Log inSign up
user avatar
Mitchell Gordon
@mitchellgordon
Assistant prof @MIT_CSAIL, research @OpenAI. PhD in computer science @Stanford
mgordon.me
Joined September 2007
444
Following
1,687
Followers
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    May 20, 2023
    Beyond excited to join @MITEECS @MIT_CSAIL as an assistant professor, starting fall 2024! I’m so lucky to have had @msbernst @landay @tatsu_hashimoto @foil as my advisors and mentors at Stanford. I can’t thank you all enough!
    user avatar
    James Landay
    @landay
    May 19, 2023
    So proud of @mitchellgordon and his brilliant PhD defense talk on “Human-AI Interaction Under Societal Disagreement”. Great lead advising by @msbernst! Excellent example of human-centered AI research for @StanfordHAI. On to his faculty position @MITEECS! Congrats!
    Image
    Image
    56K
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Dec 13, 2023
    I’m recruiting PhD students and there are still a few days left to apply! If you’re excited about working at the intersection of HCI and AI, come join my new group @MITEECS. Please submit at gradapply.mit.edu/eecs by 12/15!
    56K
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Feb 15, 2022
    1/n What should ML models do when a dataset’s annotators — the people that models are trying to emulate — disagree? In today’s typical supervised learning pipeline, we model an aggregate pseudo-human, predicting the majority vote label while ignoring annotators who disagree.
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Apr 29, 2022
    hi, I’ll be at #CHI2022! So excited to present jury learning, and please say hi if you’re interested in talking about human-centered AI, re-thinking today’s ML pipeline, evaluation metrics, or anything else!
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Jul 11, 2020
    I’m so excited and honored to be included among Apple’s first class of PhD fellows in AI/ML — and grateful for the opportunity to work with incredible mentors like @foil.
    Apple Machine Learning Research
    machinelearning.apple.com
    Introducing Apple Scholars in AIML
    Apple Scholars is a program created to recognize the contributions of emerging leaders in computer science and engineering at the graduate…
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Dec 10, 2019
    We’re presenting “HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models” as an oral at #NeurIPS2019 at 4:50 today in West Exhibition Hall C + B3! hype.stanford.edu
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Feb 15, 2022
    Replying to @mitchellgordon
    4/n We introduce jury learning, a new supervised learning architecture — a technical and normative approach — that models the individual voices in your training dataset...
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Feb 15, 2022
    Replying to @mitchellgordon
    3/n There’s not really a good answer, so we tried asking a different question: whose voices is our model emulating? Datasets are ultimately made up of individual people. So when annotators disagree, instead of modeling some aggregate pseudo-human, let’s model individual people.
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Feb 15, 2022
    Replying to @mitchellgordon
    2/n Or, maybe we do a bit better, and have our AI predict a distribution (e.g. 40% of annotators would think A, 60% would think B). But if you’re a practitioner who’s then got to make a single decision (e.g., do I remove this comment or not), what do you DO with that information?
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Aug 9, 2023
    So excited for this workshop, come join us!
    user avatar
    Michael Bernstein
    @msbernst
    Aug 9, 2023
    Join us at the upcoming #UIST2023 workshop, Architecting Novel Interactions with Generative AI Models. Featuring a keynote by Will Wright (creator of The Sims and Simcity) and Lauren Elliot (Where In The World Is Carmen Sandiego)! reverie.herokuapp.com/uist_interacti…
    Image
    2.1K
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Feb 15, 2022
    Replying to @mitchellgordon
    5/n enabling us to then design a system for interactively exploring, tuning, and shifting the behavior of the classifier, by explicitly choosing which annotators our classifier will emulate, in what proportion.
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    May 11, 2022
    Insightful and important work from a great researcher and person!
    user avatar
    Harmanpreet Kaur
    @harmankkaur
    May 11, 2022
    Beyond excited to share our #FAccT2022 paper "Sensible AI: Re-imagining Interpretability and Explainability using Sensemaking Theory" arxiv.org/abs/2205.05057 Building on incredible recent work in this space, this paper is about *who* interpretability and XAI are intended for. 🧵
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Feb 9, 2021
    Replying to @mitchellgordon @ani_nenkova and 2 others
    For instance, while the Kaggle competition’s most popular model achieved a precision of .527 and recall of .827 over standard aggregated labels, our approach adjusted that down to a precision of .514, and recall of .499.
  • user avatar
    Mitchell Gordon
    @mitchellgordon
    Apr 20, 2019
    Replying to @jeffbigham
    Feel free to just tweet me your feedback
    Image