Michelle Lam (@michelle123lam) / X

Michelle Lam

183 posts

Michelle Lam

@michelle123lam

CS PhD student @Stanford | hci, human-ai interaction (+ dance, design, doodling!)

Stanford, CA

michelle123lam.github.io

Joined August 2012

Pinned
Michelle Lam
@michelle123lam
Apr 15
Most of what I actually need help with, I never think to tell a model. But why is it on me to remember? Our new paper asks: what if AI could proactively specialize to individuals and the tasks they’re carrying out at this very moment? 🧵
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Michelle Lam
@michelle123lam
Oct 24, 2022
Today, technical experts hold the tools to conduct system-scale algorithm audits, so they largely decide what algorithmic harms are surfaced. Our #cscw2022 paper asks: how could *everyday users* explore where a system disagrees with their perspectives? hci.st/end-user-audit 🧵
Michelle Lam
@michelle123lam
Apr 18, 2024
“Can we get a new text analysis tool?” “No—we have Topic Model at home” Topic Model at home: outputs vague keywords; needs constant parameter fiddling🫠 Is there a better way? We introduce LLooM, a concept induction tool to explore text data in terms of interpretable concepts🧵
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38K
Michelle Lam
@michelle123lam
Oct 6, 2023
Algorithm audits are powerful, but focused on technical system components. We introduce Sociotechnical Audits that expand to audit both algorithms and how users change in response to algorithms. We'll be sharing more on this work soon, but excited to present at CSCW! :)
ACM CSCW
@ACM_CSCW
Oct 6, 2023
NEW PAPER: Led by @michelle123lam & @DrMetaxa, a sociotechnical audit finds online ad targeting is effective, but perhaps via repeated exposure, not inherent user benefit. #CSCW2023 tinyurl.com/socio-audits-c…
25K
Michelle Lam
@michelle123lam
Oct 17, 2023
How can we go beyond auditing algorithms to also investigate how users change in response to algorithms? We introduced Sociotechnical Audits & the Intervenr system to address this challenge! Join us at #CSCW2023—Wed 2:30pm for our honorable mention paper 🤠🧵:
20K
Michelle Lam
@michelle123lam
Apr 3, 2023
When building ML models, we often get pulled into technical implementation details rather than deliberating over critical normative questions. What if we could directly articulate the high-level ideas that models ought to reason over? #CHI2023 hci.st/model-sketching 🧵
21K
Michelle Lam
@michelle123lam
Mar 21, 2024
It's been great working with the folks from @AvidMldb to launch a public version of IndieLabel, our prototype end-user auditing system (from our CSCW22 paper)! We hope this demo can seed further discussion and future work on user-driven AI audits ✨
15K
Michelle Lam
@michelle123lam
May 14, 2024
Frustrated with topic models? Wish emergent concepts were interpretable, steerable, and able to classify new data? Check out our #CHI2024 talk on Tues 9:45am in 316C (Politics of Datasets)! Or try LLooM, our open-sourced tool :) ✨
Michelle Lam
@michelle123lam
Apr 18, 2024
“Can we get a new text analysis tool?” “No—we have Topic Model at home” Topic Model at home: outputs vague keywords; needs constant parameter fiddling🫠 Is there a better way? We introduce LLooM, a concept induction tool to explore text data in terms of interpretable concepts🧵
00:00
GitHub - michelle123lam/lloom: Concept Induction: Analyzing Unstructured Text with High-Level...
From github.com
10K
Michelle Lam
@michelle123lam
Jun 27, 2023
We're really grateful that our End-User Audits project was selected as one of the AI Audit Challenge award-winners! If you're interested in AI evaluation, come join the virtual showcase at 9a tomorrow (6/27) to hear about all of the cool projects & discuss the future of auditing!
Stanford HAI
@StanfordHAI
Jun 20, 2023
Last August, HAI and @StanfordCyber launched the #AIAuditChallenge that calls for solutions to improve our ability to evaluate AI systems. Join us on June 27 as we highlight the most innovative approaches, as well as lessons learned from the challenge: stanford.io/42SDjkN
8.5K
Michelle Lam
@michelle123lam
Aug 22, 2023
If you're interested in how we can engage end users in testing, auditing, and contesting AI systems, come join our #CSCW23 in-person workshop! The submission deadline is Sept 15 ✨
Wesley Hanwen Deng
@wes_deng
Aug 22, 2023
Excited to share our @ACM_CSCW 23 in-person workshop on ✨supporting user engagement in testing, auditing, and contesting AI✨. We plan to have a set of engaging activities for attendees! Please visit cscw-user-ai-auditing.github.io for workshop information and the submission form!
7.2K
Michelle Lam
@michelle123lam
Jun 10, 2024
How can end users more powerfully shape LLM behavior? DITTO lets a user provide just a handful of demonstrations to align a language model to their needs—and users much prefer these results over those of baseline methods and self-authored prompts!
Omar Shaikh
@oshaikh13
Jun 10, 2024
LLMs sound homogeneous *because* feedback modalities like rankings, principles, and pairs cater to group-level preferences. Asking an individual to rank ~1K outputs or provide accurate principles takes effort. What if we relied on a few demos to elicit annotator preferences?
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Michelle Lam
@michelle123lam
Apr 25, 2023
Ever wonder how we might tackle ML fairness issues way upstream during early model design instead of waiting for audits & post-hoc fixes? Come to our #CHI2023 Model Sketching talk to hear about a system for iterating on models in terms of high-level values: Today 2:30p, Hall A!
Michelle Lam
@michelle123lam
Apr 3, 2023
When building ML models, we often get pulled into technical implementation details rather than deliberating over critical normative questions. What if we could directly articulate the high-level ideas that models ought to reason over? #CHI2023 hci.st/model-sketching 🧵
4.6K
Michelle Lam
@michelle123lam
Dec 8, 2023
Today's social media AIs encode values—can we mitigate societal harms by making these values explicit and tuneable? Excited to share our #CSCW24 paper introducing societal objective functions, which translate social science constructs into algorithmic objectives for social media!
Chenyan Jia
@JiaChenyan
Dec 7, 2023
Can we design AI systems to consider democratic values as their objective functions? Our new #CSCW24 paper w/ @michelle123lam, Minh Chau Mai, @jeffhancock, @msbernst introduces a method for translating social science constructs into social media AIs arxiv.org/abs/2307.13912 (1/12)
16K
Michelle Lam
@michelle123lam
Dec 21, 2023
With so many open questions about how we ought to evaluate and audit LLMs, the HCI community has an exciting opportunity to lead the discussion with creative, human-centered approaches. Come join our workshop (HEAL) at #CHI2024 — submissions are due Feb 23!
Ziang Xiao
@ZiangXiao
Dec 20, 2023
Working on #LLMs evalution and auditing? 📢 We are organizing the first workshop on Human-centerd Evalulation and Auditing of Language Models at #CHI2024. Joining us and build the community! 🗓️ Deadline: Feb 23 More info: heal-workshop.github.io #HCI #NLProc
5.3K