@ziv-e.bsky.social's talk showed the gaps in which users are recommended content that is aligned with their values. This work definitely points to the importance of user agency in feeds!
I couldn’t find the link to this paper, but some related work from Ziv here:
🔗: arxiv.org/pdf/2509.14434

They found that while increasingly accurate LLM’s map to increasingly accurate responses, the effects plateau around 80%. Great insight into how decision supports require active design to best support people and their goals. Looking forward to reading this paper when it’s out!!

@jennahgosciak.bsky.social showed how LLM assistance can improve government caseworker accuracy in the context of SNAP eligibility questions. It was really cool to see Jennah + team get ahead of the ever-shifting technical capacity of LLMs by varying chatbot accuracy.

Sherry Jueyu Wu showed that when people participate in collective decision-making, they are more willing to express that the gov needs improvement. Interesting to think about in the context of participation and accountability on online platforms...
🔗: www.nature.com/articles/s41...

This is a really cool work demonstrating the value of human expertise in sociotechnical decision-making processes!
🔗: arxiv.org/pdf/2505.13325

@utopianturtle.top presented a causal framework for modeling algorithmically assisted decision-making, which the authors use to identify the ways academic advisors leverage non-algorithmic knowledge, and where advisors’ holistic approaches contribute to improved student outcomes.