Can AI Developers Be Incentivized to Debias their Algorithms?

TechTank - A podcast by Brookings Institution - Lunedì

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The prevalence and technical relevance of machine learning algorithms have increased over the years, making predictive decision-making tools part of the everyday lives of online users. Today, it is harder to discern what decisions are made by humans, and the others that rely upon the cognition of machines. On this new episode of the Tech Tank podcast, Darrell West is joined by Nicol Turner Lee, Senior Fellow and the Director of the Center for Technology Innovation who explores the need for a proposed Energy Star rating, or incentive-based rating system to improve the performance and optimization of these online tools.   Hosted on Acast. See acast.com/privacy for more information.

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