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Bibliography items where occurs: 151
The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site
Report highlights
Chapter 1 Reseach and Development
Chapter 2 Technical Performance
Chapter 3 Technical AI Ethics
Chapter 4 The Economy and Education
Chapter 5 AI Policy and Governance
Appendix


Exciting, Useful, Worrying, Futuristic: Public Perception of Artificial Intelligence in 8 Countries / 2001.00081 / ISBN:https://doi.org/10.48550/arXiv.2001.00081 / Published by ArXiv / on (web) Publishing site
CCS Concept
2 Background
3 Methodology
4 Findings
References
A Questionnaire - Selected Questions


Ethics of AI: A Systematic Literature Review of Principles and Challenges / 2109.07906 / ISBN:https://doi.org/10.48550/arXiv.2109.07906 / Published by ArXiv / on (web) Publishing site
2 Background
3 Research Method
5 Detail results and analysis
6 Threats to validity
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
4 Results
5 Discussion
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
4 Evaluation of Ethical AI Principles
5 Evaluation of Ethical Principle Implementations
6 Gap Mitigation
7 Threats to Validiity
References


A Framework for Ethical AI at the United Nations / 2104.12547 / ISBN:https://doi.org/10.48550/arXiv.2104.12547 / Published by ArXiv / on (web) Publishing site
Introductionn
1. Problems with AI
2. Defining ethical AI
3. Implementing ethical AI


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


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
Keywords
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
Abstract
1 Introduction
2 Related Work
3 The ESR Process
4 Deployment and Evaluation
5 Discussion
6 Conclusion
A Appendix: Interview Protocol
References


On the Current and Emerging Challenges of Developing Fair and Ethical AI Solutions in Financial Services / 2111.01306 / ISBN:https://doi.org/10.48550/arXiv.2111.01306 / Published by ArXiv / on (web) Publishing site
2 The Need forEthical AI in Finance
3 Practical Challengesof Ethical AI
4 Conclusions & Outlook
References


A primer on AI ethics via arXiv- focus 2020-2023 / Kaggle / on (web) Publishing site
Section 2: History and prospective
Section 3: Current trends 2020-2023
Section 4: Considerations and conclusions


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
3 Methodology
4 Proposed competency framework for responsible AI practitioners
References
Appendix A supplementary material


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


Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects / 2304.08275 / ISBN:https://doi.org/10.48550/arXiv.2304.08275 / Published by ArXiv / on (web) Publishing site
I. Introduction
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
1 Introduction
2 The Question Bank: QB4AIRA
3 Evaluation
4 Conclusion
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
1. Introductioon
4. Corporate Self-Governance
5. AI Literacy and Governance by Citizen
6. Psychology of Trust
7. Propensity to Trust
9. Virtue Ethics
References


From OECD to India: Exploring cross-cultural differences in perceived trust, responsibility and reliance of AI and human experts / 2307.15452 / ISBN:https://doi.org/10.48550/arXiv.2307.15452 / Published by ArXiv / on (web) Publishing site
1. Introduction
Acknowledgments
References


The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site
2. Theory
3. Methodology
4. Ethical Implications of AI Value Chains
5. Future Directions for Research, Practice, & Policy


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


Regulating AI manipulation: Applying Insights from behavioral economics and psychology to enhance the practicality of the EU AI Act / 2308.02041 / ISBN:https://doi.org/10.48550/arXiv.2308.02041 / Published by ArXiv / on (web) Publishing site
2 Clarifying Terminologies of Article-5: Insights from Behavioral Economics and Psychology
3 Enhancing Protection for the General Public and Vulnerable Groups
References


From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence / 2308.02448 / ISBN:https://doi.org/10.48550/arXiv.2308.02448 / Published by ArXiv / on (web) Publishing site
Introduction
What is Generative Artificial Intelligence?
Applications in Military Versus Healthcare
Identifying Ethical Concerns and Risks
GREAT PLEA Ethical Principles for Generative AI in Healthcare
References


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


Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AI / 2308.04448 / ISBN:https://doi.org/10.48550/arXiv.2308.04448 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
4 Centralized regulation in the US context
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
1 Introduction
2 Methodology
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
Abstract
Introduction
Responsibility in War
Computers, Autonomy and Accountability
Moral Injury
Human Factors
AI Workplace Health and Safety Framework
Discussion
Conclusion


