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Bibliography items where occurs: 436
- The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site
- 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
3 Methodology
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
- 3 Research Method
5 Detail results and analysis
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
- 3 Method
4 Results
References - The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis / 2206.03225 / ISBN:https://doi.org/10.48550/arXiv.2206.03225 / Published by ArXiv / on (web) Publishing site
- 3 Study Methodology
5 Evaluation of Ethical Principle Implementations
7 Threats to Validiity
Acknowledgment
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
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
- 2 Related Work
3 Methodology
4 Results
5 Discussion
6 Conclusion - 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
- 3 The Problem with the Near/Long-Term Distinction
References - ESR: Ethics and Society Review of Artificial Intelligence Research / 2106.11521 / ISBN:https://doi.org/10.48550/arXiv.2106.11521 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
3 The ESR Process
4 Deployment and Evaluation
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
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
Appendix B: Data and charts from arXiv - 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
- 2 Background
3 Methodology
4 Proposed competency framework for responsible AI practitioners - 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
- 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
- II. Underlying Aspects
III. Interactions between Aspects
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
- 2 The Question Bank: QB4AIRA
References - A multilevel framework for AI governance / 2307.03198 / ISBN:https://doi.org/10.48550/arXiv.2307.03198 / Published by ArXiv / on (web) Publishing site
- Abstract
4. Corporate Self-Governance
5. AI Literacy and Governance by Citizen
6. Psychology of 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
- 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 - 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
- Abstract
Introduction
Literature Review
Methods
Results
Conclusion
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
- 2 Clarifying Terminologies of Article-5: Insights from Behavioral Economics and Psychology
3 Enhancing Protection for the General Public and Vulnerable Groups - 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
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
- Introduction
System-role
Perturbation
Image-related
Hallucination
Bias and Discrimination of Training Data - 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
- Abstract
1 Introduction
2 Background
3 Policy scope
4 Centralized regulation in the US context
5 Crowdsourced safety mechanism
6 The dual governance framework - 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
- 3 Taxonomy of ethical principles
4 Previous operationalisation of ethical principles
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
- Introduction
Responsibility in War
Computers, Autonomy and Accountability
Moral Injury
Human Factors
AI Workplace Health and Safety Framework
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
- Abstract
1 Introduction
2 Results
5 Methods - A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation / 2305.11391 / ISBN:https://doi.org/10.48550/arXiv.2305.11391 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
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
- 2 Background
3 LLM-based penetration testing
4 Discussion
5 A vision of AI-augmented pen-testing - Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust / 2308.09979 / ISBN:https://doi.org/10.48550/arXiv.2308.09979 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Discussion
4 Conclusions
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
- 2 Related works
References - AIxArtist: A First-Person Tale of Interacting with Artificial Intelligence to Escape Creative Block / 2308.11424 / ISBN:https://doi.org/10.48550/arXiv.2308.11424 / Published by ArXiv / on (web) Publishing site
- 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
- 4 Enhancing User Experience through Creative AI Tools
6 Unveiling the Potential: Benefits of Interactive Web-Based Programming
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
12 The Future Landscape: Creative AI Tools and Game-Based Methodologies in Education
14 Conclusion & Discussion
References - 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
2 Related Work on Data Excellence
4 Published Annotation Tasks and Datasets
5 Results
6 Discussion
References
A Agreement Analysis - Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph / 2308.13534 / ISBN:https://doi.org/10.48550/arXiv.2308.13534 / Published by ArXiv / on (web) Publishing site
- I. Introduction
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
References
Appendix A industry-wide LLM usecases - The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward / 2308.14253 / ISBN:https://doi.org/10.48550/arXiv.2308.14253 / Published by ArXiv / on (web) Publishing site
- 3 Emerging dual-use risks and vulnerabilities in AI systems
4 Integrating red teaming, blue teaming, and ethics with violet teaming
7 Violet teaming to address dual-use risks of AI in biotechnology
10 Supplemental & additional details
References - Artificial Intelligence in Career Counseling: A Test Case with ResumAI / 2308.14301 / ISBN:https://doi.org/10.48550/arXiv.2308.14301 / Published by ArXiv / on (web) Publishing site
- 2 Literature review
4 Results and discussion - Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? / 2308.15399 / ISBN:https://doi.org/10.48550/arXiv.2308.15399 / Published by ArXiv / on (web) Publishing site
- 2 Related Works
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
- 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
- 1. Introduction
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
- Part 1 - 1 Generatives Systems: Mimicking Artifacts
Part 1 - 2 Appreciate Systems: Mimicking Styles
Part 1 - 3 Artistic Systems: Mimicking Inspiration
Part 2 Art Data and Human–Machine Interaction in Art Creation
Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data
Part 2 - 2 Motion Caputer Technologies and Motion Data
Part 2 - 4 Aesthetic Descriptor: Labelling Artefacts with Emotion
Part 3 - 2 Machine Artist Models
Part 3 - 3 Comparison with Generative Models
Part 3 - 4 Demonstration of the Proposed Framework
Part 5 - 1 Authorship and Ownership of AI-generated Works of Artt
References
Acknowledgment - FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging / 2109.09658 / ISBN:https://doi.org/10.48550/arXiv.2109.09658 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Fairness - For Equitable AI in Medical Imaging
3. Universality - For Standardised AI in Medical Imaging
4. Traceability - For Transparent and Dynamic AI in Medical Imaging
5. Usability - For Effective and Beneficial AI in Medical Imaging
6. Robustness - For Reliable AI in Medical Imaging
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
3 Legal and Ethical Considerations
4 Experiments
General References
C Case Outcome Task Description
D Case Outcome Annotation Instructions
F Evaluation of GPT Models
Cambridge Law Corpus: Datasheet - EALM: Introducing Multidimensional Ethical Alignment in
Conversational Information Retrieval / 2310.00970 / ISBN:https://doi.org/10.48550/arXiv.2310.00970 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related Work
3 Dataset Construction
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
- I. Introduction and Motivation
II. AI-Robotics Systems Architecture
IV. Attack Surfaces
V. Ethical & Legal Concerns
VI. Human-Robot Interaction (HRI) Security Studies
VII. Future Research & Discussion
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
- 4 AI Governance Principles
- 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
- 2 Background and Related Work
3 Method
4 Taxonomy of AI Privacy Risks
5 Discussion
References - ClausewitzGPT Framework: A New Frontier in Theoretical Large Language Model Enhanced Information Operations / 2310.07099 / ISBN:https://doi.org/10.48550/arXiv.2310.07099 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Nation-State Advances in AI-driven Information Operations
Theoretical Impact of LLMs on Information Operations
ClausewitzGPT and Modern Strategy
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
References - The AI Incident Database as an Educational Tool to Raise Awareness of AI Harms: A Classroom Exploration of Efficacy, Limitations, & Future Improvements / 2310.06269 / ISBN:https://doi.org/10.48550/arXiv.2310.06269 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Research Design and Methodology
3 Analysis and Findings
References
A Consent and Data Collection Processes
B Pre-class 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
- 1. Introduction
2. Literature Review
3. AI Ethical Principles
4. Implementing the Practical Use of Ethical AI Applications
