Data Science and AI at Recidiviz. Previously: Responsible AI at Google, Principal Data Scientist at Opower.
Redwood City, CA
Joined December 2012
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My post with Yoni Halpern, Mario Guajardo-Céspedes, and @mmitchell_ai on #MLFairness and bias in text models: nitter.gq/googledevs/status/9848…
To stop problematic biases from appearing in our ML models, we need to be able to identify them. In this post from the Google AI team, we detail example case studies where gender bias exists in the input text embeddings.
Find out more on the blog ↓
goo.gl/VyrmcP
Ben Packer retweeted
Attending #AAAI2021? Please join our tutorial on #ResponsibleAI in Industry [8:30am PT tomorrow]: sites.google.com/view/Respon… [w/ @packer_ben Mehrnoosh Sameki @phenomenashlie].
Slides: lnkd.in/efaPKNy
#ExplainableAI #Fairness #Privacy #MachineLearning #CaseStudies @RealAAAI
Ben Packer retweeted
I support @timnitGebru, she is an amazing researcher and a force for real change.
She has changed @googleAI and myself so much and showed everyone how real leaders lead.
Ben Packer retweeted
This is why so much of Responsible AI work is focused on actual actions and real-world effects of AI, not just on expressions and internal representations.
E.g. @PopTechWorks's Automating Inequality, @KLdivergence's criminal justice work, and many more. nitter.gq/paulg/status/128553468…
Ben Packer retweeted
I had no idea that John Lewis wrote this autobiographical graphic novel about the Civil Rights Movement: smile.amazon.com/March-Trilo… (it's also available at our local library).
Getting this for my daughter, we'll see if she's old enough. nitter.gq/BridgetMarie/status/12…
Ben Packer retweeted
In his 2017 book, The Color of Law: A Forgotten History of How Our Government Segregated America, local author Richard Rothstein deftly chronicles how Peninsula cities became segregated.
This initiative to offer paper-writing help for those in #BlackInStem is excellent. A ton of signups but few takers so far, so if you're a paper writer who could use help, don't hesitate to contact someone on the list. And if you're not, please spread the word to those who are.
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Ben Packer retweeted
Love working alongside these inspiring women to build more fair and inclusive products! @timnitGebru
Machines—they’re just like us! Well, kind of. What a machine learns depends on the data provided. So what happens if that data has bias? Meet 3 women leading our efforts to make sure we’re building machine learning systems that are fair & inclusive → goo.gle/2SY6HVK
Ben Packer retweeted
Nice interview with Tiffany Deng, Tulsee Doshi and @timnitGebru of @GoogleResearch on some of the challenges in building fair and unbiased machine learning systems.
Machines—they’re just like us! Well, kind of. What a machine learns depends on the data provided. So what happens if that data has bias? Meet 3 women leading our efforts to make sure we’re building machine learning systems that are fair & inclusive → goo.gle/2SY6HVK
Random note: This looks like a cool instance of Simpson's paradox. Each age group shifts towards Clinton from '16-'19 even though the votes themselves aren't changing, it's just the age buckets that shift (the 1st col is voter ages in '16, the 2nd is the same voters' ages in '19)
Ben Packer retweeted
Tech non-profit I have huge respect for—@RecidivizOrg— is modeling the spread of COVID in prisons with prison-specific epidemiological models & analysis. They're hiring front-end engineers to build out the web side of their work; details here: bit.ly/2XJqhrZ
Highly impactful work 👇
@RecidivizOrg has built a tool that's helping governments make decisions to protect incarcerated populations from COVID-19 outbreaks, and they're looking for help on this project.
We are building tools to model the spread of COVID-19 in prisons/jails, helping state & county governments take action to protect incarcerated populations and prevent inmates from overwhelming local hospital systems. We are looking for contractors to help! docs.google.com/forms/d/e/1F…
Talk by @alexdamour at #FAT2020 on "Fairness is not static: deeper understanding of long term fairness via simulation studies," with Hansa Srinivasan, @james_c_atwood, Pallavi Baljekar, D. Sculley, Yoni Halpern
A (cont'd): We're not trying to test productions software model. But there have been lots of great suggestions about participatory design, about aspects that are salient for communities that these systems affect. #FAT2020
A (cont'd): In terms of making sure the environment is compatible with data from a real system, interested in doing this and please let us know if you'd like to help. #FAT2020