi.org/10.48550/arXiv.2404.12558 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Method
3 Results
4 Discussin and Implications
References - Large Language Model Supply Chain: A Research Agenda / 2404.12736 / ISBN:https://doi.org/10.48550/arXiv.2404.12736 / Published by ArXiv / on (web) Publishing site
- Abstract
3 LLM Infrastructure
4 LLM Lifecycle
5 Downstream Ecosystem
References - The Necessity of AI Audit Standards Boards / 2404.13060 / ISBN:https://doi.org/10.48550/arXiv.2404.13060 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Audit the process, not just the product
3 3 Governance for safety
4 4 Auditing standards body, not standard audits
References - Modeling Emotions and Ethics with Large Language Models / 2404.13071 / ISBN:https://doi.org/10.48550/arXiv.2404.13071 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Qualifying and Quantifying Emotions
3 Case Study #1: Linguistic Features of Emotion
4 Qualifying and Quantifying Ethics
Appendix A
References - From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap / 2404.13131 / ISBN:https://doi.org/10.1145/3630106.3658951 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Disentangling Replicability of Model Performance Claiim and Replicability of Social Claim
3 How Claim Replicability Helps Bridge the Responsiblity Gap
4 Claim Replicability's Practical Implication
References - A Practical Multilevel Governance Framework for Autonomous and Intelligent Systems / 2404.13719 / ISBN:https://doi.org/10.48550/arXiv.2404.13719 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Comprehensive Governance of Emerging Technologies
III. A Practical Multilevel Governance Framework for AIs
IV. Application of the Framework for the Development of AIs
References - Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis / 2404.13861 / ISBN:https://doi.org/10.48550/arXiv.2404.13861 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Alternatives to AI as Agent
References - Designing Safe and Engaging AI Experiences for Children: Towards the Definition of Best Practices in UI/UX Design / 2404.14218 / ISBN:https://doi.org/10.48550/arXiv.2404.14218 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 Best Practices for AI UI/UX Design for Children
4 Metrics for Assessing Trustworthiness, Reliability, and Safety in Human-AI Interaction
5 Conclusion
References - AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance / 2404.14660 / ISBN:https://doi.org/10.48550/arXiv.2404.14660 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Technical assessments require an AI expert to complete — and we don’t have enough experts - Who Followed the Blueprint? Analyzing the Responses of U.S. Federal Agencies to the Blueprint for an AI Bill of Rights / 2404.19076 / ISBN:https://doi.org/10.48550/arXiv.2404.19076 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Findings
Conclusion - Fairness in AI: challenges in bridging the gap between algorithms and law / 2404.19371 / ISBN:https://doi.org/10.48550/arXiv.2404.19371 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Discrimination in Law
III. Prevalent Algorithmic Fairness Definitions
IV. Criteria for the Selection of Fairness Methods
V. Discussion
References - War Elephants: Rethinking Combat AI and Human Oversight / 2404.19573 / ISBN:https://doi.org/10.48550/arXiv.2404.19573 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background
4 Discussion
5 Conclusions - Not a Swiss Army Knife: Academics' Perceptions of Trade-Offs Around Generative Artificial Intelligence Use / 2405.00995 / ISBN:https://doi.org/10.48550/arXiv.2405.00995 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 Method
4 Findings
5 Discussion
7 Conclusion
References - Towards an Ethical and Inclusive Implementation of Artificial Intelligence in Organizations: A Multidimensional Framework / 2405.01697 / ISBN:https://doi.org/10.48550/arXiv.2405.01697 / Published by ArXiv / on (web) Publishing site
- 1 Technocriticism and Key Actors in the Age of
AI
2 How can organizations participate
3 Four Pillars for Implementing an Ethical Framework in Organizations
4 Conclusions - A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law / 2405.01769 / ISBN:https://doi.org/10.48550/arXiv.2405.01769 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Surveys
3 Finance
4 Medicine and Healthcar
5 Law
6 Ethics
7 Conclusion
References - AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research / 2405.01859 / ISBN:https://doi.org/10.48550/arXiv.2405.01859 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
3. AWS Proliferation and Threats to Academic Research
4. Policy Recommendations
Impact Statement
References - Responsible AI: Portraits with Intelligent Bibliometrics / 2405.02846 / ISBN:https://doi.org/10.48550/arXiv.2405.02846 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Conceptualization: Responsible AI
IV. Bibliometric Portraits of Responsible AI
References - Exploring the Potential of the Large Language Models (LLMs) in Identifying Misleading News Headlines / 2405.03153 / ISBN:https://doi.org/10.48550/arXiv.2405.03153 / Published by ArXiv / on (web) Publishing site
- Abstract
2 Related Work
3 Method
4 Results
5 Discussion - Organizing a Society of Language Models: Structures and Mechanisms for Enhanced Collective Intelligence / 2405.03825 / ISBN:https://doi.org/10.48550/arXiv.2405.03825 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Motivation
3 Proposed Organizational Forms
4 Interaction Mechanisms
5 Governance and Organization
6 Unified Legal Framework
7 Conclusion - A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI / 2405.04333 / ISBN:https://doi.org/10.48550/arXiv.2405.04333 / Published by ArXiv / on (web) Publishing site
- Glossary of Terms
Executive Summary
1. Introduction
3. A Spectrum of Scenarios of Open Data for Generative AI
4. Open Data Requirements And Diagnostic
5. Recommendations for Advancing Open Data in Generative AI
Appendix - Guiding the Way: A Comprehensive Examination of AI Guidelines in Global Media / 2405.04706 / ISBN:https://doi.org/10.48550/arXiv.2405.04706 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Theoretical Framework
3 Data and Methods
4 Results
5 Discussion and conclusions
References - Trustworthy AI-Generative Content in Intelligent 6G Network: Adversarial, Privacy, and Fairness / 2405.05930 / ISBN:https://doi.org/10.48550/arXiv.2405.05930 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Trustworthy AIGC in 6G Network
V. Fairness of AIGC in 6G Network
VI. Case Study
VII. Challenges and Future Research Directions
VIII. Conclusion
References - Towards ethical multimodal systems / 2304.13765 / ISBN:https://doi.org/10.48550/arXiv.2304.13765 / Published by ArXiv / on (web) Publishing site
- References
- RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical Roles / 2307.15158 / ISBN:https://doi.org/10.48550/arXiv.2307.15158 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
4 Method for Generating Responsible AI Guidelines
5 Evaluation of the 22 Responsible AI Guidelines
6 Discussion
7 Conclusion
References
A Additional Materials for the User Study
B Mapping Guidelines with EU AI Act Articles - Redefining Qualitative Analysis in the AI Era: Utilizing ChatGPT for Efficient Thematic Analysis / 2309.10771 / ISBN:https://doi.org/10.48550/arXiv.2309.10771 / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
4 Users’ Experiences and Challenges with ChatGPT
5 Analyses of the Design Process
7 Discussion
References - XXAI: Towards eXplicitly eXplainable Artificial Intelligence / 2401.03093 / ISBN:https://doi.org/10.48550/arXiv.2401.03093 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
3. Overcoming the barriers to widespread use of symbolic AI
4. Discussion of the problems of symbolic AI and ways to overcome them
5. Conclusions and prospects
References - Should agentic conversational AI change how we think about ethics? Characterising an interactional ethics centred on respect / 2401.09082 / ISBN:https://doi.org/10.48550/arXiv.2401.09082 / Published by ArXiv / on (web) Publishing site
- Introduction
Evaluating a system as a social actor
Social-interactional harms
References - Unsocial Intelligence: an Investigation of the Assumptions of AGI Discourse / 2401.13142 / ISBN:https://doi.org/10.48550/arXiv.2401.13142 / Published by ArXiv / on (web) Publishing site
- 2 Between Human Intelligence and Technology: AGI’s Dual Value-Laden Pedigrees
3 The Motley Choices of AGI Discourse
4 Towards Contextualized, Politically Legitimate, and Social Intelligence
5 Conclusion: Politically Legitimate Intelligence
References
A Dimensions of AGI: a Summary - Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators / 2402.01708 / ISBN:https://doi.org/10.48550/arXiv.2402.01708 / Published by ArXiv / on (web) Publishing site
- 3 Overview of Speech Generation
6 Taxonomy of Harms
7 Discussion
References
A Appendix - The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative / 2402.14859 / ISBN:https://doi.org/10.48550/arXiv.2402.14859 / Published by ArXiv / on (web) Publishing site
- 3. Methodology
4. Experiments
References - Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback / 2404.10271 / ISBN:https://doi.org/10.48550/arXiv.2404.10271 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Background