5. Conclusions and Recommendations
References
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
- 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
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
3 The applications of STREAM
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
- 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
- 2. Research Methodology
3. Ethics of AI and Robotics
4. Systematic Review and Scientometric Analysis
5. Ethical Issues of AI and Robotics in AEC Industry
6. Discussion
7. Future Research Direction
References - 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
- Introduction
Pilot Study: Text SERPs with Ads
Evaluation of the Pilot Study
Ethics of GEnerating Native Ads
Conclusion
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
- Notes
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
- Principal Ethics in Healthcare
Method
Results and Discussion
References - Risk of AI in Healthcare: A Comprehensive Literature Review and Study Framework / 2309.14530 / ISBN:https://doi.org/10.48550/arXiv.2309.14530 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
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
7. Issues
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 - 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
- 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
- 1 Introduction
2 Definitions of Terms
5 Relating Case Studies to Indigenous Data Sovereignty and CARE Principles
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
- 2 Harms of Influencer Marketing
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
- 1. Introduction
2. AI and blockchain in education: An overview of the benefits and challenges
4. Blockchain-based credentialing and certification
6. Blockchain-based decentralized learning networks
7. AI-powered content creation and curation
11.References - Toward an Ethics of AI Belief / 2304.14577 / ISBN:https://doi.org/10.48550/arXiv.2304.14577 / Published by ArXiv / on (web) Publishing site
- 2. “Belief” in Humans and AI
3. Proposed Novel Topics in an 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
- Introduction
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
Discussion - 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
- 2 Methodology
3 Governance Patterns
4 Process Patterns
5 Product Patterns
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
FUTURE-AI GUIDELINE
DISCUSSION
ACKNOWLEDGMENTS - 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
- 2 Agent Design
Appendix B Experiment Details - Specific versus General Principles for Constitutional AI / 2310.13798 / ISBN:https://doi.org/10.48550/arXiv.2310.13798 / Published by ArXiv / on (web) Publishing site
- 4 Reinforcement Learning with Good-for-Humanity Preference Models
References
C General Prompts for GfH Preference Modeling
G Over-Training on Good for Humanity
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
3 Method
4 Findings
5 Discussion - 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
- Abstract
4 Systematic AI for Energy Wall
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
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
References
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
- 1 Introduction
2 Risks and Ethical Issues of Big Model
3 Investigating the Ethical Values of Large Language Models
References - Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
- 3 The BvH and HK Definitions
4 The Causal Condition
6 Degree of Responsibility
References - AI for Open Science: A Multi-Agent Perspective for
Ethically Translating Data to Knowledge / 2310.18852 / ISBN:https://doi.org/10.48550/arXiv.2310.18852 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background and Related Work
3 A Formal Language of AI for Open Science
4 Optimizing an Openness Metric in AI for Science
5 Why Openness in AI for Science
References - Artificial Intelligence Ethics Education in Cybersecurity: Challenges and Opportunities: a
focus group report / 2311.00903 / ISBN:https://doi.org/10.48550/arXiv.2311.00903 / Published by ArXiv / on (web) Publishing site
- Educational Challenges of Teaching AI Ethics in Cybersecurity and Core Ethical
Principles
Technical Issues
Communication skills in cybersecurity and ethics
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
- Abstract
I. Introduction
II. Contextual Concerns: Why AI Research Needs its Own Guidelines
III. Ethical Principles for AI Research with Human Participants
IV. Principles in Practice: Guidelines for AI Research with Human Participants
References
Appendix A Evaluating Current Practices for Human-Participants Research
Appendix B Placing Research Ethics for Human Participans in Historical Context
Appendix C Defining the Scope of Research Participation in AI Research - LLMs grasp morality in concept / 2311.02294 / ISBN:https://doi.org/10.48550/arXiv.2311.02294 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 A General Theory of Meaning
4 The Moral Model
5 Conclusion
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
- Research questions
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
1 Introduction
2 Related Work
3 Methodology
4 Evaluation
5 Conclusion
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
- 4 Deontological AI Alignment
- 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
- 1 Introduction
2 Overview of ChatGPT and its capabilities
3 Transformers and pre-trained language models
4 Applications of ChatGPT in real-world scenarios
6 Limitations and potential challenges
7 Ethical considerations when using ChatGPT
8 Prompt engineering and generation
10 Future directions for ChatGPT in vision domain
References - Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies / 2304.07683 / ISBN:https://doi.org/10.48550/arXiv.2304.07683 / Published by ArXiv / on (web) Publishing site
- II. Sources of bias in AI
IV. Mitigation strategies for bias in AI
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
4 A Multimodal Ethics Classifier - 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
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
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
- 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
- 1 Introduction
3 Methodology
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
- Abstract
2 UnknownBench: Evaluating LLMs on the Unknown
3 Experiments
B Confidence Elicitation Method Comparison - 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
7. Future Research Directions
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
7 Conclusion
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
- Bloustein Local and the Center for Urban Policy Research
Preface
Why Liability Law?
Harms, Risk, and Liability Practices
Mitigation Tools
Conclusion
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
Appendix D - List of Organization Acronyms
Appendix E - A Sampling of References Addressing Liability and Digital Products - 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
- Abstract
1 Introduction
2 Proposed Process
3 Related Work and Discussion
4 Conclusion
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
- 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
- 1 Introduction
3 Study Design
4 Findings
A Overview of AIIA Instruments - GPT in Data Science: A Practical Exploration of Model Selection / 2311.11516 / ISBN:https://doi.org/10.48550/arXiv.2311.11516 / Published by ArXiv / on (web) Publishing site
- III. Approach: capturing and representing heuristics behind GPT's decision-making process
References - Responsible AI Research Needs Impact Statements Too / 2311.11776 / ISBN:https://doi.org/10.48550/arXiv.2311.11776 / Published by ArXiv / on (web) Publishing site
- What are other research communities doing?
Suggestions for More Meaningful Engagement with the Impact of RAI Research
Concluding Reflections
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
- I. Introduction
II. Education and LLMS
III. Key technologies for EDULLMS
IV. LLM-empowered education
V. Key points in LLMSEDU
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
IV. Risks of generative AI
VI. Conclusion
References - 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
- References
6 Appendix - 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
Research Method
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
METHODOLOGY
FINDINGS
DISCUSSION - 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
- 2. Pre-Deployment phase
3. Production deployment monitoring phase
4. Post-market surveillance phase
Bibliography - Ethics and Responsible AI Deployment / 2311.14705 / ISBN:https://doi.org/10.48550/arXiv.2311.14705 / Published by ArXiv / on (web) Publishing site
- 1. Introduction: The Role of Algorithms in Protecting Privacy
3. Ethical considerations in AI decision-making
4. Addressing bias, transparency, and accountability
5. Ethical AI design principles and guidelines
7. Establishing responsible AI governance and oversight
9. Discussion on engaging stakeholders: fostering dialogue and collaboration between developers, users, and affected communities.
