Making Algorithms Trustworthy with David Spiegelhalter
EPISODE 212
|
DECEMBER
19,
2018
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About this Episode
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 the Guest
David Spiegelhalter
University of Cambridge
Resources
- Winton Centre for Risk and Evidence Communication
- Video: NeurIPS 2018 Invited Talk: Making Algorithms Trustworthy: What Can Statistical Science Contribute to Transparency, Explanation and Validation?
- Slides: NeurIPS 2018 Invited Talk: Making Algorithms Trustworthy: What Can Statistical Science Contribute to Transparency, Explanation and Validation?
- Ted Talk: Onora O'neill What we don't understand about trust
- TWIML Presents: NeurIPS Series page