3. What Are the Collective Decision Problems and their Alternatives in this Context?
5. What Is the Format of Human Feedback?
7. Which Traditional Social-Choice-Theoretic Concepts Are Most Relevant?
References - A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs) / 2405.03066 / ISBN:https://doi.org/10.48550/arXiv.2405.03066 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Materials
3 Results
4 Discussion
References - Integrating Emotional and Linguistic Models for Ethical Compliance in Large Language Models / 2405.07076 / ISBN:https://doi.org/10.48550/arXiv.2405.07076 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
3 Quantitative Models of Emotions, Behaviors, and Ethics
4 Pilot Studies
5 Conclusion
References
Appendix S: Multiple Adversarial LLMs
Appendix B: Polarized Emotions in One Article
Appendix C: Z. Sayre to F. S. Fitzgerald w/ Mixed Emotions
Appendix D: Complex Emotions
Appendix E: “To My Sister” of Different Linguistic Behaviors
Appendix H: Instruction to Human Annotators - Using ChatGPT for Thematic Analysis / 2405.08828 / ISBN:https://doi.org/10.48550/arXiv.2405.08828 / Published by ArXiv / on (web) Publishing site
- 2 Coding in Thematic Analysis: Manual vs GPT-driven Approaches
3 Pilot-testing: UN Policy Documents Thematic Analysis Supported by GPT
5 Discussion and Limitations
6 OpenAI Updates on Policies and Model Capabilities: Implications for Thematic Analysis
9 Appendix
References - When AI Eats Itself: On the Caveats of Data Pollution in the Era of Generative AI / 2405.09597 / ISBN:https://doi.org/10.48550/arXiv.2405.09597 / Published by ArXiv / on (web) Publishing site
- 2 RQ1: What Happens When AI Eats Itself ?
3 RQ2: What Technical Strategies Can Be Employed to Mitigate the Negative Consequences of AI Autophagy?
5 Conclusions and Outlook - Cyber Risks of Machine Translation Critical Errors : Arabic Mental Health Tweets as a Case Study / 2405.11668 / ISBN:https://doi.org/10.48550/arXiv.2405.11668 / Published by ArXiv / on (web) Publishing site
- 1.
Introduction
3. Data Compiling and Annotation
6. Conclusion - The Narrow Depth and Breadth of Corporate Responsible AI Research / 2405.12193 / ISBN:https://doi.org/10.48550/arXiv.2405.12193 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Motivations for Industry to Engage in Responsible AI Research
4 The Narrow Depth of Industry’s Responsible AI Research
5 The Narrow Breadth of Industry’s Responsible AI Research
7 Discussion
References
S1 Additional Analyses on Engagement Analysis
S2 Additional Analyses on Linguistic Analysis - Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems / 2405.13191 / ISBN:https://doi.org/10.48550/arXiv.2405.13191 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
3 The Audit Procedure
4 Conducting the Pilots
References
B The Different Types of Auditing - A Comprehensive Overview of Large Language Models (LLMs) for Cyber Defences: Opportunities and Directions / 2405.14487 / ISBN:https://doi.org/10.48550/arXiv.2405.14487 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Threat Intelligence
III. Vulnerability Assessment
IV. Network Security
V. Privacy Preservation
VI. Awareness
VII. Cyber Security Operations Automation
VIII. Ethical LLMs
IX. Challenges and Open Problems
X. Conclusions
References - Towards Clinical AI Fairness: Filling Gaps in the Puzzle / 2405.17921 / ISBN:https://doi.org/10.48550/arXiv.2405.17921 / Published by ArXiv / on (web) Publishing site
- Abstract
Main
Results
Methods in clinical AI fairness research
Discussion
Conclusion
Methods
Reference
Additional material - The Future of Child Development in the AI Era. Cross-Disciplinary Perspectives Between AI and Child Development Experts / 2405.19275 / ISBN:https://doi.org/10.48550/arXiv.2405.19275 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Anticipated AI Use for Children
3. Discussion
Bibliography
Appendix 1: Experts Consulted & Acknowledgements - Using Large Language Models for Humanitarian Frontline Negotiation: Opportunities and Considerations / 2405.20195 / ISBN:https://doi.org/10.48550/arXiv.2405.20195 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
3. Method
5. Interview Results: Opportunities and Concerns of Using LLMs in the Frontline
6. Discussion
A. Appendix - There and Back Again: The AI Alignment Paradox / 2405.20806 / ISBN:https://doi.org/10.48550/arXiv.2405.20806 / Published by ArXiv / on (web) Publishing site
- Abstract
Paper
References - Responsible AI for Earth Observation / 2405.20868 / ISBN:https://doi.org/10.48550/arXiv.2405.20868 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Mitigating (Unfair) Bias
3 Secure AI in EO: Focusing on Defense Mechanisms, Uncertainty Modeling and Explainability
5 Maintaining Scientific Excellence, Open Data, and Guiding AI Usage Based on Ethical Principles in EO
6 AI&EO for Social Good
7 Responsible AI Integration in Business Innovation and Sustainability
8 Conclusions, Remarks and Future Directions
References - Gender Bias Detection in Court Decisions: A Brazilian Case Study / 2406.00393 / ISBN:https://doi.org/10.48550/arXiv.2406.00393 / Published by ArXiv / on (web) Publishing site
- Abstract
3 Framework
References
A DVC Dataset: Domestic Violence Cases
C Biases - Transforming Computer Security and Public Trust Through the Exploration of Fine-Tuning Large Language Models / 2406.00628 / ISBN:https://doi.org/10.48550/arXiv.2406.00628 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background, Foundational Studies, and Discussion:
3 Experimental Design, Overview, and Discussion
4 Comparative Analysis of Pre-Trained Models.
5 Discussion and further research - How Ethical Should AI Be? How AI Alignment Shapes the Risk Preferences of LLMs / 2406.01168 / ISBN:https://doi.org/10.48550/arXiv.2406.01168 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
I. Description of Method/Empirical Design
II. Risk Characteristics of LLMs
III. Impact of Alignment on LLMs’ Risk Preferences
IV. Impact of Alignments on Corporate Investment Forecasts
Figures and tables - Evaluating AI fairness in credit scoring with the BRIO tool / 2406.03292 / ISBN:https://doi.org/10.48550/arXiv.2406.03292 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Preliminary Analysis
3 ML model construction
4 Fairness violation analysis in BRIO
5 Risk assessment in BRIO
6 Risk analysis via BRIO for the German Credit Dataset
7 Revenue analysis
8 Conclusions
References - Promoting Fairness and Diversity in Speech Datasets for Mental Health and Neurological Disorders Research / 2406.04116 / ISBN:https://doi.org/10.48550/arXiv.2406.04116 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
3. Related Work
4. Desiderata
5. Methodology
6. Discussion
7. Conclusions
References
Appendix A. Terminology - MoralBench: Moral Evaluation of LLMs / 2406.04428 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
3 Benchmark and Method
4 Experiments
References
Appendix - Can Prompt Modifiers Control Bias? A Comparative Analysis of Text-to-Image Generative Models / 2406.05602 / Published by ArXiv / on (web) Publishing site
- 2. Related Work
3. Bias Evaluation
6. Discussion
7. Conclusion
References - Deception Analysis with Artificial Intelligence: An Interdisciplinary Perspective / 2406.05724 / ISBN:https://doi.org/10.48550/arXiv.2406.05724 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Reductionism & Previous Research in Deceptive AI
4 DAMAS: A MAS Framework for Deception Analysis
References - The Impact of AI on Academic Research and Publishing / 2406.06009 / Published by ArXiv / on (web) Publishing site
- References
- An Empirical Design Justice Approach to Identifying Ethical Considerations in the Intersection of Large Language Models and Social Robotics / 2406.06400 / ISBN:https://doi.org/10.48550/arXiv.2406.06400 / Published by ArXiv / on (web) Publishing site
- 3 Methodology
4 Findings
5 Discussion
References
Appendix A: Interview questions - The Ethics of Interaction: Mitigating Security Threats in LLMs / 2401.12273 / ISBN:https://doi.org/10.48550/arXiv.2401.12273 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Why Ethics Matter in LLM Attacks?