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
- Abstract
2. Material and methods
3. Results
References - Generative AI and US Intellectual Property Law / 2311.16023 / ISBN:https://doi.org/10.48550/arXiv.2311.16023 / Published by ArXiv / on (web) Publishing site
- Abstract
II. US Patent law
III. US Copyright law
IV. Caveart emptor: no free ride for automation
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
- 1 Introduction
2 Privacy and data protection
3 Transparency and explainability
4 Fairness and equity
5 Responsiblity, accountability, and regulations
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
II. Background
III. The rise of large AI models
IV. Societal implications
V. Technical defense mechanisms
VI. Cross-platform strategies
VII. Ethical considerations
VIII. Proposed integrated defense framework
IX. Discussion
X. Conclusion
References - Privacy and Copyright Protection in Generative AI: A Lifecycle Perspective / 2311.18252 / ISBN:https://doi.org/10.48550/arXiv.2311.18252 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Legal Basis of Privacy and Copyright Concerns over Generative AI
3 Mapping Challenges throughout the Data Lifecycle
4 Lifecycle Approaches
5 Conclusion
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
- Introduction
Software system features
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
4 Conclusions
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
- Abstract
1. Introduction
4. Method
6. Discussion
7. Conclusion - Contra generative AI detection in higher education assessments / 2312.05241 / ISBN:https://doi.org/10.48550/arXiv.2312.05241 / Published by ArXiv / on (web) Publishing site
- 2. The pitfalls in detecting generative AI output
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
- 1 Introduction
2 Human intelligence
4 Bias, prejudice, and individuality
6 Measuring intelligence
7 Mathematically modeling intelligence
8 Consciousness
9 Augmenting human intelligence
12 Large language models and Generative AI
14 Wrong numbers
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
- 2 Related work
3 Methodology
4 Results & analysis
References - Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site
- 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
- 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
6 Related Works
References
7 Ethical Impacts
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
- ...
Data Collection
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
- Literature
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
Artificial intelligence – concept and ethical background
Culturally responsive AI – current landscape
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
III. Research methodology
IV. Results
References
Appendix B – Interview Questionnaire - 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
- 1 Objective
2 Background and significance
3 Materials and methods
4 Results
5 Discussion
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
- 2 The Reign of Algorithmic Fairness
4 Limitations
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
- 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
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
- 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
- 2. Foundations of AI-driven threat intelligence
3. Autonomous threat hunting: conceptual framework
4. State-of-the-art AI techniques in autonomous threat hunting
6. Case studies and applications
8. Future directions and emerging trends
9. Conclusion
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
4. LLMs in educational and developmental psychology
5. LLMs in social and cultural psychology
6. LLMs as research tools in 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
- 2. The generation of synthetic data
3. The usage of synthetic data
4. Risks and Challenges in Utilizing Synthetic Datasets for AI
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
- Abstract
I. Introduction
II. Related work
III. Methodology: model development
IV. System design
V. Evaluation
VII. Conclusion
References - AI Ethics Principles in Practice: Perspectives of Designers and Developers / 2112.07467 / ISBN:https://doi.org/10.48550/arXiv.2112.07467 / Published by ArXiv / on (web) Publishing site
- III. Methods
IV. Results
V. Discussion and suggestions
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
- Background and significance
Materials and methods
Results
Discussion
Supplementary material - 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
III. Discussion and Recommendations
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
- 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
Bibliography - Business and ethical concerns in domestic Conversational Generative AI-empowered multi-robot systems / 2401.09473 / ISBN:https://doi.org/10.48550/arXiv.2401.09473 / Published by ArXiv / on (web) Publishing site
- 2 Background
3 Method
4 Results
5 Discussion
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
- 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
- 2. Background
3. Use cases representing different image data types and their challenges and status for sharing
References
International Working Group Members who contributed to the discussion and writing of the white paper (in alphabetical order) - Beyond principlism: Practical strategies for ethical AI use in research practices / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site
- 1 The “Triple-Too” problem of AI ethics
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
- 1 Introduction
2 Related work
3 Methods
4 RAI tool evaluation practices
5 Towards evaluation of RAI tool effectiveness
6 Limitations
7 Conclusion
References
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
3 Detection
5 Discussion
6 Conclusion
References
Authors' bios - 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
- 1. Introduction
2. Related literature
3. Research study
4. Findings
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
1. Introduction
2. Literature review
3. Methodology
4. Discussion
5. Conclusion
References
B. An Example Dialog With Sentiment Analysis - 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
- 3 Moral and ethical obligations when developing crossover AI technology
4 Recommendations to address threats posed by crossover AI technology
References - (A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice / 2402.01864 / ISBN:https://doi.org/10.48550/arXiv.2402.01864 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Related work and our approach
3 Methods: case-based expert deliberation
4 Results
5 Discussion
6 Conclusion
References
A Provided AI response strategies and examples
B Workshop participant information - 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
- 4 The POLARIS framework
5 POLARIS framework application
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
- 2. Background
4. Proposed framework
5. The framework in practice
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
- 1 Introduction
2 Background
4 Challenges, Threats and Limitations
5 Findings
7 Methodological Lessons Learned
A List of Included Studies
Data Availability Statement
References
Authors - Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist / 2311.02107 / ISBN:https://doi.org/10.48550/arXiv.2311.02107 / Published by ArXiv / on (web) Publishing site
- Introduction
Methods
Results
Discussion
Data sharing
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
- 4. Results
Ethics statement
References - I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench / 2401.17882 / ISBN:https://doi.org/10.48550/arXiv.2401.17882 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
3 Awareness in LLMs
4 Awareness Dataset: AWAREEVAL
5 Experiments
References
A AWAREEVAL Dataset Details
B Experimental Settings & Results - Mapping the Ethics of Generative AI: A Comprehensive Scoping Review / 2402.08323 / ISBN:https://doi.org/10.48550/arXiv.2402.08323 / Published by ArXiv / on (web) Publishing site
- 3 Results
4 Discussion
References - Taking Training Seriously: Human Guidance and Management-Based Regulation of Artificial Intelligence / 2402.08466 / ISBN:https://doi.org/10.48550/arXiv.2402.08466 / Published by ArXiv / on (web) Publishing site
- 2 Emerging Management-based
AI Regulation
4 Techniques of Human-Guided Training
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
2 Analysis of the Terminology
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
- III. Unified Evaluation Framework For LLM
Benchmarks
V. Processual Elements
VII. Discussions
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
5. Open Challenges for Free-Formed AI Collectives
References
C. Public Good 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
2 Related Work
3 CosmoAgent Simulation Setting
4 CosmoAgent Architecture
5 Evaluation
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
- Introduction
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
- 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
6 Conclusion: Navigating the future of AI and HCI within the EU AI Act framework
References - Multi-stakeholder Perspective on Responsible Artificial Intelligence and Acceptability in Education / 2402.15027 / ISBN:https://doi.org/10.48550/arXiv.2402.15027 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background
3 Materials and Methods
6 Discussion
References
Appendix 1 Scenarios
Appendix 2 Modified psychometric scales - 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
III. Ethical Considerations and Bias in AI-Driven Software Development for Autonomous Vehicles
IV. AI’S Role in the Emerging Trend of Internet of Things (IOT) Ecosystem for Autonomous Vehicles
V. Review of Existing Research and Use Cases
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
- 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
- 3 Methodology
4 Results
5 Discussion
References
A Survey Questions - 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
- 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
- Abstract
Part 1. Study design
Part 2. A new train-test split for prompt development and few-shot learning
Part 5. Interpretability of generative models
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
- I. Introduction & Motivation
II. Background & Literature Review
III. The AI-Enhanced CTI Processing Pipeline
IV. Challenges and Considerations
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
- 1 Introduction
2 AI Model Improvements with Human-AI Teaming
3 Effective Human-AI Joint Systems
4 Safe, Secure and Trustworthy AI
5 Applications
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
- 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
- B Baseline Setup
- 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
- 2. What is AGI
3. The Potentials of AGI in Transforming Future Education
5. Discussion
6. Conclusion
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
3. Data
4. Methods
6. Discussion and Conclusion
References - 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
- 3. Analysis
4. Discussion
5. Research Limitations
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
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
3 Research Methodology
4 Results of the Systematic Literature Review
5 Towards Privacy- and Security-Aware Framework for Ethical AI
6 Discussion and Limitations
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
- 7 Ethic Impact
References - Trust in AI: Progress, Challenges, and Future Directions / 2403.14680 / ISBN:https://doi.org/10.48550/arXiv.2403.14680 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
3. Findings
4. Discussion
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
- Method
Results
AI Ethics Development Phases Based on Keyword Analysis
Key AI Ethics Issues
Key Gaps
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
- Abstract
Introduction
Methodology
Data
Results
Conclusion
Web Appendix A: Analysis of the Disinformation Manipulations - The Journey to Trustworthy AI- Part 1 Pursuit of Pragmatic Frameworks / 2403.15457 / ISBN:https://doi.org/10.48550/arXiv.2403.15457 / Published by ArXiv / on (web) Publishing site
- 2 Trustworthy AI Too Many Definitions or Lack Thereof?