The Future of ChatGPT-enabled Labor Market: A Preliminary Study / 2304.09823 / ISBN:https://doi.org/10.48550/arXiv.2304.09823 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Results
3 Discussion
5 Methods
References


A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation / 2305.11391 / ISBN:https://doi.org/10.48550/arXiv.2305.11391 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Large Language Models
3 Vulnerabilities, Attack, and Limitations
5 Falsification and Evaluation
6 Verification
7 Runtime Monitor
8 Regulations and Ethical Use
10 Conclusions
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
Keywords
1 Introduction
2 Background
3 LLM-based penetration testing
6 Final ethical considerations
References


Artificial Intelligence across Europe: A Study on Awareness, Attitude and Trust / 2308.09979 / ISBN:https://doi.org/10.48550/arXiv.2308.09979 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
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
1 Introduction
2 Related works
3 Targeted data augmentation
4 Experiments
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
Abstract
Introduction
Case study
Reflections
References


Exploring the Power of Creative AI Tools and Game-Based Methodologies for Interactive Web-Based Programming / 2308.11649 / ISBN:https://doi.org/10.48550/arXiv.2308.11649 / Published by ArXiv / on (web) Publishing site
3 Emergence of Creative AI Tools and Game-Based Methodologies
4 Enhancing User Experience through Creative AI Tools
6 Unveiling the Potential: Benefits of Interactive Web-Based Programming
7 Navigating Constraints: Limitations of Creative AI and GameBased Techniques
11 Bias Awareness: Navigating AI-Generated Content in Education
13 Case Study Example: Learning Success with Creative AI and Game-Based Techniques
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
1 Introduction
2 Related Work on Data Excellence
5 Results
6 Discussion
7 Conclusions
References


Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph / 2308.13534 / ISBN:https://doi.org/10.48550/arXiv.2308.13534 / Published by ArXiv / on (web) Publishing site
I. Introduction
II. Methods and training process of LLMs
III. Comprehensive review of state-of-the-art LLMs
V. Market analysis of LLMs and cross-industry use cases
VI. Solution architecture for privacy-aware and trustworthy conversational AI
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
2 The evolution of artificial intelligence: from theory to general capabilities
4 Integrating red teaming, blue teaming, and ethics with violet teaming
6 A pathway for balanced AI innovation
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
3 Methods
5 Conclusion


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
3 Theory and method
4 Experiment
References
A Details of datasets


The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / ISBN:https://doi.org/10.48550/arXiv.2308.16538 / Published by ArXiv / on (web) Publishing site
Table of contents and index
Executive summary
1 Introduction
2 Key AI technology in financial services
3 Benefits of AI use in the finance sector
4 Threaths & potential pitfalls
5 Challenges
6 Regulation of AI and regulating through AI
7 Recommendations
References


Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / ISBN:https://doi.org/10.48550/arXiv.2309.00064 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Black box and lack of transparency
3 Bias and fairness
4 Human-centric AI
5 Ethical concerns and value alignment
6 Way forward
7 Conclusion
References


The Impact of Artificial Intelligence on the Evolution of Digital Education: A Comparative Study of OpenAI Text Generation Tools including ChatGPT, Bing Chat, Bard, and Ernie / 2309.02029 / ISBN:https://doi.org/10.48550/arXiv.2309.02029 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Related work
3. ChatGPT Training Process
4. Methods
5. Discussion
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
Contents
Introduction
Part 1 - 1 Generatives Systems: Mimicking Artifacts
Part 1 - 2 Appreciate Systems: Mimicking Styles
Part 2 Art Data and Human–Machine Interaction in Art Creation
Part 2 - 1 Biometric Signal Sensing Technologies and Emotion Data
Part 2 - 3 Photogrammetry / Volumetric Capture
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 4 NFTs and the Future Art Economy
Part 5 - 1 Authorship and Ownership of AI-generated Works of Artt
Part 5 - 3 Democratization of Art with new Technologies
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
8. FUTURE-AI Quality Check
9. Discussion and Conclusion
Acknowledgments
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
Legal References
A Detailed Information on Corpus Content
B Example XML case
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
5 Experiments
6 Conclusions
Appendix
References


Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunities / 2310.08565 / ISBN:https://doi.org/10.48550/arXiv.2310.08565 / Published by ArXiv / on (web) Publishing site
I. Introduction and Motivation
II. AI-Robotics Systems Architecture
III. Survey Approach & Taxonomy
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
Abstract
2 Emotion, Sentience and Morality
3 Proposing a Hybrid Approach
4 AI Governance Principles
5 Towards Moral AI
References


Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks / 2310.07879 / ISBN:https://doi.org/10.48550/arXiv.2310.07879 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background and Related Work
3 Method
4 Taxonomy of AI Privacy Risks
5 Discussion
6 Conclusion
References


ClausewitzGPT Framework: A New Frontier in Theoretical Large Language Model Enhanced Information Operations / 2310.07099 / ISBN:https://doi.org/10.48550/arXiv.2310.07099 / Published by ArXiv / on (web) Publishing site
Introduction
Theoretical Impact of LLMs on Information Operations
ClausewitzGPT and Modern Strategy
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
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
4 Discussion
References
A Consent and Data Collection Processes
C In-class Activity


A Review of the Ethics of Artificial Intelligence and its Applications in the United States / 2310.05751 / ISBN:https://doi.org/10.48550/arXiv.2310.05751 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Literature Review
3. AI Ethical Principles
4. Implementing the Practical Use of Ethical AI Applications
5. Conclusions and Recommendations


A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics / 2310.05694 / ISBN:https://doi.org/10.48550/arXiv.2310.05694 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. WHAT LLMS CAN DO FOR HEALTHCARE? FROM FUNDAMENTAL TASKS TO ADVANCED APPLICATIONS
III. FROM PLMS TO LLMS FOR HEALTHCARE
IV. TRAIN AND USE LLM FOR HEALTHCARE
V. EVALUATION METHOD
VI. IMPROVING FAIRNESS, ACCOUNTABILITY, TRANSPARENCY, AND ETHICS
VII. FUTURE WORK AND CONCLUSION
References


STREAM: Social data and knowledge collective intelligence platform for TRaining Ethical AI Models / 2310.05563 / ISBN:https://doi.org/10.48550/arXiv.2310.05563 / Published by ArXiv / on (web) Publishing site
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
Abstract
1 Introduction
2 Regulation: A Short Introduction
4 Scientific Expertise, Social Media and Regulatory Capture
5 Regulation and NLP (RegNLP): A New Field
References


Ethics of Artificial Intelligence and Robotics in the Architecture, Engineering, and Construction Industry / 2310.05414 / ISBN:https://doi.org/10.48550/arXiv.2310.05414 / Published by ArXiv / on (web) Publishing site
Abstract
4. Systematic Review and Scientometric Analysis
5. Ethical Issues of AI and Robotics in AEC Industry
6. Discussion
7. Future Research Direction
8. Conclusion
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
Evaluation of the Pilot Study
Ethics of GEnerating Native Ads
References


Compromise in Multilateral Negotiations and the Global Regulation of Artificial Intelligence / 2309.17158 / ISBN:https://doi.org/10.48550/arXiv.2309.17158 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. The practice of multilateral negotiation and the mechanisms of compromises
4. Towards a compromise: drafting the normative hybridity
5. Text negotiations as normative testing
6. Conclusion
Notes
Bibliography


Towards A Unified Utilitarian Ethics Framework for Healthcare Artificial Intelligence / 2309.14617 / ISBN:https://doi.org/10.48550/arXiv.2309.14617 / Published by ArXiv / on (web) Publishing site
Introduction
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
2. Methods for Comprehensive Review
3. Clinical Risks
4. Technical Risks
References
Appendix


Autonomous Vehicles an overview on system, cyber security, risks, issues, and a way forward / 2309.14213 / ISBN:https://doi.org/10.48550/arXiv.2309.14213 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Autonomous vehicles
5. Cybersecurity Risks
6. Risk management
9. References