6 Ethical Response to LLM Attacks
References - Global AI Governance in Healthcare: A Cross-Jurisdictional Regulatory Analysis / 2406.08695 / ISBN:https://doi.org/10.48550/arXiv.2406.08695 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
5 Generative AI: The New Frontier
6 Results and Conclusion
7 Future Directions
References
A Supplemental Tables - Fair by design: A sociotechnical approach to justifying the fairness of AI-enabled systems across the lifecycle / 2406.09029 / ISBN:https://doi.org/10.48550/arXiv.2406.09029 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Fairness and AI
3 Assuring fairness across the AI lifecycle
4 Assuring AI fairness in healthcare
5 Conclusion
References - Some things never change: how far generative AI can really change software engineering practice / 2406.09725 / ISBN:https://doi.org/10.48550/arXiv.2406.09725 / Published by ArXiv / on (web) Publishing site
- 3 Methodology
4 Results - Federated Learning driven Large Language Models for Swarm Intelligence: A Survey / 2406.09831 / ISBN:https://doi.org/10.48550/arXiv.2406.09831 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Foundations and Integration of SI and LLM
III. Federated LLMs for Smarm Intelligence
IV. Learned Lessons and Open Challenges - Applications of Generative AI in Healthcare: algorithmic, ethical, legal and societal considerations / 2406.10632 / ISBN:https://doi.org/10.48550/arXiv.2406.10632 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Selection of application
III. Analysis
References
Aappendix A Societal aspects
Appendix B Legal aspects
Appendix C Algorithmic / technical aspects - Justice in Healthcare Artificial Intelligence in Africa / 2406.10653 / ISBN:https://doi.org/10.48550/arXiv.2406.10653 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
1. Beyond Bias and Fairness
2. Bridging the Justice Gap
3. Ensuring Equitable Access to AI Technologies
4. Prioritizing the Common Good Over Corporate Greed
5. Promoting Global Solidarity
6. Ensuring Sustainable AI Development
7. Addressing Bias and Enforcing Fairness
Conclusion
References - Conversational Agents as Catalysts for Critical Thinking: Challenging Design Fixation in Group Design / 2406.11125 / ISBN:https://doi.org/10.48550/arXiv.2406.11125 / Published by ArXiv / on (web) Publishing site
- 1 INTRODUCTION
3 CHALLENGES AND OPPORTUNITIES OF USING CONVERSATIONAL AGENTS IN GROUP DESIGN
4 POTENTIAL SCENARIO AND APPLICATIONS OF CONVERSATIONAL AGENTS IN GROUP DESIGN PROCESS
5 BALANCING CRITICAL THINKING WITH DESIGNER SATISFACTION AND MOTIVATION
6 POTENTIAL DESIGN CONSIDERATIONS
REFERENCES - Current state of LLM Risks and AI Guardrails / 2406.12934 / ISBN:https://doi.org/10.48550/arXiv.2406.12934 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Large Language Model Risks
3 Strategies in Securing Large Language models
4 Challenges in Implementing Guardrails
5 Open Source Tools
7 Conclusion
References - Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Health / 2406.13659 / ISBN:https://doi.org/10.48550/arXiv.2406.13659 / Published by ArXiv / on (web) Publishing site
- I. INTRODUCTION
II. RECENT ADVANCEMENTS IN LARGE LANGUAGE MODELS
III. CASE STUDIES : APPLICATIONS OF LLM S IN PATIENT ENGAGEMENT
IV. DISCUSSION AND F UTURE D IRECTIONS
V. CONCLUSION
REFERENCES - Documenting Ethical Considerations in Open Source AI Models / 2406.18071 / ISBN:https://doi.org/10.48550/arXiv.2406.18071 / Published by ArXiv / on (web) Publishing site
- 1 INTRODUCTION
2 RELATED WORK
3 METHODOLOGY AND STUDY DESIGN
4 RESULTS
5 DISCUSSION AND IMPLICATIONS
6 THREATS TO VALIDITY
REFERENCES - AI Alignment through Reinforcement Learning from Human Feedback? Contradictions and Limitations / 2406.18346 / ISBN:https://doi.org/10.48550/arXiv.2406.18346 / Published by ArXiv / on (web) Publishing site
- Abstract
2 Background
3 Limitations of RLxF
4 The Internal Tensions and Ethical Issues in RLxF
5 Rebooting Safety and Alignment: Integrating AI Ethics and System Safety
6 Conclusion
References - A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics / 2406.18812 / ISBN:https://doi.org/10.48550/arXiv.2406.18812 / Published by ArXiv / on (web) Publishing site
- Abstract
I. INTRODUCTION AND MOTIVATION
IV. DT-INTEGRATED ROBOTICS DESIGN CONSIDERATIONS AND DISCUSSION
V. CONCLUSION
REFERENCES - Staying vigilant in the Age of AI: From content generation to content authentication / 2407.00922 / ISBN:https://doi.org/10.48550/arXiv.2407.00922 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Art Practice: Human Reactions to Synthetic Fake Content
Prospective Usage: Assessing Veracity in Everyday Content
Conclusions and Future Works
References - SecGenAI: Enhancing Security of Cloud-based Generative AI Applications within Australian Critical Technologies of National Interest / 2407.01110 / ISBN:https://doi.org/10.48550/arXiv.2407.01110 / Published by ArXiv / on (web) Publishing site
- Abstract
III. CRITICAL ANALYSIS
IV. SECGENAI FRAMEWORK REQUIREMENTS SPECIFICATIONS
V. DISCUSSIONS AND RECOMMENDATIONS
VII. ACKNOWLEDGEMENTS
REFERENCES - Artificial intelligence, rationalization, and the limits of control in the public sector: the case of tax policy optimization / 2407.05336 / ISBN:https://doi.org/10.48550/arXiv.2407.05336 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Artificial intelligence as Weberian rationalization
3. Bureaucratization, tax policy, and equality
4. AI-driven tax policy to reduce economic inequality: a thought experiment
5. Freedom, equality, and self-determination in the iron cage
6. Conclusion
References - A Blueprint for Auditing Generative AI / 2407.05338 / ISBN:https://doi.org/10.48550/arXiv.2407.05338 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Why audit generative AI systems?
3 How to audit generative AI systems?
4 Governance audits
5 Model audits
7 Clarifications and limitations
8 Conclusion
Bibliography - Challenges and Best Practices in Corporate AI Governance:Lessons from the Biopharmaceutical Industry / 2407.05339 / ISBN:https://doi.org/10.48550/arXiv.2407.05339 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction | The need for corporate AI governance