4 AI Regulation: Current Global Landscape
5 Risk
8 Implementation Framework
9 A Few Suggestions for a Viable Path Forward
11 About the Authors
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
A Possible Solution to These Concerns With Government Regulation
References - The Pursuit of Fairness in Artificial Intelligence Models A Survey / 2403.17333 / ISBN:https://doi.org/10.48550/arXiv.2403.17333 / Published by ArXiv / on (web) Publishing site
- 3 Conceptualizing Fairness and Bias in ML
5 Ways to mitigate bias and promote Fairness
6 How Users can be affected by unfair ML Systems
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
- 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
3 RQ1: What Factors Influence Members’ “Licens to Critique” when Discussing AI Ethics with their Team?
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
- 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
- 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
- 2 Applications of Large Language Models in Legal Tasks
4 Legal Problems of Large Languge Models
5 Data Resources for Large Language Models in Law
References - A Review of Multi-Modal Large Language and Vision Models / 2404.01322 / ISBN:https://doi.org/10.48550/arXiv.2404.01322 / Published by ArXiv / on (web) Publishing site
- Abstract
2 What is a Language Model?
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
- III. Study Design
IV. Results
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
- 1 Introduction
2 Background
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
II. Preliminaries
III. Proposed Design: IBIS
IV. Detailed Construction
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
- A Primer
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
- 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
- Authors
- 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 - AI Alignment: A Comprehensive Survey / 2310.19852 / ISBN:https://doi.org/10.48550/arXiv.2310.19852 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Learning from Feedback
3 Learning under Distribution Shift
4 Assurance
5 Governance
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
- 3 Remote Biometric Identification and the AI Act
5 Research Questions
7 Discussion
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
- 1 Introduction
3 Generative Ghosts: A Design Space
4 Benefits and Risks of Generative Ghost
5 Discussion
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
- 2 The Lower Status of Ethics Work within AI Cultures
3 Automated Model Cards: Legitimacy via Quantified Objectivity
5 Alternative AI Ethics: Space for Embodied Complaints
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
- Recommenda5ons
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
- 1 Introduction
2 Background and Related Work
3 Methodology
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
- Abstract
I. Introduction
II. Literature Review
III. Proposed Methodology
V. Conclusion
References - 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
- 2 Robot Rights: the Debate
3 The Robots at Issue
4 The Machines Like us Argument: Mistaking the Map for the Territory
6 Posthumanism
7 The Legal Perspective
8 The Troubling Implications of Legal Rationales for Robot Rights
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
4 DECAI: Design-Enhanced Control of AI Systems
5 Case Studies
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
- Abstract
1 Introduction
2 EU Public Policy Analysis
3 A Geo-Political AI Risk Taxonomy
4 European Union Artificial Intelligence Act
5 Conclusion
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
- 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
- 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
- 2 Audit the process, not just the product
3 3 Governance for safety
4 4 Auditing standards body, not standard audits
5 Conclusion
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
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
- 2 Disentangling Replicability of Model Performance Claiim and Replicability of
Social Claim
3 How Claim Replicability Helps Bridge the Responsiblity Gap
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
V. Conclusion - 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
2 Mechanistic Agency: A Common View in AI Practice
3 Volitional Agency: an Alternative Approach
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
- 2 Towards Ethical and Engaging AI Interfaces for Children: a Comprehensive
Framework
3 Best Practices for AI UI/UX Design for Children
4 Metrics for Assessing Trustworthiness, Reliability, and Safety in Human-AI Interaction
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
3 Substantive and Procedural Transparency are Necessary for Deploying Effective and Ethical AI systems
4 Building Towards Better Governance of Government AI - 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
- II. Discrimination in Law
IV. Criteria for the Selection of Fairness Methods
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
References - 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
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
- 2 How can organizations participate
- 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 Healthcare
5 Law
6 Ethics
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
- 1. Introduction
2. Current State of AWS - 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
III. Data and Methodology
IV. Bibliometric Portraits of Responsible AI
References
Authors - 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
1 Introduction
2 Related Work
4 Results
5 Discussion
6 Conclusion
References - 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
- 3 Proposed Organizational Forms
4 Interaction Mechanisms
References - 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
- 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
IV. Privacy of AIGC in 6G Network
V. Fairness of AIGC in 6G Network
VI. Case Study
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
- 1 Introduction
2 Related Work
4 Method for Generating Responsible AI Guidelines
5 Evaluation of the 22 Responsible AI Guidelines
6 Discussion
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
3 Methods
4 Users’ Experiences and Challenges with ChatGPT
5 Analyses of the Design Process
7 Discussion
8 Limitations and Future Work
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
- 1.
Introduction
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
Design implications for LLM agents
Conclusion
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
- 5 Conclusion: Politically Legitimate Intelligence
Acknowledgments
References - 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
- 2 Related Work
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
- Abstract
1. Introduction
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
- 4. Who Provides the Human Feedback?
5. What Is the Format of Human Feedback?
7. Which Traditional Social-Choice-Theoretic Concepts Are Most Relevant?
8. How Should We Account for Behavioral Aspects and Human Cognitive Structures?
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
- Abstract
1 Introduction
2 Materials
3 Results
4 Discussion
5 Conclusions
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
References
Appendix S: Multiple Adversarial LLMs - Using ChatGPT for Thematic Analysis / 2405.08828 / ISBN:https://doi.org/10.48550/arXiv.2405.08828 / Published by ArXiv / on (web) Publishing site
- 3 Pilot-testing: UN Policy Documents Thematic Analysis Supported by GPT
5 Discussion and Limitations
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
- 4 RQ3: Which Regulatory Strategies Can Be
Employed to Address These Negative
Consequences?
