Ideas worth spreading

How I'm fighting bias in algorithms

1,688,834 views |

Joy Buolamwini |

TEDxBeaconStreet

• November 2016

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.

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.

This talk was presented to a local audience at TEDxBeaconStreet, an independent event. TED's editors chose to feature it for you.

Read more about TEDx.

Donate to the Algorithmic Justice League.

Fight coded bias by taking action through sharing your story, spreading the word and getting involved.

Sign up for the Algorithmic Justice League Newsletter.

Follow Joy Buolamwini on Twitter.

About the speaker

Joy Buolamwini

See speaker profile

Joy Buolamwini's research explores the intersection of social impact technology and inclusion.

Clare Garvie, Alvaro Bedoya, Jonathan Frankle | Explore

The Perpetual Line-up: Unregulated Police Face Recognition in America

This investigative report highlights the growing use of facial recognition by law enforcement. One in two adults in the United State is in a facial recognition database that can be searched using algorithms that have not been publicly tested for demographic accuracy.

Christian Sandvig, Kevin Hamilton, Karrie Karahalios, and Cedric Langbort | Article

"When the Algorithm Itself Is a Racist: Diagnosing Ethical Harm in the Basic Components of Software"

Though the development of algorithms takes specialist knowledge, we can take steps to understand the impact of technical choices that hold ethical implications.

Cathy O'Neil | Crown, 2016 | Book

Weapons of Math Destruction

Through powerful examples, Cathy shows that the increasing use of machine learning to make life altering decisions about employment, loans and access to education necessitates transparency and accountability.

Margot Lee Shetterly | William Morrow Paperbacks, 2016 | Book

Hidden Figures

Shetterly revisits history to reveal the forgotten stories of brilliant black female mathematicians whose work enabled NASA to touch the stars. By uncovering their stories, she shows the importance of embracing full spectrum teams that propel humanity forward.

Learn more

About TEDx

TEDx was created in the spirit of TED's mission, "ideas worth spreading." It supports independent organizers who want to create a TED-like event in their own community.

Find a TEDx event near you

This talk was presented to a local audience at TEDxBeaconStreet, an independent event. TED's editors chose to feature it for you.

Read more about TEDx.

Donate to the Algorithmic Justice League.

Fight coded bias by taking action through sharing your story, spreading the word and getting involved.

Sign up for the Algorithmic Justice League Newsletter.

Follow Joy Buolamwini on Twitter.