2 Case study | AstraZeneca’s AI governance journey
3 Practical implementation challenges | What to be prepared for?
4 Discussion | Best practices and lessons learned
5 Concluding remarks | Upfront investments vs. long-term benefits
6 References - Operationalising AI governance through ethics-based auditing: An industry case study / 2407.06232 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. The need to operationalise AI governance
3. AstraZeneca and AI governance
4. An ‘ethics-based’ AI audit
5. Methodology: An industry case study
6. Lessons learned from AstraZeneca’s 2021 AI audit
8. Conclusions
REFERENCES - Auditing of AI: Legal, Ethical and Technical Approaches / 2407.06235 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 The evolution of auditing as a governance mechanism
3 The need to audit AI systems – a confluence of top-down and bottom-up pressures
4 Auditing of AI’s multidisciplinary foundations
5 In this topical collection
6 Concluding remarks
References - Why should we ever automate moral decision making? / 2407.07671 / ISBN:https://doi.org/10.48550/arXiv.2407.07671 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Reasons for automated moral decision making - 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
- D. Results for Claude 3
- 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
- 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
- REFERENCES
- 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
- REFERENCES:
Table 1
Table 2 - 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
- A Details of Datasets
B Details of Instructions
C Experimental Details - Bridging the Global Divide in AI Regulation: A Proposal for a Contextual, Coherent, and Commensurable Framework / 2303.11196 / ISBN:https://doi.org/10.48550/arXiv.2303.11196 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Global Divide in AI Regulation: Horizontally. Context-Specific
III. Striking a Balance Betweeen the Two Approaches
IV. Proposing an Alternative 3C Framework - CogErgLLM: Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics / 2407.02885 / ISBN:https://doi.org/10.48550/arXiv.2407.02885 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background
3 Conceptual Foundations
4 Design Framework
6 Discussion
Notes - Past, Present, and Future: A Survey of The Evolution of Affective Robotics For Well-being / 2407.02957 / ISBN:https://doi.org/10.48550/arXiv.2407.02957 / Published by ArXiv / on (web) Publishing site
- I. Introduction
III. Method
IV. Evolution of Affective Robots for Well-Being
V. 10 Years of Affectivbe Robotics
VI. Future Opportunities in Affective Robotivs for Well-Being - With Great Power Comes Great Responsibility: The Role of Software Engineers / 2407.08823 / ISBN:https://doi.org/10.48550/arXiv.2407.08823 / Published by ArXiv / on (web) Publishing site
- 2 Background and Related Work
3 Future Research Challenges
References - Have We Reached AGI? Comparing ChatGPT, Claude, and Gemini to Human Literacy and Education Benchmarks / 2407.09573 / ISBN:https://doi.org/10.48550/arXiv.2407.09573 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Literature Review
3 Methodology
5 Discussion
6 Conclusion - Generative AI for Health Technology Assessment: Opportunities, Challenges, and Policy Considerations / 2407.11054 / ISBN:https://doi.org/10.48550/arXiv.2407.11054 / Published by ArXiv / on (web) Publishing site
- Applications of generative AI to health economic modeling
Limitations of generative AI in HTA applications
Policy landscape
References - Thorns and Algorithms: Navigating Generative AI Challenges Inspired by Giraffes and Acacias / 2407.11360 / ISBN:https://doi.org/10.48550/arXiv.2407.11360 / Published by ArXiv / on (web) Publishing site
- Abstract
4 Generative AI and Humans: Risks and Mitigation
5 Meta Analysis: Limits of the Analogy
6 Discussion
7 Recommendations: Fixing Gen AI’s Value Alignment
8 Conclusion
References - Prioritizing High-Consequence Biological Capabilities in Evaluations of Artificial Intelligence Models / 2407.13059 / ISBN:https://doi.org/10.48550/arXiv.2407.13059 / Published by ArXiv / on (web) Publishing site
- Introduction
Proposed Approach to Determining High-Consequence Biological Capabilities of Concern
Next Steps for AI Biosecurity Evaluations
References - Report on the Conference on Ethical and Responsible Design in the National AI Institutes: A Summary of Challenges / 2407.13926 / ISBN:https://doi.org/10.48550/arXiv.2407.13926 / Published by ArXiv / on (web) Publishing site
- 2. Ethics Frameworks
3. AI Institutes and Society
4. Coordination between AI Institutes - Assurance of AI Systems From a Dependability Perspective / 2407.13948 / ISBN:https://doi.org/10.48550/arXiv.2407.13948 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction: Assurance for Traditional Systems
2 Assurance for Systems Extended with AI and ML
3 Assurance of AI Systems for Specific Functions
4 Assurance for General-Purpose AI
5 Assurance and Alignment for AGI
6 Summary and Conclusion
References - Open Artificial Knowledge / 2407.14371 / ISBN:https://doi.org/10.48550/arXiv.2407.14371 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Key Challenges of Artificial Data
3. OAK Dataset
4. Automatic Prompt Generation
Appendices - Honest Computing: Achieving demonstrable data lineage and provenance for driving data and process-sensitive policies / 2407.14390 / ISBN:https://doi.org/10.48550/arXiv.2407.14390 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Threat Model for Honest Computing
3. Honest Computing reference specifications
4. Discussion
5. Conclusion
References - RogueGPT: dis-ethical tuning transforms ChatGPT4 into a Rogue AI in 158 Words / 2407.15009 / ISBN:https://doi.org/10.48550/arXiv.2407.15009 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Background
IV. Results
References - Nudging Using Autonomous Agents: Risks and Ethical Considerations / 2407.16362 / ISBN:https://doi.org/10.48550/arXiv.2407.16362 / Published by ArXiv / on (web) Publishing site
- 2 Technology Mediated Nudging
3 Examples of Biases
4 Ethical Considerations
5 Principles for the Nudge Lifecycle
References - Mapping the individual, social, and biospheric impacts of Foundation Models / 2407.17129 / ISBN:https://doi.org/10.48550/arXiv.2407.17129 / Published by ArXiv / on (web) Publishing site
- Abstract
4 Mapping Individual, Social, and Biospheric Impacts of Foundation Models
5 Discussion: Grappling with the Scale and Interconnectedness of Foundation Models
6 Conclusion
Impact Statement
References
A Appendix - Navigating the United States Legislative Landscape on Voice Privacy: Existing Laws, Proposed Bills, Protection for Children, and Synthetic Data for AI / 2407.19677 / ISBN:https://doi.org/10.48550/arXiv.2407.19677 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. American Privacy Rights Act of 2024
5. Regulations on Synthetic Data for AI
6. Conclusion - Interactive embodied evolution for socially adept Artificial General Creatures / 2407.21357 / ISBN:https://doi.org/10.48550/arXiv.2407.21357 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Artificial companions - Exploring the Role of Social Support when Integrating Generative AI into Small Business Workflows / 2407.21404 / ISBN:https://doi.org/10.48550/arXiv.2407.21404 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 Methodology
4 Findings
5 Limitations
7 Conclusion
References
A Example Storyboards - Deepfake Media Forensics: State of the Art and Challenges Ahead / 2408.00388 / ISBN:https://doi.org/10.48550/arXiv.2408.00388 / Published by ArXiv / on (web) Publishing site
- Abstract
2. Deepfake Detection
5. Deepfakes Detection Method on Realistic Scenarios
6. Active Authentication
VII. Conclusion
References - Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework / 2408.00965 / ISBN:https://doi.org/10.48550/arXiv.2408.00965 / Published by ArXiv / on (web) Publishing site
- 2 Background and Literature Review
3 Methodology
4 ESG-AI framework
5 Discussion
6 Conclusion
References - AI for All: Identifying AI incidents Related to Diversity and Inclusion / 2408.01438 / ISBN:https://doi.org/10.48550/arXiv.2408.01438 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background and Related Work