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


An Evaluation of GPT-4 on the ETHICS Dataset / 2309.10492 / ISBN:https://doi.org/10.48550/arXiv.2309.10492 / Published by ArXiv / on (web) Publishing site
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
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
3 Objectives
4 Methodology
5 Relating Case Studies to Indigenous Data Sovereignty and CARE Principles
6 Discussion
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
1 Introduction


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
3. AI-powered personalized learning: Customized learning experiences for learners
4. Blockchain-based credentialing and certification
5. AI-powered assessment and evaluation
7. AI-powered content creation and curation
8. Case studies: AI and blockchain in education
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
4. Proposed Novel Topics in an Ethics of AI Belief
5. Nascent Extant Work that Falls Within the Ethics of AI Belief
References


Ensuring Trustworthy Medical Artificial Intelligence through Ethical and Philosophical Principles / 2304.11530 / ISBN:https://doi.org/10.48550/arXiv.2304.11530 / Published by ArXiv / on (web) Publishing site
Ethical datasets and algorithm development guidelines
Towards solving key ethical challenges in Medical AI
Ethical guidelines for medical AI model deployment
Discussion
Conclusion and future directions


Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineering / 2209.04963 / ISBN:https://doi.org/10.48550/arXiv.2209.04963 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Methodology
3 Governance Patterns
4 Process Patterns
5 Product Patterns
6 Related Work
8 Conclusion
References


The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance / 2307.16787 / ISBN:https://doi.org/10.48550/arXiv.2307.16787 / Published by ArXiv / on (web) Publishing site
Bibliography
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
3 FUTURE-AI Guideline
4 Discussion
References
Appendix A Tables
Appendix B Full Author Affiliations


Language Agents for Detecting Implicit Stereotypes in Text-to-Image Models at Scale / 2310.11778 / ISBN:https://doi.org/10.48550/arXiv.2310.11778 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Agent Design
3 Agent Benchmark
5 Related Work
References
Appendix A Data Details
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
2 AI feedback on specific problematic AI traits
3 Generalization from a Simple Good for Humanity Principle
4 Reinforcement Learning with Good-for-Humanity Preference Models
7 Contribution Statement
References
B Trait Preference Modeling
D Generalization to Other Traits
H Samples
I Responses on Prompts from PALMS, LaMDA, and InstructGPT


The Self 2.0: How AI-Enhanced Self-Clones Transform Self-Perception and Improve Presentation Skills / 2310.15112 / ISBN:https://doi.org/10.48550/arXiv.2310.15112 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Method
4 Findings
5 Discussion
References


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
2 Trifecta of AI Challenges
3 Systematic AI Approach for AGI
4 Systematic AI for Energy Wall
5 System Design for AI Alignment
6 System Insights from the Brain
7 Conclusions
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
Abstract
1 Introduction
3 Arrow-Sen Impossibility Theorems for RLHF
4 Implications for AI Governance and Policy
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
VI. Review Summary
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
4 Equilibrium Alignment: A Prospective Paradigm for Ethical Value Alignmen
References


Moral Responsibility for AI Systems / 2310.18040 / ISBN:https://doi.org/10.48550/arXiv.2310.18040 / Published by ArXiv / on (web) Publishing site
1 Introduction
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
Introduction
AI Ethics in Cybersecurity
Educational Challenges of Teaching AI Ethics in Cybersecurity and Core Ethical Principles
Technical Issues
AI tool-specific educational concerns
Broader educational preparedness for work in AI Cybersecurity
Conclusion
References


Human Participants in AI Research: Ethics and Transparency in Practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Contextual Concerns: Why AI Research Needs its Own Guidelines
3 Ethical Principles for AI Research with Human Participants
4 Principles in Practice: Guidelines for AI Research with Human Participants
Acknowledgments
References
A Evaluating Current Practices for Human-Participants Research
B Placing Research Ethics for Human Participants in Historical Context
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
3 The Meaning Model
4 The Moral Model
A Supplementary Material
References


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


Kantian Deontology Meets AI Alignment: Towards Morally Robust Fairness Metrics / 2311.05227 / ISBN:https://doi.org/10.48550/arXiv.2311.05227 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Overview of Kantian Deontology
4 Deontological AI Alignment
5 Conclusion
References


