Topics of Interest
We encourage submissions on any topic within the broad space of responsible AI, including but not limited to:
Adversarial AI and Red Teaming: Approaches for testing and improving AI robustness against adversarial threats.
Fairness and Bias in AI: Techniques to assess and mitigate biases in AI models and data.
Algorithmic Decision-Making and Accountability: Strategies to ensure recourse, interpretability, and transparency in AI-driven systems.
Trust and Reliability in AI Systems: Methods to enhance trust, appropriate reliance, and assurance testing.
Auditing AI Models and Systems: Approaches for evaluating AI applications across sectors, including industry, government, and civic society.
Sociotechnical Perspectives on AI: Research on the cultural, historical, and social implications of AI adoption.
Environmental Considerations in AI: Investigating the sustainability and ecological footprint of AI technologies.
Regulatory, Legal, and Policy Considerations: Governance frameworks, intellectual property, data protection, and regulatory compliance.
Human-Centered AI Design: Participatory, interdisciplinary, and values-sensitive approaches to AI system development.
AI Ethics and Social Impact: Studies on justice, equity, labor implications, and risks associated with AI deployment.
AI Ethics Education: Strategies for integrating responsible AI concepts into curricula and professional training programs
AI Ethics and Social Impact: Studies on justice, equity, labor implications, and risks associated with AI deployment.
Transparency and Explainability: Techniques for documenting, communicating, and improving the interpretability of AI systems.
Risk Management and AI Safety: Technical and policy-based strategies for mitigating AI harms and failures.
We welcome a broad range of perspectives and encourage interdisciplinary submissions that connect responsible AI with other fields of study. Submissions from diverse methodological backgrounds, including theoretical work, position papers, empirical research, case studies, and practical applications, are highly encouraged.