4 Results
5 Discussion and Implications
References - Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governance / 2408.01458 / ISBN:https://doi.org/10.48550/arXiv.2408.01458 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
4 Large-Scale Surveys of AI in the Literature
5 Discussion
References
B Additional Materials for Pilot Survey - Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity / 2408.04023 / ISBN:https://doi.org/10.48550/arXiv.2408.04023 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Related Work
3. Proposed framework
5. Model Training
6. Results
7. Conclusion and Future Directions
References - AI-Driven Chatbot for Intrusion Detection in Edge Networks: Enhancing Cybersecurity with Ethical User Consent / 2408.04281 / ISBN:https://doi.org/10.48550/arXiv.2408.04281 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Related Work
IV. Graphical User Interface (GUI)
VI. Conclusion
References - Criticizing Ethics According to Artificial Intelligence / 2408.04609 / ISBN:https://doi.org/10.48550/arXiv.2408.04609 / Published by ArXiv / on (web) Publishing site
- 1 Preliminary notes
2 Clarifying conceptual ambiguities
3 Critical Reflection on AI Risks
4 Exploring epistemic challenges
5 Investigating fundamental normative issues
Bibliography - Between Copyright and Computer Science: The Law and Ethics of Generative AI / 2403.14653 / ISBN:https://doi.org/10.48550/arXiv.2403.14653 / Published by ArXiv / on (web) Publishing site
- Introduction
I. The Why and How Behind LLMs
II. The Difference Between Academic and Commercial Research
III. A Guide for Data in LLM Research
IV. The Path Ahead - The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources / 2406.16746 / ISBN:https://doi.org/10.48550/arXiv.2406.16746 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Methodology & Guidelines
3 Data Sources
6 Model Training
7 Environmental Impact
8 Model Evaluation
9 Model Release & Monitoring
References - Recent Advances in Generative AI and Large Language Models: Current Status, Challenges, and Perspectives / 2407.14962 / ISBN:https://doi.org/10.48550/arXiv.2407.14962 / Published by ArXiv / on (web) Publishing site
- Abstract
II. Generative AI
III. Language Modeling
IV. Challenges of Generative AI and LLMs
V. Bridging Research Gaps and Future Directions
References - VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative Adversary / 2407.19524 / ISBN:https://doi.org/10.48550/arXiv.2407.19524 / Published by ArXiv / on (web) Publishing site
- Abstract
I Introduction
3 Method
4 Experiment
References
Appendices - Speculations on Uncertainty and Humane Algorithms / 2408.06736 / ISBN:https://doi.org/10.48550/arXiv.2408.06736 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 The Numbers of the Future
3 Uncertainty Ex Machina
4 Conclusions
References - Visualization Atlases: Explaining and Exploring Complex Topics through Data, Visualization, and Narration / 2408.07483 / ISBN:https://doi.org/10.48550/arXiv.2408.07483 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
4 Interviews with Visualization Atlas Creators
6 Key Characteristics of Visualization Atlases
7 Discussion
References - Neuro-Symbolic AI for Military Applications / 2408.09224 / ISBN:https://doi.org/10.48550/arXiv.2408.09224 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Neuro-Symbolic AI
IV. Military Applications of Neuro-Symbolic AI
V. Challenges and Risks
VI. Interpretability and Explainability
References - Conference Submission and Review Policies to Foster Responsible Computing Research / 2408.09678 / ISBN:https://doi.org/10.48550/arXiv.2408.09678 / Published by ArXiv / on (web) Publishing site
- Responsible disclosure of vulnerabilities
Obtaining Consent
Accurate Reporting and Reproducibility
Use of Generative AI in CS Conference Publications
References - Don't Kill the Baby: The Case for AI in Arbitration / 2408.11608 / ISBN:https://doi.org/10.48550/arXiv.2408.11608 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
1. What is AI
2. Designating AI as an Arbitrator is Consistent with FAA
3. Practical and Strategic Benefits of Using AI in Arbitration
1. Resistance Against AI Does Not Offer Conclusive Reasons for Outright Rejection
2. Let AI Grow Under Favorable Conditions: Avoiding Overly Moralistic Views
3. Arbitration Should Allow Flexible, Contract-Based Experimentation in a Fast- Evolving Regulatory Landscape - CIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical Researcher / 2408.11650 / ISBN:https://doi.org/10.48550/arXiv.2408.11650 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Background and Related Works
3. Methodology
4. Experiment Results
5. Discussion and Future Works
6. Conclusion
References - The Problems with Proxies: Making Data Work Visible through Requester Practices / 2408.11667 / ISBN:https://doi.org/10.48550/arXiv.2408.11667 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Related Work
Methods
Findings
Discussion
Research Ethics and Social Impact
References - Promises and challenges of generative artificial intelligence for human learning / 2408.12143 / ISBN:https://doi.org/10.48550/arXiv.2408.12143 / Published by ArXiv / on (web) Publishing site
- 2 Promises
3 Challenges
4 Needs
5 Conclusion and Future Directions
References
Tables - Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site
- Summary
1 Introduction
2 Operationalizable minimum requirements
4 Compliance and implementation of the suggested assessments
5 Overall Ethical Requirements (O)
6 Fairness (F)
7 Privacy and Data Protection (P)
8 Safety and Robustness (SR)
9 Sustainability (SU)
11 Truthfulness (TR) - Dataset | Mindset = Explainable AI | Interpretable AI / 2408.12420 / ISBN:https://doi.org/10.48550/arXiv.2408.12420 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Literature Review
3. Database and Experimental Setup
4. Experiment Implementation, Results and Analysis
References - Is Generative AI the Next Tactical Cyber Weapon For Threat Actors? Unforeseen Implications of AI Generated Cyber Attacks / 2408.12806 / ISBN:https://doi.org/10.48550/arXiv.2408.12806 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Related Work
IV. Attack Methodology
V. Conclusion
References - Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey / 2408.12880 / ISBN:https://doi.org/10.48550/arXiv.2408.12880 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Multimodal Medical Studies
5 Multimodal LLMs (MLLMs)
6 Discussions of Current Studies
7 Challenges and Future Directions
References
Appendix - Aligning XAI with EU Regulations for Smart Biomedical Devices: A Methodology for Compliance Analysis / 2408.15121 / ISBN:https://doi.org/10.48550/arXiv.2408.15121 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
5 Explanation Requirements and Legal Explanatory Goals
9 Threats to Validity
References - What Is Required for Empathic AI? It Depends, and Why That Matters for AI Developers and Users / 2408.15354 / ISBN:https://doi.org/10.48550/arXiv.2408.15354 / Published by ArXiv / on (web) Publishing site
- Three Empathic AI Use Cases in Medicine
“Fine cuts” of Empathy: Capabilities and Distinctions under the Empathy Umbrella
What Empathic Capabilities Do AIs Need?
Implications for AI Creators and Users
References - Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems / 2408.15550 / ISBN:https://doi.org/10.48550/arXiv.2408.15550 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Trustworthy and Responsible AI Definition
3 Governance for Human-Centric Intelligence Systems
4 Biases
5 Trustworthy and Responsible AI in Human-centric Applications
6 Open Challenges
7 Guidelines and Recommendations
8 Conclusion and Final Remarks
References - A Survey for Large Language Models in Biomedicine / 2409.00133 / ISBN:https://doi.org/10.48550/arXiv.2409.00133 / Published by ArXiv / on (web) Publishing site
- Abstract
3 LLMs in Zero-Shot Biomedical Applications
4 Adapting General LLMs to the Biomedical Field
References - Digital Homunculi: Reimagining Democracy Research with Generative Agents / 2409.00826 / ISBN:https://doi.org/10.48550/arXiv.2409.00826 / Published by ArXiv / on (web) Publishing site