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
Abstract
1 Introduction
2 Overview of ChatGPT and its capabilities
3 Transformers and pre-trained language models
4 Applications of ChatGPT in real-world scenarios
5 Advantages of ChatGPT in natural language processing
6 Limitations and potential challenges
8 Prompt engineering and generation
9 Future directions for ChatGPT and natural language processing
10 Future directions for ChatGPT in vision domain
11 Conclusion
References


Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies / 2304.07683 / ISBN:https://doi.org/10.48550/arXiv.2304.07683 / Published by ArXiv / on (web) Publishing site
Abstract
II. Sources of bias in AI
III. Impacts of bias in AI
IV. Mitigation strategies for bias in AI
V. Fairness in AI
VI. Mitigation strategies for fairness in AI
VII. Conclusions
References


Towards ethical multimodal systems / 2304.13765 / ISBN:https://doi.org/10.48550/arXiv.2304.13765 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Related Work
3 Crafting an Ethical Dataset
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
VII. The second wave in 2017: rise of RL
X. 2020-2021: the rise of LLMS
XI. 2022-current: beyond language generation
XII. Conclusions
References


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


How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Experiments
Limitations
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
2 UnknownBench: Evaluating LLMs on the Unknown
References
B Confidence Elicitation Method Comparison
C Additional Details of the Dataset Construction


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
Abstract
1. Introduction
2. Chatbots Background and Scope of Research
3. Chatbot approaches overview: Taxonomy of existing methods
4. ChatGPT
5. Applications
6. Open chanllenges
7. Future Research Directions
8. Conclusion
References


Practical Cybersecurity Ethics: Mapping CyBOK to Ethical Concerns / 2311.10165 / ISBN:https://doi.org/10.48550/arXiv.2311.10165 / Published by ArXiv / on (web) Publishing site
Abstract
2 Background
3 Methodology
4 Findings
5 Discussion
7 Conclusion
References


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
Executive Summary
Introduction
The Problem
Harms, Risk, and Liability Practices
Conclusion
Appendix A - What is an Algorithmic Harm? And a Bibliography
About the Author


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
1 Introduction
3 Methods
4 Findings
7 Limitations
References


Assessing AI Impact Assessments: A Classroom Study / 2311.11193 / ISBN:https://doi.org/10.48550/arXiv.2311.11193 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Background
3 Study Design
4 Findings
5 Discussion
References
A Overview of AIIA Instruments


GPT in Data Science: A Practical Exploration of Model Selection / 2311.11516 / ISBN:https://doi.org/10.48550/arXiv.2311.11516 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Background
III. Approach: capturing and representing heuristics behind GPT's decision-making process
IV. Comparative results
V. Conclusion and future work
VI. Future work
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
Abstract
What are other research communities doing?
Suggestions for More Meaningful Engagement with the Impact of RAI Research
References


Large Language Models in Education: Vision and Opportunities / 2311.13160 / ISBN:https://doi.org/10.48550/arXiv.2311.13160 / Published by ArXiv / on (web) Publishing site
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
I. Introduction
II. Extent and impact of generative AI
IV. Risks of generative AI


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


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


RAISE -- Radiology AI Safety, an End-to-end lifecycle approach / 2311.14570 / ISBN:https://doi.org/10.48550/arXiv.2311.14570 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Pre-Deployment phase
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
6. The role of AI in decision-making: ethical implications and potential consequences
7. Establishing responsible AI governance and oversight
8. AI in sensitive domains: healthcare, finance, criminal justice, defence, and human resources
9. Discussion on engaging stakeholders: fostering dialogue and collaboration between developers, users, and affected communities.
10. Conclusion
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
II. US Patent law
III. US Copyright law
IV. Caveart emptor: no free ride for automation
V. Potential harms and mitigation
VI. Conclusion
References


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
3 Transparency and explainability
4 Fairness and equity
5 Responsiblity, accountability, and regulations
6 Environmental impact
References


Deepfakes, Misinformation, and Disinformation in the Era of Frontier AI, Generative AI, and Large AI Models / 2311.17394 / ISBN:https://doi.org/10.48550/arXiv.2311.17394 / Published by ArXiv / on (web) Publishing site
I. Introduction
III. The rise of large AI models
IV. Societal implications
VII. Ethical considerations
References


