Michelle Lam
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mlam.bsky.social
Michelle Lam
@mlam.bsky.social
910 followers 240 following 11 posts
Stanford CS PhD student | hci, human-centered AI, social computing, responsible AI (+ dance, design, doodling!)
michelle123lam.github.io
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Reposted by Michelle Lam
kaitlynzhou.bsky.social
As of June 2025, 66% of Americans have never used ChatGPT.

Our new position paper, Attention to Non-Adopters, explores why this matters: AI research is being shaped around adopters—leaving non-adopters’ needs, and key LLM research opportunities, behind.

arxiv.org/abs/2510.15951
A circular flow diagram that compares current and proposed practices for LLM development using data from adopters and non-adopters. Three gray boxes represent current practices: “R&D,” “Chat Models,” and “Adopters’ Needs and Usage Data,” connected in a clockwise loop with black arrows. A blue box labeled “Non-adopters’ Needs and Usage Data” adds a proposed feedback path, shown with blue arrows, linking non-adopter data back to R&D and adopters’ data.
October 21, 2025 at 5:12 PM
mlam.bsky.social
LLM safety work often reasons over high-level policies (be helpful & polite), but must tackle on-the-ground cases (unsolicited money advice when stocks are mentioned). This can feel like driving on an unfamiliar road guided by a generic driver’s manual instead of a map. We introduce: Policy Maps 🗺️
September 29, 2025 at 3:54 PM
Reposted by Michelle Lam
mariaa.bsky.social
Somehow only just became aware of LlooM, a toolkit that uses a combination of clustering and prompts to extract concepts and describe custom datasets — similar to a topic model. Looks nice, with lots of documentation and open colab notebooks!

Has anyone used it?

stanfordhci.github.io/lloom/about/
What is LLooM? | LLooM
Concept Induction: Analyzing Unstructured Text with High-Level Concepts
stanfordhci.github.io
January 17, 2025 at 9:09 AM
mlam.bsky.social
We're excited to host a second iteration of the HEAL workshop! Join us at CHI 2025 :)

→ Deadline: Feb 17, more info at heal-workshop.github.io
liuyulu.bsky.social Yu Lu Liu @liuyulu.bsky.social · Dec 16
Human-centered Evalulation and Auditing of Language models (HEAL) workshop is back for #CHI2025, with this year's special theme: “Mind the Context”! Come join us on this bridge between #HCI and #NLProc!

Workshop submission deadline: Feb 17 AoE
More info at heal-workshop.github.io.
The image includes a shortened call for participation that reads: "We welcome participants who work on topics related to supporting human-centered evaluation and auditing of language models. Topics of interest include, but not limited to: - Empirical understanding of stakeholders' needs and goals of LLM evaluation and auditing - Human-centered evaluation and auditing methods for LLMs - Tools, processes, and guidelines for LLM evaluation and auditing - Discussion of regulatory measures and public policies for LLM auditing - Ethics in LLM evaluation and auditing Special Theme: Mind the Context. We invite authors to engage with specific contexts in LLM evaluation and auditing. This theme could involve various topics: the usage contexts of LLMs, the context of the evaluation/auditing itself, and more! The term ''context'' is purposefully left open for interpretation! The image also includes pictures of workshop organizers, who are: Yu Lu Liu, Wesley Hanwen Deng, Michelle S. Lam, Motahhare Eslami, Juho Kim, Q. Vera Liao, Wei Xu, Jekaterina Novikova, and Ziang Xiao.
December 19, 2024 at 4:15 AM
Reposted by Michelle Lam
mbernst.bsky.social
Wednesday, at CSCW: @mlam.bsky.social and Chenyan Jia present their Best Paper award winner, "Embedding Democratic Values into Social Media AIs via Societal Objective Functions"

hai.stanford.edu/news/buildin...
Building a Social Media Algorithm That Actually Promotes Societal Values
A Stanford research team shows that building democratic values into a feed-ranking algorithm reduces partisan animosity.
hai.stanford.edu
November 12, 2024 at 8:32 PM