5 Conclusions and Outlook
6 Ethical Disclaimer and Acknowledgements - 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
- 2.MT Critical Errors
4.Error Analysis
6. Conclusion
7. Bibliographical References - 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
4 The Narrow Depth of Industry’s Responsible AI Research
5 The Narrow Breadth of Industry’s Responsible AI Research
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
- 1 Introduction
2 Related Work
3 The Audit Procedure
4 Conducting the Pilots
5 Lessons Learned from the Pilots
6 Conclusion and Outlook
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
- I. Introduction
II. Threat Intelligence
III. Vulnerability Assessment
IV. Network Security
V. Privacy Preservation
VI. Awareness
VIII. Ethical LLMs
IX. Challenges and Open Problems
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
- Results
Methods in clinical AI fairness research
Discussion
Methods
Reference
Additional material - The ethical situation of DALL-E 2 / 2405.19176 / ISBN:https://doi.org/10.48550/arXiv.2405.19176 / Published by ArXiv / on (web) Publishing site
- 5 Technology and society, a complex relationship
6 Technological mediation - 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
- Abstract
1. Introduction
2. Anticipated AI Use for Children
3. Discussion
4. Conclusion
Bibliography - 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
2. Related Work
3. Method
5. Interview Results: Opportunities and Concerns of Using LLMs in the Frontline
6. Discussion
A. Appendix - The AI Alignment Paradox / 2405.20806 / ISBN:https://doi.org/10.48550/arXiv.2405.20806 / Published by ArXiv / on (web) Publishing site
- 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
4 Geo-Privacy and Privacy-preserving Measures
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
1 Introduction
2 Related Work
3 Framework
4 Discussion
Ethics Statement
References
A DVC Dataset: Domestic Violence Cases - 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. - 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
- Introduction
II. Risk Characteristics of LLMs
IV. Impact of Alignments on Corporate Investment Forecasts
V. Robustness: Transcript Readability and Investment Score Predictability
VI. Conclusions
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
- 3 ML model construction
4 Fairness violation analysis in BRIO
5 Risk assessment in BRIO
7 Revenue analysis
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
- 3. Related Work
4. Desiderata
5. Methodology
6. Discussion
7. Conclusions
References
Appendix A. Terminology
Appendix B. Retrieval Methodology - MoralBench: Moral Evaluation of LLMs / 2406.04428 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Related Work
References - Can Prompt Modifiers Control Bias? A Comparative Analysis of Text-to-Image Generative Models / 2406.05602 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Related Work
3. Bias Evaluation
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
2 Theories and Components of Deception
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
- Ethics of AI for Writing Papers
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
- Abstract
1 Introduction
2 Theoretical Background
3 Methodology
4 Findings
6 Conclusions and Recommendations
References
Appendix B: Collected data summary - 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
- Abstract
1 Introduction
2 Why Ethics Matter in LLM Attacks?
3 Potential Misuse and Security Concerns
4 Towards Ethical Mitigation: A Proposed Methodology
6 Ethical Response to LLM Attacks - 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
- 4 Global Regulatory Landscape of AI
5 Generative AI: The New Frontier
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
- 2 Fairness and AI
3 Assuring fairness across the AI lifecycle
4 Assuring AI fairness in healthcare
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
- 2 Background and related work
3 Methodology
4 Results
REFERENCES - 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
- I. Introduction
II. Foundations and Integration of SI and LLM
III. Federated LLMs for Smarm Intelligence
References - 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
- Abstract
I. Introduction
II. Selection of application
III. Analysis
IV. Conclusion
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
- 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
- 2 BEYOND RECOMMENDATIONS:
ENHANCING CRITICAL THINKING WITH
GENERATIVE AI
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
- 2 Large Language Model Risks
3 Strategies in Securing Large Language models
4 Challenges in Implementing Guardrails
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
- 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
- Abstract
1 INTRODUCTION
2 RELATED WORK
4 RESULTS
5 DISCUSSION AND IMPLICATIONS
8 ACKNOWLEDGEMENTS
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
- 2 Background
3 Limitations of RLxF
4 The Internal Tensions and Ethical Issues in RLxF
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
- I. INTRODUCTION AND MOTIVATION
II. BACKGROUND
III. ATTACKS ON DT-INTEGRATED AI ROBOTS
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
- Art Practice: Human Reactions to Synthetic
Fake Content
Emphasizing Reasoning Over Detection
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
- II. UNDERSTANDING GENAI SECURITY
III. CRITICAL ANALYSIS
IV. SECGENAI FRAMEWORK REQUIREMENTS SPECIFICATIONS
V. DISCUSSIONS AND RECOMMENDATIONS
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
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
- Abstract
1 Introduction
2 Why audit generative AI systems?
3 How to audit generative AI systems?
4 Governance audits
5 Model audits
6 Application 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
- 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 - Operationalising AI governance through ethics-based auditing: An industry case study / 2407.06232 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
4. An ‘ethics-based’ AI audit
5. Methodology: An industry case study
6. Lessons learned from AstraZeneca’s 2021 AI audit
7. Limitations
8. Conclusions
REFERENCES
APPENDIX 1 - Auditing of AI: Legal, Ethical and Technical Approaches / 2407.06235 / Published by ArXiv / on (web) Publishing site
- 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
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
- 2 Reasons for automated moral decision making
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
- 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 - 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
- AUTHORS
- 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
- 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
- 3 Conceptual Foundations
4 Design Framework
5 Case Studies - 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
- III. Method
IV. Evolution of Affective Robots for Well-Being
VI. Future Opportunities in Affective Robotivs for Well-Being
References
Authors Bios - 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
- 1 Introduction
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
- 2 Literature Review
5 Discussion
References - 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 in literature reviews and evidence synthesis
Applications of generative AI to real-world evidence (RWE):
Applications of generative AI to health economic modeling
Limitations of generative AI in HTA applications
Policy landscape
Glossary
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
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
- Abstract
Introduction
Proposed Approach to Determining High-Consequence Biological Capabilities of Concern
Next Steps for AI Biosecurity Evaluations - 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
- 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
References
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
- 1. Introduction
3. Honest Computing reference specifications
4. Discussion
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
V. Benchmarking with Chat GPT4 Default Interface
VI. Discussion
VII. Conclusion
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
- 1 Introduction
2 Technology Mediated Nudging
3 Examples of Biases
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
1 Introduction
2 Theoretical Lens: Expanding Views on Algorithmic Risks and Harms
3 Methods: Snowball and Structured Search
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
3. Children’s Privacy in the US
4. State-level Privacy Regulations in the US
5. Regulations on Synthetic Data for AI - 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
- 1 Introduction
2 Related Work
3 Methodology
4 Findings
6 Discussion and Future Work
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
- 4. Passive Deepfake Authentication Methods
5. Deepfakes Detection Method on Realistic Scenarios
6. Active Authentication
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
- 1 Introduction
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
- 1 Introduction
3 Methodology
4 Results
5 Discussion and Implications
6 Threats to Validity
7 Conclusions and Future Work
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
- 1 Introduction
2 Related Work
3 Methods
4 Large-Scale Surveys of AI in the Literature
5 Discussion
6 Conclusion
7 Research Ethics and Social Impact
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
- 1. Introduction
2. Related Work
3. Proposed framework
4. Model architecture and training parameters
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
III. Methodology
IV. Graphical User Interface (GUI)
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
4 Exploring epistemic challenges
Bibliography - 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
- References
- Between Copyright and Computer Science: The Law and Ethics of Generative AI / 2403.14653 / ISBN:https://doi.org/10.48550/arXiv.2403.14653 / Published by ArXiv / on (web) Publishing site
- Introduction
I. The Why and How Behind LLMs
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
3 Data Sources
4 Data Preparation
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
- II. Generative AI
III. Language Modeling
IV. Challenges of Generative AI and LLMs
References
Authors - 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
- 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
- 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
3 Visualization Atlas Design Patterns
4 Interviews with Visualization Atlas Creators
5 Visualization Atlases Genres
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
- I. Introduction
II. Neuro-Symbolic AI
III. Autonomy in Military Weapons Systems
IV. Military Applications of Neuro-Symbolic AI
V. Challenges and Risks
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
- Executive Summary
Avoiding harm
Ethics Board Review
Obtaining Consent
Accurate Reporting and Reproducibility
Use of Generative AI in CS Conference Publications
Conclusions
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
- 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 - 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 - 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
- Introduction
Related Work
Findings
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
- Abstract
1 Main
2 Promises
3 Challenges
4 Needs
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
- 5 Overall Ethical Requirements (O)