Navigating Privacy and Copyright Challenges Across the Data Lifecycle of Generative AI / 2311.18252 / ISBN:https://doi.org/10.48550/arXiv.2311.18252 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Legal Basis of Privacy and Copyright Concerns over Generative AI
3 Mapping Challenges throughout the Data Lifecycle
References


Integrating AI into CCTV Systems: A Comprehensive Evaluation of Smart Video Surveillance in Community Space / 2312.02078 / ISBN:https://doi.org/10.48550/arXiv.2312.02078 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Related works
III. System features
IV. System setup and configuration
V. Real-world results and evaluation
References


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


Seeing ChatGPT Through Universities' Policies, Resources and Guidelines / 2312.05235 / ISBN:https://doi.org/10.48550/arXiv.2312.05235 / Published by ArXiv / on (web) Publishing site
3. Literature review


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
6 Measuring intelligence
7 Mathematically modeling intelligence
8 Consciousness
9 Augmenting human intelligence
10 Exceeding human intelligence
11 Control of 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
Abstract
1 Introduction
2 Related work
3 Methodology
4 Results & analysis
5 Discussion
6 Conclusion & future work
References


Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site
III. Ethics: a primer
IV. Guidelines for promoting ethical responsibility
References


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
6 Related Works
References
Appendix A Assessing the Risks of AI Misuse in Scientific Research
Appendix C Detailed Implementation of SciGuard


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


Navigating the generative AI era: Introducing the AI assessment scale for ethical GenAI assessment / 2312.07086 / ISBN:https://doi.org/10.48550/arXiv.2312.07086 / Published by ArXiv / on (web) Publishing site
Problematizing The View Of GenAI Content As Academic Misconduct
The AI Assessment Scale
References


Culturally Responsive Artificial Intelligence -- Problems, Challenges and Solutions / 2312.08467 / ISBN:https://doi.org/10.48550/arXiv.2312.08467 / Published by ArXiv / on (web) Publishing site
Introduction
The concept of multiculturalism and its importance
Artificial intelligence – concept and ethical background
Culturally responsive AI – current landscape
Recommendations
Conclusion
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
I. Introduction
II. Background and motivation
III. Research methodology
IV. Results
V. Discussion
References
Appendix A – Survey Questionnaire
Appendix B – Interview Questionnaire
Author’s Biographies


Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health / 2312.11803 / ISBN:https://doi.org/10.48550/arXiv.2312.11803 / Published by ArXiv / on (web) Publishing site
Abstract
1 Objective
2 Background and significance
4 Results
5 Discussion
References
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
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
Related Work
Methods
Results
References


The Economics of Human Oversight: How Norms and Incentives Affect Costs and Performance of AI Workers / 2312.14565 / ISBN:https://doi.org/10.48550/arXiv.2312.14565 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
II. Theoretical background and hypotheses
III. Method
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
References


Autonomous Threat Hunting: A Future Paradigm for AI-Driven Threat Intelligence / 2401.00286 / ISBN:https://doi.org/10.48550/arXiv.2401.00286 / Published by ArXiv / on (web) Publishing site
Abstract
1. Introduction
2. Foundations of AI-driven threat intelligence
3. Autonomous threat hunting: conceptual framework
4. State-of-the-art AI techniques in autonomous threat hunting
5. Challenges in autonomous threat hunting
6. Case studies and applications
7. Evaluation metrics and performance benchmarks
8. Future directions and emerging trends
References


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


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
5. Conclusions
References


MULTI-CASE: A Transformer-based Ethics-aware Multimodal Investigative Intelligence Framework / 2401.01955 / ISBN:https://doi.org/10.48550/arXiv.2401.01955 / Published by ArXiv / on (web) Publishing site
Abstract
I. Introduction
III. Methodology: model development
IV. System design
V. Evaluation
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
II. Related work
III. Methods
IV. Results
V. Discussion and suggestions
VI. Support mechanisms
References


Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models / 2310.19917 / ISBN:https://doi.org/10.48550/arXiv.2310.19917 / Published by ArXiv / on (web) Publishing site
Abstract
Background and significance
Materials and methods
Results
Discussion
PRISMA 2020 flow diagram and bias handling workflow
References


