Sometimes too convenient: AI under the microscope

Scientists from Tübingen and Toronto call for stronger testing procedures for algorithms

The achievements of artificial intelligence (AI) are usually regarded as success stories: AI translates texts with impressive accuracy, detects cancer in some cases better than doctors. However, it is often forgotten that AI also makes mistakes. An international team of scientists has compiled the various forms these take in a perspectives paper. In it, they focus on how AI learns and how things can go wrong, even though the algorithms perform well in standard testing procedures.

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University of Tübingen
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University of Tübingen
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ELLIS Institute Tübingen, Max Planck Institute for Intelligent Systems & Tübingen Al Center

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