angela zhou

Excited to share our paper! Due Process on Hold: A Queueing Framework for Improving Access in SNAP arxiv.org/abs/2605.15165 Millions of Americans interface with the social safety net via call centers that are too congested. In Holmes v. Knodell, bad operations = procedural due…

[2605.15165] Due Process on Hold: A Queueing Framework for Improving Access in SNAP arxiv.org

You might also like a recent perspective piece we have, taking a program evaluation point of view on algorithmic accountability: arxiv.org/pdf/2606.25668 it's about predictive, not GenAI; but is refocusing the role of social systems in AI evaluation

arxiv.org

This is a bit of a "hard launch" for our series of workshops and whitepapers with a multidisciplinary crew of amazing folks! Longer paper: arxiv.org/abs/2507.05216 Shorter perspective: arxiv.org/abs/2606.25668 Your predictive ADS is actually an organizational process, decision…

Bridging Prediction and Intervention Problems in Social Systems arxiv.org

This is a bit of a "hard launch" for our series of workshops and whitepapers with a multidisciplinary crew of amazing folks! Longer paper: arxiv.org/abs/2507.05216 Shorter perspective: arxiv.org/abs/2606.25668 Your predictive ADS is actually an organizational process, decision…

Bridging Predictions and Interventions: An Integrated Framework for Automated Decision-Systems arxiv.org

i don't think we should waste real expert reviewer's time reviewing mediocre AI-written papers and having real expert reviewer provide valuable feedback that, presumably, will just get sent to LLMs to complete. at that point the reviewers might as well be authoring along with the authors

if you need me, you'll find me at the joint misery of: * the federal govt is destroying most things i care about, every day, for my research on social services * there is no accountability for frontier AI & my SV-friends' ability to buy multi-million dollar homes is reliant on this continuing

need an ai agent to pm me on my multiple projects (or keep me from adding too many projects to my stack)

feeling .... extremely depressed today how llms are giant plagiarism machines, and how much work on the side of review it takes to point that out.

I think often in AI for social good research spaces, we talk about projects as just consulting projects (derogatory) But actually, I think there's a lot of worth in developing consulting capabilities: paying attention to client needs, building mental models for client goals, processes, resources

... am i allowed to decline review requests at journals because i'm overloaded and the abstract is plainly written by AI? :( signed, someone working around the clock without the capacity to do this

i feel like prototyping an ai product or workflow to Work Well and Add Value instead of becoming More Workslop is like cooking. you need to be tasting as you go, and even as models are getting better, you need someone to be tasting as you go along (where tasting = looking at the data)

So ... what do all the freaked out / guilty-feeling AI researchers do to get mandatory incident reporting in place for AI development? is transparency going to be just based on handshake agreements with an in-crowd?