Computational Policy Lab
@CompPolicyLab
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We're a team of researchers and data scientists who use computational approaches to address issues in criminal justice, education, voting rights, and beyond.
Cambridge, MA
Joined June 2018
RT @Kennedy_School: HKS researchers—including @5harad, @Soroush_Saghaf, and @madisoncoots—created an analytical framework that informs the…
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RT @LX_CW: NEW in Management Science! My coauthors and I came up with a new consequentialist approach to designing equitable algorithms.…
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Less than one week to join our study on using AI to improve education! Give your students access to a free virtual tutor & receive a $1,000 honorarium. Apps open for college instructors (esp. those teaching math, comp science, stats, & econ) until Dec 16:
Calling instructors at 2- & 4-year colleges! Give your students free access to a virtual tutor optimized for learning by taking part in our study on using AI to improve education. Participating instructors receive a $1,000 honorarium. Sign up by Dec. 16:
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RT @madisoncoots: The use of race in clinical risk models is heavily debated. While race-aware models can be more accurate, some are concer…
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Our virtual tutor, called PingPong, is based on ChatGPT. It's designed to help students learn, not to simply give them answers. We'll help customize PingPong to your course content. Instructors can view de-identified student interactions. PingPong is multilingual.
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🏆 Congratulations to @jgaeb1 and @5harad (@CompPolicyLab) for winning the Best Paper at #EAAMO2024! Their work introduces the Robust Outcome Test to improve fairness analysis in discrimination studies by combining benchmark and outcome tests under a new statistical guarantee.
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Finally, we’re excited to note that the US Place Sampler was recognized earlier this year with an “Award of Excellence” from the Society for News Design! Congratulations to @JoeNudell and team.
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Our co-director @LX_CW spoke with @Arnold_Ventures about the role AI can play in supporting fair charging decisions. Read more about our race-blind charging project, which aims to mitigate unintended biases in the justice system:
It was great chatting with @Arnold_Ventures about why this research effort is so important to me!
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RT @LX_CW: Are you a prospective PhD student interested in combining statistical, computational, and social science approaches to address p…
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Data collected since 2018 under the Racial and Identity Profiling Act help measure disparities in California police traffic stops.@LX_CW contributed data to highlight these disparities for a story in the @sfchronicle:
Yesterday we posted an unusual story for us at the @sfchronicle that was actually about 400 stories. Here is a little thread about how it happened.
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RT @danmlevy: Want to use ChatGPT in your teaching but don't have much time⏱️to learn how? If so, this webinar recording from @HarvardBizEd…
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RT @LX_CW: Some personal news: I’m back at @nyuniversity in a new role as an assistant professor of computational social science at @NYU_AS…
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RT @ShorensteinCtr: The deadline to submit nominations for the 2024 David Nyhan Prize for Public Policy Journalism is just 10 days away! Le…
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Can racial disparities in arrest records skew criminal risk assessments, & how should we study this issue? This analysis, co-authored by @ Michael Z-T examines implications of the data used in criminal legal system RAIs & provides a roadmap for assessing real-world consequences.
I’m excited to share that my article, “Algorithmic Bias in Criminal Risk Assessment: The Consequences of Racial Differences in Arrest as a Measure of Crime” (coauthored with Roland Neil) is now online at the Annual Review of Criminology and is open access!
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