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Chronicles

The story behind the story

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A game made with a real world dataset of defendants shows the shortcomings of COMPAS, an AI-powered risk assessment tool used in the US criminal legal system

Sundays are for making a house into a home … Tweets: Karen Hao / @_karenhao : IT'S HERE!!! The biggest story I've ever worked on. @techreview's very first interactive ever, which walks through a concrete example of AI bias, and why it's so much more complicated than initially meets the eye. https://www.technologyreview.com/ ... 1/ Gerry McGovern / @gerrymcgovern : Software engineers are being asked to articulate what it means to be fair in their code. This is why regulators around the world are now grappling with a question: How can you mathematically quantify fairness? https://www.technologyreview.com/ ... @techreview : In 2016, a @ProPublica investigation argued that an algorithm used in the US criminal legal system was biased against black defendants. Can you make AI fairer with this courtroom algorithm game? (don't worry, it won't involve any coding) https://www.technologyreview.com/ ... https://twitter.com/... @techreview : We need your help to make a real algorithm less biased. We're going to walk through the algorithm, one used to decide who gets sent to jail, and ask you to tweak its various parameters to make its outcomes more fair. Play the game—and read the story. https://www.technologyreview.com/ ... Mary L. Gray / @marylgray : Original, critical, thought-provoking journalism—idata-driven reporting at its best. It doesn't let data sit self-evident. Instead, @_KarenHao and @techreview colleagues ask us to consider how we impose tech on each other, particularly the most disenfranchised 👇🏼👇🏼 👇🏼 https://twitter.com/... Franois Petitjean / @ledataminer : Such a fantastic, didactic tool to explain the issues of fairness and AI to non-specialists. Hard recommend. Via @sarahbmyers. In case you didn'tsee this @westylesty @rgibli @kim_weatherall @Lizzie_OShea @parismarx https://twitter.com/... @ainowinstitute : Great article by @_KarenHao that shows why predictive algorithms don't make the judicial process more fair - and why we need impact assessments 👍 (nice to see shout outs to @ruha9 and our policy director Rashida Richardson) https://twitter.com/... Varoon Mathur / @varoonmathur : This is really good - and highlights well the divide between algorithmic “fairness” and actual justice. https://twitter.com/... Jason Pontin / @jason_pontin : This interactive exploration of the criminal risk assessment algorithm COMPAS by @_KarenHao and @jonathanstray is one of the best things published by @techreview. It unpacks the conflicts inherent in any such tool in a way a linear narrative could not. https://www.technologyreview.com/ ... Hi-Phi Nation / @hiphination : MIT has made a visual to show the exact problems with algorithmic risk assessment to date, and essentially why there is no solution. https://www.technologyreview.com/ ...

MIT Technology Review

Discussion

  • @_karenhao Karen Hao on x
    IT'S HERE!!! The biggest story I've ever worked on. @techreview's very first interactive ever, which walks through a concrete example of AI bias, and why it's so much more complicated than initially meets the eye. https://www.technologyreview.com/ ... 1/
  • @gerrymcgovern Gerry McGovern on x
    Software engineers are being asked to articulate what it means to be fair in their code. This is why regulators around the world are now grappling with a question: How can you mathematically quantify fairness? https://www.technologyreview.com/ ...
  • @techreview @techreview on x
    In 2016, a @ProPublica investigation argued that an algorithm used in the US criminal legal system was biased against black defendants. Can you make AI fairer with this courtroom algorithm game? (don't worry, it won't involve any coding) https://www.technologyreview.com/ ... http…
  • @techreview @techreview on x
    We need your help to make a real algorithm less biased. We're going to walk through the algorithm, one used to decide who gets sent to jail, and ask you to tweak its various parameters to make its outcomes more fair. Play the game—and read the story. https://www.technologyreview.…
  • @marylgray Mary L. Gray on x
    Original, critical, thought-provoking journalism—idata-driven reporting at its best. It doesn't let data sit self-evident. Instead, @_KarenHao and @techreview colleagues ask us to consider how we impose tech on each other, particularly the most disenfranchised 👇🏼👇🏼 👇🏼 https://twi…
  • @ledataminer Franois Petitjean on x
    Such a fantastic, didactic tool to explain the issues of fairness and AI to non-specialists. Hard recommend. Via @sarahbmyers. In case you didn'tsee this @westylesty @rgibli @kim_weatherall @Lizzie_OShea @parismarx https://twitter.com/...
  • @ainowinstitute @ainowinstitute on x
    Great article by @_KarenHao that shows why predictive algorithms don't make the judicial process more fair - and why we need impact assessments 👍 (nice to see shout outs to @ruha9 and our policy director Rashida Richardson) https://twitter.com/...
  • @varoonmathur Varoon Mathur on x
    This is really good - and highlights well the divide between algorithmic “fairness” and actual justice. https://twitter.com/...
  • @jason_pontin Jason Pontin on x
    This interactive exploration of the criminal risk assessment algorithm COMPAS by @_KarenHao and @jonathanstray is one of the best things published by @techreview. It unpacks the conflicts inherent in any such tool in a way a linear narrative could not. https://www.technologyrevie…
  • @hiphination Hi-Phi Nation on x
    MIT has made a visual to show the exact problems with algorithmic risk assessment to date, and essentially why there is no solution. https://www.technologyreview.com/ ...