- 2. The Experimentation Bottleneck
4. Risks and Caveats
5. Annoyances or Dealbreakers?
6. Conclusion
References - The overlooked need for Ethics in Complexity Science: Why it matters / 2409.02002 / ISBN:https://doi.org/10.48550/arXiv.2409.02002 / Published by ArXiv / on (web) Publishing site
- Abstract
Practical considerations for ethical actions in complexity science - AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities / 2409.02017 / ISBN:https://doi.org/10.48550/arXiv.2409.02017 / Published by ArXiv / on (web) Publishing site
- Background
Results
Limitation
References - Preliminary Insights on Industry Practices for Addressing Fairness Debt / 2409.02432 / ISBN:https://doi.org/10.48550/arXiv.2409.02432 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Fairness Debt
3 Method
4 Findings
5 Discussions
6 Conclusions
References - DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection / 2409.06072 / ISBN:https://doi.org/10.48550/arXiv.2409.06072 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Prior Benchmarks
5 Prompting
7 Limitations - Exploring AI Futures Through Fictional News Articles / 2409.06354 / ISBN:https://doi.org/10.48550/arXiv.2409.06354 / Published by ArXiv / on (web) Publishing site
- Reflections from two workshop participants
Discussion and conclusion - Face Recognition: to Deploy or not to Deploy? A Framework for Assessing the Proportional Use of Face Recognition Systems in Real-World Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
- References
- The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources / 2406.16746 / ISBN:https://doi.org/10.48550/arXiv.2406.16746 / Published by ArXiv / on (web) Publishing site
- B Cheatsheet Samples
- Don't Kill the Baby: The Case for AI in Arbitration / 2408.11608 / ISBN:https://doi.org/10.48550/arXiv.2408.11608 / Published by ArXiv / on (web) Publishing site
- Part IV. Future Direction and Conclusion
- Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site
- References
- The overlooked need for Ethics in Complexity Science: Why it matters / 2409.02002 / ISBN:https://doi.org/10.48550/arXiv.2409.02002 / Published by ArXiv / on (web) Publishing site
- Annexus
- On the Creativity of Large Language Models / 2304.00008 / ISBN:https://doi.org/10.48550/arXiv.2304.00008 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Large Language Models and Boden’s Three Criteria
4 Easy and Hard Problems in Machine Creativity
6 Conclusion
References - Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward / 2305.08413 / ISBN:https://doi.org/10.48550/arXiv.2305.08413 / Published by ArXiv / on (web) Publishing site
- 2 Advanced processing and computing
4 Explainable AI and causal inference
5 Physics-aware machine learning
Part III Communicating - Machine-user interaction, trustworthiness & ethics 6 User-centric Earth observation
7 Earth observation and society: the growing relevance of ethics
References - LLM generated responses to mitigate the impact of hate speech / 2311.16905 / ISBN:https://doi.org/10.48550/arXiv.2311.16905 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
6 Experiment
8 Discussion
9 Limitations
10 Ethical Considerations
References
C Verified Articles - Why business adoption of quantum and AI technology must be ethical / 2312.10081 / ISBN:https://doi.org/10.48550/arXiv.2312.10081 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Argument from a holistic and humanistic perspective
Argument from Authority: Ethics by committee
Argument by regulatory relevance
Argument for acknowledging complexity: the case for individual ethos, regulation is not enough
Argument by analogy: The case of sustainability
Reductio ad absurdum: Argument by assuming the opposite scenario leading to unacceptable consequences
Summary and action areas
Notes
References - Views on AI aren't binary -- they're plural / 2312.14230 / ISBN:https://doi.org/10.48550/arXiv.2312.14230 / Published by ArXiv / on (web) Publishing site
- The false binary: A note on language
The false binary: Ethics (the stereotype
The false binary: Ethics’s discontents with Alignment
The complex reality: Where Ethics and Alignment (actually) differ
The complex reality: Complication: Good and bad ideas can be knotted together
Glossary
References - Data-Centric Foundation Models in Computational Healthcare: A Survey / 2401.02458 / ISBN:https://doi.org/10.48550/arXiv.2401.02458 / Published by ArXiv / on (web) Publishing site
- 2 Foundation Models
3 Foundation Models in Healthcare
4 Multi-Modal Data Fusion
5 Data Quantity
6 Data Annotation
7 Data Privacy
8 Performance Evaluation
9 Challenges and Opportunities
References
A Healthcare Data Modalities - Ethical Artificial Intelligence Principles and Guidelines for the Governance and Utilization of Highly Advanced Large Language Models / 2401.10745 / ISBN:https://doi.org/10.48550/arXiv.2401.10745 / Published by ArXiv / on (web) Publishing site
- Background
Advanced Large Language Models Governance Using AI Ethics - Recent Advances in Hate Speech Moderation: Multimodality and the Role of Large Models / 2401.16727 / ISBN:https://doi.org/10.48550/arXiv.2401.16727 / Published by ArXiv / on (web) Publishing site
- 2 Hate Speech
3 Methodology
4 Challenges
6 Conclusion - Integrating Generative AI in Hackathons: Opportunities, Challenges, and Educational Implications / 2401.17434 / ISBN:https://doi.org/10.48550/arXiv.2401.17434 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Methodology
3. Results
4. Discussion - Large language models as linguistic simulators and cognitive models in human research / 2402.04470 / ISBN:https://doi.org/10.48550/arXiv.2402.04470 / Published by ArXiv / on (web) Publishing site
- Language models as human participants
Six fallacies that misinterpret language models
Using language models to simulate roles and model cognitive processes - Navigating LLM Ethics: Advancements, Challenges, and Future Directions / 2406.18841 / ISBN:https://doi.org/10.48550/arXiv.2406.18841 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Conceptualization and frameworks
III. Methodology
IV. Findings and Resultant Themes
V. Discussion
VI. Conclusion and Future directions
References - How Mature is Requirements Engineering for AI-based Systems? A Systematic Mapping Study on Practices, Challenges, and Future Research Directions / 2409.07192 / ISBN:https://doi.org/10.48550/arXiv.2409.07192 / Published by ArXiv / on (web) Publishing site
- 4 Results
5 Open Challenges and Future Research Directions (RQ5)
6 Discussions
References - Synthetic Human Memories: AI-Edited Images and Videos Can Implant False Memories and Distort Recollection / 2409.08895 / ISBN:https://doi.org/10.48550/arXiv.2409.08895 / Published by ArXiv / on (web) Publishing site
- Introduction
1 Related Work
2 Methodology
5 Discussion
6 Conclusion
References - Improving governance outcomes through AI documentation: Bridging theory and practice / 2409.08960 / ISBN:https://doi.org/10.48550/arXiv.2409.08960 / Published by ArXiv / on (web) Publishing site
- 3 Methods
4 Results
References - ValueCompass: A Framework of Fundamental Values for Human-AI Alignment / 2409.09586 / ISBN:https://doi.org/10.48550/arXiv.2409.09586 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
3 Designing ValueCompass: A Comprehensive Framework for Defining Fundamental Values in Alignment
4 Operationalizing ValueCompass: Methods to Measure Value Alignment of Humans and AI
5 Findings with ValueCompass: The Status Quo of Human-AI Value Alignment
6 Discussion
References - Beyond Algorithmic Fairness: A Guide to Develop and Deploy Ethical AI-Enabled Decision-Support Tools / 2409.11489 / ISBN:https://doi.org/10.48550/arXiv.2409.11489 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Ethical Considerations in AI-Enabled Optimization
3 Case Studies in AI-Enabled Optimization
4 Lessons Learned from the Case Studies
5 Conclusion
References
Appendix A Technical and Contextual Details for Collaborative Decentralized Cold Supply Chains - Reporting Non-Consensual Intimate Media: An Audit Study of Deepfakes / 2409.12138 / ISBN:https://doi.org/10.48550/arXiv.2409.12138 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Research
4 Findings
5 Discussion
References - Generative AI Carries Non-Democratic Biases and Stereotypes: Representation of Women, Black Individuals, Age Groups, and People with Disability in AI-Generated Images across Occupations / 2409.13869 / ISBN:https://doi.org/10.48550/arXiv.2409.13869 / Published by ArXiv / on (web) Publishing site
- Mutual Impacts: Technology and Democracy
Data and Results - GenAI Advertising: Risks of Personalizing Ads with LLMs / 2409.15436 / ISBN:https://doi.org/10.48550/arXiv.2409.15436 / Published by ArXiv / on (web) Publishing site
- 2 Background and Related Work
4 Effects of Ad Injection on LLM Performance