6 Fairness (F)
7 Privacy and Data Protection (P)
9 Sustainability (SU)
10 Transparency and Explainability (T)
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
- 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
- I. Introduction
II. Related Work
III. Generative AI
IV. Attack Methodology
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
2 Preliminaries
3 Multimodal Medical Studies
4 Contrastice Foundation Models (CFMs)
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
- 1 Introduction
3 Methodology
4 Background
5 Explanation Requirements and Legal Explanatory Goals
6 A Categorisation of XAI in Terms of Explanatory Goals
8 Instructions for Use & Discussion of Findings
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
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
- 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
- 1 Introduction
3 LLMs in Zero-Shot Biomedical Applications
4 Adapting General LLMs to the Biomedical Field
5 Discussion
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
3. How GenAI Could Make a Difference
4. Risks and Caveats
5. Annoyances or Dealbreakers?
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
- Mapping ethical challenges in complexity science
Practical considerations for ethical actions in complexity science
References - 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
Methods
Results
Discussion
Conclusion
Ethic Statement
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
3 Method
4 Findings - 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
3 Data Details
7 Limitations
8 Dataset Disclaimers and Terms
10 Appendix - 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 - 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
- Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site
- 13 Ethical requirements at a glance
References - 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
- 4 Easy and Hard Problems in Machine Creativity
5 Practical Implications
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
- Abstract
Introduction
Part I Modelling - Machine learning, computer vision and processing 1 Machine learning and computer vision for Earth observation
2 Advanced processing and computing
4 Explainable AI and causal inference
Part III Communicating - Machine-user interaction, trustworthiness & ethics 6 User-centric Earth observation
7 Earth observation and society: the growing relevance of ethics
Conclusions
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
- 1 Introduction
2 Related Work
5 Retrieval-Augmented Generation
6 Experiment
7 Results
8 Discussion
9 Limitations
10 Ethical Considerations
References
E Used Prompts
G Model Answers Analysis - 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
- Introduction
Argument from a holistic and humanistic perspective
Argument from Authority: Ethics by committee
Argument by analogy: The case of sustainability
Reductio ad absurdum: Argument by assuming the opposite scenario leading to unacceptable consequences
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: Ethics (the stereotype
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
- Abstract
1 Introduction
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
- Introduction
Background
Comprehending Advanced Large Language Models and its Capabilities
Considerations for Advanced Large Language Models and Policy-Making - 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
- 1 Introduction
3 Methodology
5 Future Directions - 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
- Abstract
1. Introduction
2. Methodology
3. Results
4. Discussion
References - 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
References - Navigating LLM Ethics: Advancements, Challenges, and Future Directions / 2406.18841 / ISBN:https://doi.org/10.48550/arXiv.2406.18841 / Published by ArXiv / on (web) Publishing site
- 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
- 3 Research Design
4 Results
5 Open Challenges and Future Research Directions (RQ5)
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
- Abstract
Introduction
1 Related Work
2 Methodology
5 Discussion
6 Conclusion
References
7 Supplementary Materials - 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
- Abstract
1 Introduction
2 What organizations could document about AI systems
3 Methods
4 Results - 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
- 4 Lessons Learned from the Case Studies
References
Appendix A Technical and Contextual Details for Collaborative Decentralized Cold Supply Chains
Appendix B Technical and Conceptual Details for the Power Systems Case Study - 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
- 2 Related Research
3 Method
4 Findings
5 Discussion
References
Appendices - 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
- 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
- 1 Introduction
2 Background and Related Work
3 Chatbot Ad Engine Design
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
3 XTRUST Construction
4 Experiments
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
- 1 Introduction
2 Views on Intelligence
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
7 Conclusion
8 Acknowledgement
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
- 2. Literature Review
3. Methodology
4. Framework Development
5. Analysis and Discussion - 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
- 1 Introduction
2 Systematic Reviews
5 Aims & Objectives (RQ1)
6 Methodologies & Capabilities (RQ2)
8 Discussion
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
I. Introduction
II. Related Work
III. Current Platform Measures
V. Results
VI. Conclusion
References - Safety challenges of AI in medicine / 2409.18968 / ISBN:https://doi.org/10.48550/arXiv.2409.18968 / Published by ArXiv / on (web) Publishing site
- 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
- Abstract
I Introduction
2 Related Work
3 Methods
4 Results
5 Discussion
6 Conclusion
References - The Gradient of Health Data Privacy / 2410.00897 / ISBN:https://doi.org/10.48550/arXiv.2410.00897 / Published by ArXiv / on (web) Publishing site
- Abstract
2 Background and Related Work
3 The Health Data Privacy Gradient
4 Technical Implementation of a Privacy Gradient Model
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 - 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
III. Research Methodology
IV. Results
V. Discussion
References
APPENDIX A SELECTED STUDIES
APPENDIX C PUBLICATION TRENDS
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
References - 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
- 5 Model Preference and Steerability on Daily Dilemmas
References - 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
Discussion - 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
- 1 Introduction
2 Related Works
3 AI Press System
References
C Prompts for Agents on Press Drafting Module
D Prompts for Agents on Press Polishing Module - 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
- 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
- Appendix D
A Note on Terminology
- 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
- 2. Related Work
3. Method
5. Discussion
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
- The multiple levels of AI impact
The emerging social impacts of ChatGPT
Discussion - 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
- 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
- III. Research Methodology
IV. Challenges of AWS
V. Opportunities of AWS
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
- 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
- References
- 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 - 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
2 Previous studies
4 Cultural safety dataset - 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
5 Mechanisms of Industry Influence in US AI Policy
6 Mitigating or Preventing Regulatory Capture in AI Policy
8 Conclusion
Ethical Considerations Statement
Acknowledgments
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
- Abstract
