IBM releases AI model toolkit to help developers measure uncertainty

IBM AI toolkit

At its Digital Developer Conference today, IBM open-sourced Uncertainty Quantification 360 (UQ360), a new toolkit focused on enabling AI to understand and communicate its uncertainty. Following in the footsteps of IBM’s AI Fairness 360 and AI Explainability 360, the goal of UQ360 is to foster community practices across researchers, data scientists, developers, and others that might lead to better understanding and communication around the limitations of AI.

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Confidence, uncertainty, and trust in AI affect how humans make decisions

In 2019, as the Department of Defense considered adopting AI ethics principles, the Defense Innovation Unit held a series of meetings across the U.S. to gather opinions from experts and the public. At one such meeting in Silicon Valley, Stanford University professor Herb Lin argued that he was concerned about people trusting AI too easily and said any application of AI should include a confidence score indicating the algorithm’s degree of certainty.

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