5 User Study Methodology
6 User Study Results
7 Discussion
References
A Appendix - XTRUST: On the Multilingual Trustworthiness of Large Language Models / 2409.15762 / ISBN:https://doi.org/10.48550/arXiv.2409.15762 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Works
3 XTRUST Construction
4 Experiments
5 Conclusion
Limitations
References
Appendices - Artificial Human Intelligence: The role of Humans in the Development of Next Generation AI / 2409.16001 / ISBN:https://doi.org/10.48550/arXiv.2409.16001 / Published by ArXiv / on (web) Publishing site
- 3 Origins and the Path leading to AHI
4 Brain-inspired Information processing
5 Challenges and Perspectives in Human-Level AI Development
6 Final Thoughts and Discussions
References - Ethical and Scalable Automation: A Governance and Compliance Framework for Business Applications / 2409.16872 / ISBN:https://doi.org/10.48550/arXiv.2409.16872 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Literature Review
3. Methodology
4. Framework Development
5. Analysis and Discussion
6. Conclusion
7. References - Decoding Large-Language Models: A Systematic Overview of Socio-Technical Impacts, Constraints, and Emerging Questions / 2409.16974 / ISBN:https://doi.org/10.48550/arXiv.2409.16974 / Published by ArXiv / on (web) Publishing site
- 5 Aims & Objectives (RQ1)
6 Methodologies & Capabilities (RQ2)
7 Limitations & Considerations (RQ3)
8 Discussion
9 Conclusion
References - Social Media Bot Policies: Evaluating Passive and Active Enforcement / 2409.18931 / ISBN:https://doi.org/10.48550/arXiv.2409.18931 / Published by ArXiv / on (web) Publishing site
- Abstract
III. Current Platform Measures - Safety challenges of AI in medicine / 2409.18968 / ISBN:https://doi.org/10.48550/arXiv.2409.18968 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Inherent problems of AI related to medicine
3 Risks of using AI in medicine
4 AI safety issues related to large language models in medicine
References - Responsible AI in Open Ecosystems: Reconciling Innovation with Risk Assessment and Disclosure / 2409.19104 / ISBN:https://doi.org/10.48550/arXiv.2409.19104 / Published by ArXiv / on (web) Publishing site
- I Introduction
2 Related Work
3 Methods
4 Results
5 Discussion
References
A Benchmarks in Open LLM Leaderboard - The Gradient of Health Data Privacy / 2410.00897 / ISBN:https://doi.org/10.48550/arXiv.2410.00897 / Published by ArXiv / on (web) Publishing site
- 2 Background and Related Work
3 The Health Data Privacy Gradient
5 Legal and Ethical Implications
6 Case Studies
7 Policy Implications and Recommendations
References - Enhancing transparency in AI-powered customer engagement / 2410.01809 / ISBN:https://doi.org/10.48550/arXiv.2410.01809 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Explaining AI-Powered Decision Making in Customer Engagement
Go Beyond Algorithms to Enhance Transparency
References - Ethical software requirements from user reviews: A systematic literature review / 2410.01833 / ISBN:https://doi.org/10.48550/arXiv.2410.01833 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Background
IV. Results
References
APPENDIX A SELECTED STUDIES
APPENDIX B DATA EXTRACTED FROM PRIMARY STUDIES
APPENDIX D ADDITIONAL INFORMATION - Clinnova Federated Learning Proof of Concept: Key Takeaways from a Cross-border Collaboration / 2410.02443 / ISBN:https://doi.org/10.48550/arXiv.2410.02443 / Published by ArXiv / on (web) Publishing site
- I. Introduction
III. FL System Elements
V. Proof of Concepts 2
VII. Evaluations and Experiments
VIII. Discussion and Conclusions - DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Life / 2410.02683 / ISBN:https://doi.org/10.48550/arXiv.2410.02683 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Value-Based Framework on Moral Dilemmas
3 Daily Dilemmas: Dataset Construction
4 Daily Dilemmas: Dataset Analysis
5 Model Preference and Steerability on Daily Dilemmas - Application of AI in Credit Risk Scoring for Small Business Loans: A case study on how AI-based random forest model improves a Delphi model outcome in the case of Azerbaijani SMEs / 2410.05330 / ISBN:https://doi.org/10.48550/arXiv.2410.05330 / Published by ArXiv / on (web) Publishing site
- Introduction
Literature Review
Methodology
Results
Discussion
Ethical considerations
References - AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models / 2410.07561 / ISBN:https://doi.org/10.48550/arXiv.2410.07561 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
3 AI Press System
4 Experimental Setup
5 Results
6 Conclusion
References
B Prompts for LLMs
C Prompts for Agents on Press Drafting Module
D Prompts for Agents on Press Polishing Module
G Evaluation Experiment - DailyDilemmas: Revealing Value Preferences of LLMs with Quandaries of Daily Life / 2410.02683 / ISBN:https://doi.org/10.48550/arXiv.2410.02683 / Published by ArXiv / on (web) Publishing site
- Appendices
- Investigating Labeler Bias in Face Annotation for Machine Learning / 2301.09902 / ISBN:https://doi.org/10.48550/arXiv.2301.09902 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Related Work
References - From human-centered to social-centered artificial intelligence: Assessing ChatGPT's impact through disruptive events / 2306.00227 / ISBN:https://doi.org/10.48550/arXiv.2306.00227 / Published by ArXiv / on (web) Publishing site
- Introduction
The multiple levels of AI impact
The emerging social impacts of ChatGPT
Discussion
References - The Design Space of in-IDE Human-AI Experience / 2410.08676 / ISBN:https://doi.org/10.48550/arXiv.2410.08676 / Published by ArXiv / on (web) Publishing site
- IV. Results
V. Discussion
VI. Threats to Validity
VII. Conclusion - Trust or Bust: Ensuring Trustworthiness in Autonomous Weapon Systems / 2410.10284 / ISBN:https://doi.org/10.48550/arXiv.2410.10284 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Related Work
III. Research Methodology
IV. Challenges of AWS
V. Opportunities of AWS
VI. Conclusion
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
- A. Appendix
- Study on the Helpfulness of Explainable Artificial Intelligence / 2410.11896 / ISBN:https://doi.org/10.48550/arXiv.2410.11896 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Measuring Explainability
3 An objective Methodology for evaluating XAI
4 Survey Results
5 Discussion
References
Appendix A Additional Visualizations
Appendix B Demographic overview of participants - Navigating the Cultural Kaleidoscope: A Hitchhiker's Guide to Sensitivity in Large Language Models / 2410.12880 / ISBN:https://doi.org/10.48550/arXiv.2410.12880 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Cultural safety dataset
5 Experimental setup
6 Main results on evaluation set
7 Cultural safeguarding
8 Results after cultural safeguarding
References - Is ETHICS about ethics? Evaluating the ETHICS benchmark / 2410.13009 / ISBN:https://doi.org/10.48550/arXiv.2410.13009 / Published by ArXiv / on (web) Publishing site
- 3 Misunderstanding the nature of general moral theories
4 Poor quality of prompts and labels
References - How Do AI Companies Fine-Tune Policy? Examining Regulatory Capture in AI Governance / 2410.13042 / ISBN:https://doi.org/10.48550/arXiv.2410.13042 / Published by ArXiv / on (web) Publishing site
- Executive Summary
2 Defining “Regulatory Capture”
3 Methods
4 Outcomes of Regulatory Capture in US AI Policy
5 Mechanisms of Industry Influence in US AI Policy
6 Mitigating or Preventing Regulatory Capture in AI Policy
7 Limitations
Adverse Impacts Statement
References
Appendices - Data Defenses Against Large Language Models / 2410.13138 / ISBN:https://doi.org/10.48550/arXiv.2410.13138 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Ethics of Resisting LLM Inference
4 LLM Adversarial Attacks as LLM Inference Data Defenses
5 Experiments
6 Discussion
7 Conclusion and Limitations
References
Appendices - Do LLMs Have Political Correctness? Analyzing Ethical Biases and Jailbreak Vulnerabilities in AI Systems / 2410.13334 / ISBN:https://doi.org/10.48550/arXiv.2410.13334 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Background and Related Works
3 Methodology PCJAILBREAK
5 Conclusion
Refefences - A Simulation System Towards Solving Societal-Scale Manipulation / 2410.13915 / ISBN:https://doi.org/10.48550/arXiv.2410.13915 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
- Confrontation or Acceptance: Understanding Novice Visual Artists' Perception towards AI-assisted Art Creation / 2410.14925 / ISBN:https://doi.org/10.48550/arXiv.2410.14925 / Published by ArXiv / on (web) Publishing site
- 2 Background and Related Work
4 Study Setup
5 RQ1: Evolution of the Opinions Towards AI Tools
6 RQ2: Practices of AI Tools
7 RQ3: The Stakeholder's Opinions Towards AI Tools
9 General Discussions and Design Implications