Resolving Ethics Trade-offs in Implementing Responsible AI / 2401.08103 / ISBN:https://doi.org/10.48550/arXiv.2401.08103 / Published by ArXiv / on (web) Publishing site
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
Abstract
Contents / List of figures / List of tables / Acronyms
1 Introduction
I Understanding bias - 2 Bias and moral framework in AI-based decision making
3 Bias on demand: a framework for generating synthetic data with bias
4 Fairness metrics landscape in machine learning
II Mitigating bias - 5 Fairness mitigation
6 FFTree: a flexible tree to mitigate multiple fairness criteria
III Accounting for bias - 7 Addressing fairness in the banking sector
8 Fairview: an evaluative AI support for addressing fairness
9 Towards fairness through time
Bibliography


Business and ethical concerns in domestic Conversational Generative AI-empowered multi-robot systems / 2401.09473 / ISBN:https://doi.org/10.48550/arXiv.2401.09473 / Published by ArXiv / on (web) Publishing site
Abstract
2 Background
3 Method
4 Results
6 Conclusion
References


FAIR Enough: How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training? / 2401.11033 / ISBN:https://doi.org/10.48550/arXiv.2401.11033 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 FAIR Data Principles: Theoretical Background and Significance
3 Data Management Challenges in Large Language Models
4 Framework for FAIR Data Principles Integration in LLM Development
5 Discussion
References
Appendices


Enabling Global Image Data Sharing in the Life Sciences / 2401.13023 / ISBN:https://doi.org/10.48550/arXiv.2401.13023 / Published by ArXiv / on (web) Publishing site
2. Background
3. Use cases representing different image data types and their challenges and status for sharing
4. Towards global image data sharing
Acknowledgements


Building ethical guidelines for generative AI in scientific research / 2401.15284 / ISBN:https://doi.org/10.48550/arXiv.2401.15284 / Published by ArXiv / on (web) Publishing site
Understand Model Training and Output
Apply AI Beneficially
Use AI Transparently and Reproducibly
References


A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations / 2401.17486 / ISBN:https://doi.org/10.48550/arXiv.2401.17486 / Published by ArXiv / on (web) Publishing site
Abstract
1 Introduction
2 Related work
3 Methods
4 RAI tool evaluation practices
5 Towards evaluation of RAI tool effectiveness
References
A List of RAI tools, with their primary publication
B RAI tools listed by target stage of AI development
D Summary of themes and codes


Detecting Multimedia Generated by Large AI Models: A Survey / 2402.00045 / ISBN:https://doi.org/10.48550/arXiv.2402.00045 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Generation
3 Detection
4 Tools
5 Discussion
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
4 Sense of engagement and responsibility
5 Possible next steps
References


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


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


Commercial AI, Conflict, and Moral Responsibility: A theoretical analysis and practical approach to the moral responsibilities associated with dual-use AI technology / 2402.01762 / ISBN:https://doi.org/10.48550/arXiv.2402.01762 / Published by ArXiv / on (web) Publishing site
2 Establishing the novel aspect of AI as a crossover technology
3 Moral and ethical obligations when developing crossover AI technology
4 Recommendations to address threats posed by crossover AI technology


(A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice / 2402.01864 / ISBN:https://doi.org/10.48550/arXiv.2402.01864 / Published by ArXiv / on (web) Publishing site
1 Introduction
3 Methods: case-based expert deliberation
4 Results
5 Discussion
6 Conclusion
References
A Provided AI response strategies and examples


POLARIS: A framework to guide the development of Trustworthy AI systems / 2402.05340 / ISBN:https://doi.org/10.48550/arXiv.2402.05340 / Published by ArXiv / on (web) Publishing site
1 Introduction
2 Background
3 State of the practice
4 The POLARIS framework
5 POLARIS framework application
References


A Framework for Assessing Proportionate Intervention with Face Recognition Systems in Real-Life Scenarios / 2402.05731 / ISBN:https://doi.org/10.48550/arXiv.2402.05731 / Published by ArXiv / on (web) Publishing site
1. Introduction
2. Background
4. Proposed framework
5. The framework in practice
References