1 Introduction
2 Ethics of Resisting LLM Inference
3 Threat Model
4 LLM Adversarial Attacks as LLM Inference Data Defenses
5 Experiments
6 Discussion
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
- 1 Introduction
3 Methodology PCJAILBREAK
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
- Abstract
1 Introduction
2 Related Work
3 Methodology
4 Analysis
References
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
- Abstract
3 Positionality Statementy
4 Study Setup
6 RQ2: Practices of AI Tools
8 RQ4: Expectation and Confrontation Towards The Future
10 Ethical Considerations
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
- II. Background and Concepts
III. Jailbreak Attack Methods and Techniques
IV. Defense Mechanisms Against Jailbreak Attacks
V. Evaluation and Benchmarking
VI. Research Gaps and Future Directions
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
- 1.0 Introduction
2.0 Literature Review
4.0 Results
5.0 Discussions
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
Redefining the Landscape - 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
- Understanding Social Spaces: An Anthropological Ethics Approach
Taxonomies of Harm Must be Vernacularized to be Operationalized
Overgeneral Taxonomies Can Compound Potential Harms
Vernacularization as a General AI Safety Operationalization Methodology
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
IV. Different Factors Improved by Adopting AI-Based Exoskeleton
V. Technical Factors During the System Design
References - Trustworthy XAI and Application / 2410.17139 / ISBN:https://doi.org/10.48550/arXiv.2410.17139 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Trustworthy XAI Vs AI
3 Applications of Trustworthy XAI
4 Future 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
- 2 Background
4 Evaluation
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
- Ethical Challenges Presented by AI
Opportunities for Ethical Leadership in the age of AI
Framework for Ethical Leadership
The Importance of Interdisciplinary Collaboration
Recommendations for Leaders - 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
Task Formulation
Large Language Model Selection
Prompt engineering
Fine-tuning
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
IV. Detection Methods Based on Textual and Multimodal Analysis for Text-to-Image Models
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
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
- Abstract
1 Introduction
2 Related Work
3 Methodology
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
- 1 Introduction
2 Related Work
3 Assessing the Current State of Self-Awareness in Artificial Intelligent Systems
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
- 1 Introduction
3 Trends in advanced AI safety and trustworthiness standardization
4 Conclusion
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
- Abstract
1 Introduction
3 Interactive-Reflective Dialogue Alignment (IRDA) System
4 Study Design & Methodology
7 Discussion
References
Appendices - 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
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
- Abstract
1 Introduction
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
- 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 - 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
- 1 Introduction
4 CaseStudies and Results
5 Discussion
7 Conclusion
Acknowledgement
References - 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
- The Evolution of Responsible AI for Assessment
Integrating Classical Validation Theory and Responsible AI - 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
- 1 Introduction
2 Related Work
References - 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
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
- Abstract
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
- 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
- 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
- 6 Directions for future research
7 Conclusions - 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
- References
- How should AI decisions be explained? Requirements for Explanations from the Perspective of European Law / 2404.12762 / ISBN:https://doi.org/10.48550/arXiv.2404.12762 / Published by ArXiv / on (web) Publishing site
- 2 Related Work
3 Properties of XAI-Methods (Possibly) Relevant for their Legal Use
4 Legal Requirements: Decision-Centric
5 Legal Requirements: Model-Centric
6 Discussion
7 Summary
References - A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions / 2406.03712 / ISBN:https://doi.org/10.48550/arXiv.2406.03712 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Background and Technology
III. From General to Medical-Specific LLMs
IV. Improving Algorithms for Med-LLMs
V. Applying Medical LLMs
VI. Trustworthiness and Safety
VII. Future Directions
References - The doctor will polygraph you now: ethical concerns with AI for fact-checking patients / 2408.07896 / ISBN:https://doi.org/10.48550/arXiv.2408.07896 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Clinical, Technical, and Ethical Concerns
3. Methods
4. Results
5. Discussion
References: - Nteasee: A mixed methods study of expert and general population perspectives on deploying AI for health in African countries / 2409.12197 / ISBN:https://doi.org/10.48550/arXiv.2409.12197 / Published by ArXiv / on (web) Publishing site
- 2 Methods
3 Results
5 Conclusion
References - Large-scale moral machine experiment on large language models / 2411.06790 / ISBN:https://doi.org/10.48550/arXiv.2411.06790 / Published by ArXiv / on (web) Publishing site
- Introduction
Results
Discussion
Supporting information
References - Persuasion with Large Language Models: a Survey / 2411.06837 / ISBN:https://doi.org/10.48550/arXiv.2411.06837 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Application Domains
3 Factors Influencing Persuasiveness
4 Experimental Design Patterns
5 Ethical Considerations
6 Conclusion and Future Directions
References - Enhancing Accessibility in Special Libraries: A Study on AI-Powered Assistive Technologies for Patrons with Disabilities / 2411.06970 / ISBN:https://doi.org/10.48550/arXiv.2411.06970 / Published by ArXiv / on (web) Publishing site
- 4. Overview of Assistive Technology and AI-Based Assistive Technology
5. Methodology
6. Data Collection Method
7. Case Studies:
8. Collection Development and Data Analytics
9. Conclusion
References - Collaborative Participatory Research with LLM Agents in South Asia: An Empirically-Grounded Methodological Initiative and Agenda from Field Evidence in Sri Lanka / 2411.08294 / ISBN:https://doi.org/10.48550/arXiv.2411.08294 / Published by ArXiv / on (web) Publishing site
- 3 Proposed LLM4Participatory Research
Framework
4 Field Work and Implementation Insights
References - The EU AI Act is a good start but falls short / 2411.08535 / ISBN:https://doi.org/10.48550/arXiv.2411.08535 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Methodology
3 Results
4 Discussion
References - Human-Centered AI Transformation: Exploring Behavioral Dynamics in Software Engineering / 2411.08693 / ISBN:https://doi.org/10.48550/arXiv.2411.08693 / Published by ArXiv / on (web) Publishing site
- III. Research Method
IV. Results
References - Programming with AI: Evaluating ChatGPT, Gemini, AlphaCode, and GitHub Copilot for Programmers / 2411.09224 / ISBN:https://doi.org/10.48550/arXiv.2411.09224 / Published by ArXiv / on (web) Publishing site
- 8 Ethical Issues
10 Limitations
References - Generative AI in Multimodal User Interfaces: Trends, Challenges, and Cross-Platform Adaptability / 2411.10234 / ISBN:https://doi.org/10.48550/arXiv.2411.10234 / Published by ArXiv / on (web) Publishing site
- IV. Current App Frameworks and AI Integration
VI. Limitations, Challenges, and Future Directions for AI-Driven Interfaces - Bias in Large Language Models: Origin, Evaluation, and Mitigation / 2411.10915 / ISBN:https://doi.org/10.48550/arXiv.2411.10915 / Published by ArXiv / on (web) Publishing site
- References
1. Introduction
