RT @BedoyaFTC: 1/ Today @FTC brought and settled charges against Rite Aid for using a biased face scanning system that led to employees fal….

Really important early work on the effects of ransomware attacks on patients from @HNeprash @saynikpay and Claire McGlave!. We talk a lot about financial impacts, but there are so many other consequences for patients. This is a great writeup in Stat.

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We developed this paper at a workshop on algorithmic reparations led by @AprylW and Jenny Davis. From beginning to end it was an incredible experience and will lead to more empirical work on how to make algorithmic systems more just.

First, we apply bounded justice to fairness and clinical algorithms by describing structural constraints on health equity efforts. We then reimagine how clinical algorithms could function as a reparative technology to support justice and empower patients in healthcare.

It's such a critical perspective, especially when so many seem satisfied with the idea of algorithmic fairness. That doesn't even begin to address the root causes of inequity.

RT @kdpsinghlab: When an outcome influences a predictor, it’s “outcome leakage.” But what about when a predictor influences an outcome?. Wi….

RT @DrRachelShelton: Repost- Our dept is seeking to hire up to two tenure-track Assistant Professors at @ColumbiaMSPH! Application is open….

RT @Younglordsean: Being unapologetic isn’t for everyone some of you need to apologize.

RT @rwcarpenterphd: And to think, I once doubted whether I could really manage this whole advisor thing

RT @lopez_wd: Omg I’m obsessed with @FlemingPaulJ testifying at city council in support of the Ann Arbor driving equality ordinance and hol….

RT @AJHolmgren: If you’re at ARM on the job market and do research at the crossroads of health policy, HSR, and informatics please don’t he….

Reflecting on Dr @KadijaFerryman and Dr @MelissaSCreary's work, we write that inclusion is not an end in and of itself. Its value lies in being a mechanism through which people can be served. And that takes a lot more than data representativeness.

Extracting people's data can exacerbate structural harms. What are we we *doing* with the data?. ➡️Is it used to provide a resource, to surveil, or both? .➡️Is it used to respond to a health need or to serve commercial interests?.

In our short @bioethics_net commentary, @sarahelazab1 and I discuss how this hyper-visibility can apply to data representativeness. How might data representation undermine or bound health equity efforts in practice?.

Applying Dr @MelissaSCreary's bounded justice to ELSI, Dr @KadijaFerryman sparked this discussion. She explains racialization & invisibility/hyper-visibility in her featured article in AJOB. A huge contribution to ELSI literature & precision med!

There's a lot of excitement about how data representation could lead to health equity. But what does data representation mean in a system that subjects racialized people to hyper-visibility and surveillance? .

RT @CornwallTiffany: Last year, my father died on my sisters graduation day. His passing deepened my commitment to advocate for a more dive….

RT @ravindranize: This especially interested me: Epic said early users of its AI-guided MyChart draft tool can choose whether to automatica….

RT @WilliamDeringer: 📢JOB ALERT📢. My department, the Program in Science, Technology, & Society at MIT (@mitpsts), is running a search for t….

RT @kdpsinghlab: On April 18, @ONC_HealthIT issued a proposed rule w/ the goal of ⬆️ transparency on the use of healthcare algorithms. @je….