Playlist (4 talks)
The inherent bias in our technology

These talks reveal how our technology often reflects the unconscious biases and prejudices we hold.
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Playlist (4 talks): The inherent bias in our technology

  • 8:44
    Now playing
    MIT grad student Joy Buolamwini was working with facial analysis software when she noticed a problem: the software didn't detect her face — because the people who coded the algorithm hadn't taught it to identify a broad range of skin tones and facial structures. Now she's on a mission to fight bias in machine learning, a phenomenon she calls the "coded gaze." It's an eye-opening talk about the need for accountability in coding ... as algorithms take over more and more aspects of our lives.
  • 9:18
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    Search engines have become our most trusted sources of information and arbiters of truth. But can we ever get an unbiased search result? Swedish author and journalist Andreas Ekström argues that such a thing is a philosophical impossibility. In this thoughtful talk, he calls on us to strengthen the bonds between technology and the humanities, and he reminds us that behind every algorithm is a set of personal beliefs that no code can ever completely eradicate.
  • 9:04
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    As web companies strive to tailor their services (including news and search results) to our personal tastes, there's a dangerous unintended consequence: We get trapped in a "filter bubble" and don't get exposed to information that could challenge or broaden our worldview. Eli Pariser argues powerfully that this will ultimately prove to be bad for us and bad for democracy.
  • 17:42
    Now playing
    Machine intelligence is here, and we're already using it to make subjective decisions. But the complex way AI grows and improves makes it hard to understand and even harder to control. In this cautionary talk, techno-sociologist Zeynep Tufekci explains how intelligent machines can fail in ways that don't fit human error patterns — and in ways we won't expect or be prepared for. "We cannot outsource our responsibilities to machines," she says. "We must hold on ever tighter to human values and human ethics."