Making Algorithms Trustworthy with David Spiegelhalter

800 800 This Week in Machine Learning & AI

In this, the second episode of our NeurIPS series, we’re joined by David Spiegelhalter, Chair of Winton Center for Risk and Evidence Communication at Cambridge University and President of the Royal Statistical Society.

David, an invited speaker at NeurIPS, presented on “Making Algorithms Trustworthy: What Can Statistical Science Contribute to Transparency, Explanation and Validation?”. In our conversation, we explore the nuanced difference between being trusted and being trustworthy, and its implications for those building AI systems. We also dig into how we can evaluate trustworthiness, which David breaks into four phases, the inspiration for which he drew from British philosopher Onora O’Neill’s ideas around ‘intelligent transparency’.

About David

Mentioned in the Interview

“More On That Later” by Lee Rosevere licensed under CC By 4.0

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