We use computers to help us make (hopefully) unbiased decisions. The problem is that machine-learning algorithms do not always make fair classifications if human bias is embedded in the data used to train them—which is often the case in practice.
New mitigation framework reduces bias in classification outcomes
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HighlightsFree Dark Web Monitoring Stamps the $17 Million Credentials Markets
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HighlightsSmart buildings: What happens to our free will when tech makes choices for us?
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AppsScreenshots have generated new forms of storytelling, from Twitter fan fiction to desktop film
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HighlightsDarknet markets generate millions in revenue selling stolen personal data, supply chain study finds
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SecurityPrivacy violations undermine the trustworthiness of the Tim Hortons brand
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Featured HeadlinesWhy Tesla’s Autopilot crashes spurred the feds to investigate driver-assist technologies – and what that means for the future of self-driving cars