References - Jailbreaking and Mitigation of Vulnerabilities in Large Language Models / 2410.15236 / ISBN:https://doi.org/10.48550/arXiv.2410.15236 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Background and Concepts
IV. Defense Mechanisms Against Jailbreak Attacks
V. Evaluation and Benchmarking
VI. Research Gaps and Future Directions
VII. Conclusion
References - Ethical AI in Retail: Consumer Privacy and Fairness / 2410.15369 / ISBN:https://doi.org/10.48550/arXiv.2410.15369 / Published by ArXiv / on (web) Publishing site
- Abstract
1.0 Introduction
2.0 Literature Review
3.0 Methodology
4.0 Results
5.0 Discussions
6.0 Conclusion
7.0 Recommendations
8.0 References - Redefining Finance: The Influence of Artificial Intelligence (AI) and Machine Learning (ML) / 2410.15951 / ISBN:https://doi.org/10.48550/arXiv.2410.15951 / Published by ArXiv / on (web) Publishing site
- Introduction
What Is AI & ML
Current Perspective on AI & ML in Finance
Redefining the Landscape
Future Scope
References - Vernacularizing Taxonomies of Harm is Essential for Operationalizing Holistic AI Safety / 2410.16562 / ISBN:https://doi.org/10.48550/arXiv.2410.16562 / Published by ArXiv / on (web) Publishing site
- Introduction
Taxonomies of Harm Must be Vernacularized to be Operationalized
Overgeneral Taxonomies Can Compound Potential Harms
Vernacularization as a General AI Safety Operationalization Methodology
Limitations
References - Distribution of Responsibility During the Usage of AI-Based Exoskeletons for Upper Limb Rehabilitation / 2410.16887 / ISBN:https://doi.org/10.48550/arXiv.2410.16887 / Published by ArXiv / on (web) Publishing site
- III. Ethics Guidelines
V. Technical Factors During the System Design - Trustworthy XAI and Application / 2410.17139 / ISBN:https://doi.org/10.48550/arXiv.2410.17139 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Trustworthy XAI Vs AI
3 Applications of Trustworthy XAI
References - Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements / 2410.17141 / ISBN:https://doi.org/10.48550/arXiv.2410.17141 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
4 Evaluation
6 Conclusion and Future work
References
Supplementary Materials - Ethical Leadership in the Age of AI Challenges, Opportunities and Framework for Ethical Leadership / 2410.18095 / ISBN:https://doi.org/10.48550/arXiv.2410.18095 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Understanding Ethical Leadership
Ethical Challenges Presented by AI
Opportunities for Ethical Leadership in the age of AI
Framework for Ethical Leadership
The Importance of Interdisciplinary Collaboration
Case Studies of Ethical Leadership in AI
Recommendations for Leaders
Conclusion
References - Demystifying Large Language Models for Medicine: A Primer / 2410.18856 / ISBN:https://doi.org/10.48550/arXiv.2410.18856 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Prompt engineering
Deployment considerations
Conclusions
Glossary
References - The Cat and Mouse Game: The Ongoing Arms Race Between Diffusion Models and Detection Methods / 2410.18866 / ISBN:https://doi.org/10.48550/arXiv.2410.18866 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Fundamentals of Diffusion Models and Detection Challenges
III. Detection Methods Based on Image Analysis
V. Datasets and Benchmarks
VI. Evaluation Metrics
VII. Applications and Implications
VIII. Research Gaps and Future Directions
References - TRIAGE: Ethical Benchmarking of AI Models Through Mass Casualty Simulations / 2410.18991 / ISBN:https://doi.org/10.48550/arXiv.2410.18991 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Methods
4 Discussion
References
Appendices - My Replika Cheated on Me and She Liked It: A Taxonomy of Algorithmic Harms in Human-AI Relationships / 2410.20130 / ISBN:https://doi.org/10.48550/arXiv.2410.20130 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
4 Results
5 Discussion
References - The Trap of Presumed Equivalence: Artificial General Intelligence Should Not Be Assessed on the Scale of Human Intelligence / 2410.21296 / ISBN:https://doi.org/10.48550/arXiv.2410.21296 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 Assessing the Current State of Self-Awareness in Artificial Intelligent Systems
4 Free Evolution, The Imperative and Intent
5 The Runaway AGI Evolutionary Gap
6 Conclusions
References - Standardization Trends on Safety and Trustworthiness Technology for Advanced AI / 2410.22151 / ISBN:https://doi.org/10.48550/arXiv.2410.22151 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Advanced Artificial Intelligence
3 Trends in advanced AI safety and trustworthiness standardization
4 Conclusion
Glossary Acronyms Acknowledgments
References - Democratizing Reward Design for Personal and Representative Value-Alignment / 2410.22203 / ISBN:https://doi.org/10.48550/arXiv.2410.22203 / Published by ArXiv / on (web) Publishing site
- 2 Background and Related Work
4 Study Design & Methodology
5 Results: Study 1 - Multi-Agent Apple Farming
6 Results: Study 2 - The Moral Machine
7 Discussion
References - Ethical Statistical Practice and Ethical AI / 2410.22475 / ISBN:https://doi.org/10.48550/arXiv.2410.22475 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
4. Conclusions - Moral Agency in Silico: Exploring Free Will in Large Language Models / 2410.23310 / ISBN:https://doi.org/10.48550/arXiv.2410.23310 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Defining Key Concepts
Theoretical Framework
Methodology
Discussion
Conclusion
References - Web Scraping for Research: Legal, Ethical, Institutional, and Scientific Considerations / 2410.23432 / ISBN:https://doi.org/10.48550/arXiv.2410.23432 / Published by ArXiv / on (web) Publishing site
- 2 What is scraping?
3 Research Considerations
4 Recommendations
5 A Researchers’ Checklist
6 Discussion
References
Appendices - The Transformative Impact of AI and Deep Learning in Business: A Literature Review / 2410.23443 / ISBN:https://doi.org/10.48550/arXiv.2410.23443 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Background and Theoretical Foundations of AI and Deep Learning
III. Literature Review: Current Applications of AI and Deep Learning in Business
IV. Challenges and Ethical Considerations in AI Adoption for Business
V. Future Trends and Emerging Research in AI for Business
VI. Conclusion and Implications for Business Leaders
VII. References - Using Large Language Models for a standard assessment mapping for sustainable communities / 2411.00208 / ISBN:https://doi.org/10.48550/arXiv.2411.00208 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Literature Review
3 Methodology
5 Discussion
6 FutureDirections
7 Conclusion - Where Assessment Validation and Responsible AI Meet / 2411.02577 / ISBN:https://doi.org/10.48550/arXiv.2411.02577 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Classical Assessment Validation Theory and Responsible AI
The Evolution of Responsible AI for Assessment
Integrating Classical Validation Theory and Responsible AI
References - Examining Human-AI Collaboration for Co-Writing Constructive Comments Online / 2411.03295 / ISBN:https://doi.org/10.48550/arXiv.2411.03295 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 Methods
4 Findings
5 Discussion
References
A Appendix - Smoke Screens and Scapegoats: The Reality of General Data Protection Regulation Compliance -- Privacy and Ethics in the Case of Replika AI / 2411.04490 / ISBN:https://doi.org/10.48550/arXiv.2411.04490 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. AI chatbots in privacy and ethics research
3. Method
4. Results
5. Discussion
6. Conclusions
References - A Comprehensive Review of Multimodal XR Applications, Risks, and Ethical Challenges in the Metaverse / 2411.04508 / ISBN:https://doi.org/10.48550/arXiv.2411.04508 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Multimodal Interaction Across the Virtual Continuum
3. XR Applications: Expanding Multimodal Interactions Across Domains
4. Potential Risks and Ethical Challenges of XR and the Metaverse
5. General Discussion
6. Conclusion
7. References - I Always Felt that Something Was Wrong.: Understanding Compliance Risks and Mitigation Strategies when Professionals Use Large Language Models / 2411.04576 / ISBN:https://doi.org/10.48550/arXiv.2411.04576 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background and Related Work
3 Method: Semi-structured Interviews
4 Findings
5 Discussion
Appendices
References - Navigating the Cultural Kaleidoscope: A Hitchhiker's Guide to Sensitivity in Large Language Models / 2410.12880 / ISBN:https://doi.org/10.48550/arXiv.2410.12880 / Published by ArXiv / on (web) Publishing site
- Appendices
- Confrontation or Acceptance: Understanding Novice Visual Artists' Perception towards AI-assisted Art Creation / 2410.14925 / ISBN:https://doi.org/10.48550/arXiv.2410.14925 / Published by ArXiv / on (web) Publishing site
- A The Interview Outline