Published Dec 3, 2021

Upol Ehsan on Human-Centered Explainable AI and Social Transparency

Dive into the world of Human-Centered Explainable AI with expert Upol Ehsan as he reveals the critical role of socio-organizational context, transparency, and scenario-based design in fostering trust, accountability, and alignment with human values in AI systems.

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Episode Highlights

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Upol Ehsan on Human-Centered Explainable AI and Social Transparency

Topics covered

Popular Clips

Journey to Human-Centered AI

Trust and Accountability

Understanding Explainability

Social Transparency in Human-AI Collaboration

Exploring Explainable XAI

Transparency in AI

Making Context Visible

Exploring Interdisciplinary AI

Human Centered AI

Social Transparency Challenges

Sociotechnical Perspective

Firewall Bloat

Trust and Transparency

Sociotechnical Challenges

Episode Highlights

AI in Practice

Explainability in AI

Human-Centered AI

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Vera Liao: AI Explainability and Transparency

Ben Green: "Tech for Social Good" Needs to Do More

Catherine Olsson and Nelson Elhage: Anthropic, Understanding Transformers

Azeem Azhar: The Exponential View

Irene Solaiman: AI Policy and Social Impact

Joe Edelman: Meaning-Aligned AI

Anant Agarwal: AI for Education

Been Kim: Interpretable Machine Learning

Arjun Ramani & Zhengdong Wang: Why Transformative AI is Really, Really Hard to Achieve

Joon Park: Generative Agents and Human-Computer Interaction

Terry Winograd: AI, HCI, Language, and Cognition

Evan Hubinger on Effective Altruism and AI Safety

Venkatesh Rao: Protocols, Intelligence, and Scaling

Daniel Situnayake: AI on the Edge

Michael Levin & Adam Goldstein: Intelligence and its Many Scales

Upol Ehsan on Human-Centered Explainable AI and Social Transparency

Topics covered

Popular Clips

Episode Highlights

AI in PracticeUpol Ehsan examines the intricate relationship between trust and accountability in AI systems, highlighting the importance of socio-organizational context. He also explores scenario-based design as a method to enhance AI understanding and decision-making.

AI in Practice

Explainability in AIUpol Ehsan, an expert in Explainable AI, explores the nuances of making AI systems transparent and understandable. He discusses the importance of human-centered approaches and the challenges of avoiding pitfalls in AI explanations.

Explainability in AI

Human-Centered AIUpol Ehsan explores the importance of social transparency and human-centered design in Explainable AI (XAI). He emphasizes the need for AI systems to align with human practices and values, enhancing accountability and usability.

Human-Centered AI

Related Episodes