2. Intrinsic Bias
3. Extrinsic Bias
5. Bias Mitigation - Framework for developing and evaluating ethical collaboration between expert and machine / 2411.10983 / ISBN:https://doi.org/10.48550/arXiv.2411.10983 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Method - Chat Bankman-Fried: an Exploration of LLM Alignment in Finance / 2411.11853 / ISBN:https://doi.org/10.48550/arXiv.2411.11853 / Published by ArXiv / on (web) Publishing site
- Abstract
2 Related work
3 Experimental framework
4 Results
References - Artificial Intelligence in Cybersecurity: Building Resilient Cyber Diplomacy Frameworks / 2411.13585 / ISBN:https://doi.org/10.48550/arXiv.2411.13585 / Published by ArXiv / on (web) Publishing site
- Paper
Bibliography - GPT versus Humans: Uncovering Ethical Concerns in Conversational Generative AI-empowered Multi-Robot Systems / 2411.14009 / ISBN:https://doi.org/10.48550/arXiv.2411.14009 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Background
3 Method
4 Results
5 Discussion
6 Conclusion
References - Privacy-Preserving Video Anomaly Detection: A Survey / 2411.14565 / ISBN:https://doi.org/10.48550/arXiv.2411.14565 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Foundations of P2VAD
III. P2VAD with non -Identifiable Elements
IV. Desensitized Intermediate Modalities P2VAD
V. Edge-Cloud Intelligencve Empowered P2VAD
VI. Evaluation Benchmarks and Metrics
VII. Discussion
References - Advancing Transformative Education: Generative AI as a Catalyst for Equity and Innovation / 2411.15971 / ISBN:https://doi.org/10.48550/arXiv.2411.15971 / Published by ArXiv / on (web) Publishing site
- 2 Theoretical Framework
6 Ethical Implications of Generative AI in Education
7 Long-Term Implications of Generative AI Integration
9 Future Work - Responsible forecasting: identifying and typifying forecasting harms / 2411.16531 / ISBN:https://doi.org/10.48550/arXiv.2411.16531 / Published by ArXiv / on (web) Publishing site
- 2 Harms in forecasting
3 Methods
4 Findings: typology of harm in forecasting
5 Discussion
7 Conclusions
References - AI-Augmented Ethical Hacking: A Practical Examination of Manual Exploitation and Privilege Escalation in Linux Environments / 2411.17539 / ISBN:https://doi.org/10.48550/arXiv.2411.17539 / Published by ArXiv / on (web) Publishing site
- 4 Methodology
5 Execution
6 Discussion: Benefits, Risks and Limitations
7 Related Work
8 Conclusions and Directions for Further Research
References - Examining Multimodal Gender and Content Bias in ChatGPT-4o / 2411.19140 / ISBN:https://doi.org/10.48550/arXiv.2411.19140 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Related Works
3. Textual Generation Experiment
4. Visual Generation Experiment
6. Conclusion and Future Directions
References
Author - Ethics and Artificial Intelligence Adoption / 2412.00330 / ISBN:https://doi.org/10.48550/arXiv.2412.00330 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. Literature Review
IV. Method
VI. Conclusions
References - Human-centred test and evaluation of military AI / 2412.01978 / ISBN:https://doi.org/10.48550/arXiv.2412.01978 / Published by ArXiv / on (web) Publishing site
- Full Summary
- Artificial Intelligence Policy Framework for Institutions / 2412.02834 / ISBN:https://doi.org/10.48550/arXiv.2412.02834 / Published by ArXiv / on (web) Publishing site
- III. Key Considerations for AI Policy
IV. Framework for AI Policy Development
V. Conclusion
References - Ethical Challenges and Evolving Strategies in the Integration of Artificial Intelligence into Clinical Practice / 2412.03576 / ISBN:https://doi.org/10.48550/arXiv.2412.03576 / Published by ArXiv / on (web) Publishing site
- Introduction and Motivation
Core Ethical Challenges
Emerging Ideas - Towards a Practical Ethics of Generative AI in Creative Production Processes / 2412.03579 / ISBN:https://doi.org/10.48550/arXiv.2412.03579 / Published by ArXiv / on (web) Publishing site
- Introduction
Ethics for AI in design - Exploring AI Text Generation, Retrieval-Augmented Generation, and Detection Technologies: a Comprehensive Overview / 2412.03933 / ISBN:https://doi.org/10.48550/arXiv.2412.03933 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
II. AI Text Generators (AITG)
III. Retrieval Augmented Generation (RAG)
IV. Tools and Methods for RAG
V. AI Text Detectors (AITD)
VI. Ethical Considerations
VII. Limitations
References - Large Language Models in Politics and Democracy: A Comprehensive Survey / 2412.04498 / ISBN:https://doi.org/10.48550/arXiv.2412.04498 / Published by ArXiv / on (web) Publishing site
- 3. LLM Applications in Politics
4. Future Prospects
References - From Principles to Practice: A Deep Dive into AI Ethics and Regulations / 2412.04683 / ISBN:https://doi.org/10.48550/arXiv.2412.04683 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Preliminaries and definitions
3 How to design regulation-compliant systems: the synergies and conflicts
4 Discussion and future directions
5 Conclusion
References - Employee Well-being in the Age of AI: Perceptions, Concerns, Behaviors, and Outcomes / 2412.04796 / ISBN:https://doi.org/10.48550/arXiv.2412.04796 / Published by ArXiv / on (web) Publishing site
- Introduction
I. Key Concerns on AI and Employee Well-Being
IX. Practical Implications
References - Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground / 2412.05130 / ISBN:https://doi.org/10.48550/arXiv.2412.05130 / Published by ArXiv / on (web) Publishing site
- II AI Practice and Contextual Integrity
III AI Ethics and the notion of AI as uncharted moral territory
VI References - Can OpenAI o1 outperform humans in higher-order cognitive thinking? / 2412.05753 / ISBN:https://doi.org/10.48550/arXiv.2412.05753 / Published by ArXiv / on (web) Publishing site
- 2 Methods
3 Results
References - Political-LLM: Large Language Models in Political Science / 2412.06864 / ISBN:https://doi.org/10.48550/arXiv.2412.06864 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 Preliminaries
3 Taxonomy on LLM for Political Science
4 Classical Political Science Functions and Modern Transformations
5 Technical Foundations for LLM Applications in Political Science
6 Future Directions & Challenges
7 Conclusion
References - Responsible AI in the Software Industry: A Practitioner-Centered Perspective / 2412.07620 / ISBN:https://doi.org/10.48550/arXiv.2412.07620 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Method
References - Trustworthy artificial intelligence in the energy sector: Landscape analysis and evaluation framework / 2412.07782 / ISBN:https://doi.org/10.48550/arXiv.2412.07782 / Published by ArXiv / on (web) Publishing site
- II. Landscape of Trustworthy AI in the EU
III. E-TAI – Methodological Framework for Trustworthy AI in the Energy Domain
References - Digital Democracy in the Age of Artificial Intelligence / 2412.07791 / ISBN:https://doi.org/10.48550/arXiv.2412.07791 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Digital Citizenship: from Individualised to Stereotyped Identities
3. Participation: Civic Engagement and Digital Platforms
4. Representation: Digital and AI Technologies in Modern Electoral Processes
5. Public Sphere and Political Advocacy
6. Conclusions
References - Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact / 2412.07880 / ISBN:https://doi.org/10.48550/arXiv.2412.07880 / Published by ArXiv / on (web) Publishing site
- 2 Preliminaries
3 Formulating the Problem
4 Designing Solution Methods
5 Testing and Deployment
References - Bias in Large Language Models: Origin, Evaluation, and Mitigation / 2411.10915 / ISBN:https://doi.org/10.48550/arXiv.2411.10915 / Published by ArXiv / on (web) Publishing site
- Appendices
- Chat Bankman-Fried: an Exploration of LLM Alignment in Finance / 2411.11853 / ISBN:https://doi.org/10.48550/arXiv.2411.11853 / Published by ArXiv / on (web) Publishing site
- Appendices
- Ethical Challenges and Evolving Strategies in the Integration of Artificial Intelligence into Clinical Practice / 2412.03576 / ISBN:https://doi.org/10.48550/arXiv.2412.03576 / Published by ArXiv / on (web) Publishing site
- Discussion
References