Berk Ustun

@berkustun

Postdoc CS. I work on fairness and interpretability in machine learning. Previously , 🇨🇭🇹🇷

Cambridge, MA
Vrijeme pridruživanja: ožujak 2009.

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  1. Prikvačeni tweet
    17. ruj 2018.

    Denied a loan by an ML model? You should be able to change something to get approved! In a new paper w & @yxxxliu, we call this concept "recourse" & we develop tools to measure it for linear classifiers. PDF CODE

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  2. proslijedio/la je Tweet
    28. sij

    There's a need for deep intimacy with our precarious present! Fascinating work from & Mark Alfano , so very aligned with our findings from the work on

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  3. proslijedio/la je Tweet
    21. sij
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  4. proslijedio/la je Tweet
    8. sij

    Ok, people! Are you looking for something to read at the intersection of machine learning and HCI? Three new papers posted online today that you should check out, all with my amazing colleague/BFF ! Ready? I'm gonna try a thread!

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  5. 8. sij
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  6. proslijedio/la je Tweet
    20. pro 2019.

    This is a very utopian view of AI in education. Some is appropriate—there are big opportunities for some aspects of learning—but it ignores the way that software can amplify disparities, helping students with strong self-regulation skills, harming others.

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  7. proslijedio/la je Tweet
    13. pro 2019.

    “We typically assume that there’s one best model, but in practice there can be many models that produce different results.” -

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  8. 12. pro 2019.

    Just got into Vancouver in time for the workshops! Let's chat! I'll be at the human-centered ML workshop on Friday, and the Fairness in ML for Healthcare workshop on Saturday.

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  9. proslijedio/la je Tweet
    10. pro 2019.

    Political speech is paid, not free. On it also cost different $$$ to advertise different political opinions to the same people 1/4

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  10. proslijedio/la je Tweet
    9. pro 2019.

    Assessing Disparate Impact of Personalized Interventions: Identifiability and Bounds Thu Dec 12th 10:45 AM -- 12:45 PM @ East Exhibition Hall B + C #72 joint work !

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  11. 6. pro 2019.

    Ask yourself - who is making decisions in algorithm design and model selection? Did I have a say? Were there other reasonable alternative algorithms and models that would have benefitted me? 2/2

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  12. 6. pro 2019.

    I really loved this article and this take. The more I work in this field, the more I think that the real issue about human-facing ML isn't "bias" but "power" 1/2

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  13. 5. pro 2019.
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  14. proslijedio/la je Tweet
    2. pro 2019.

    An ML researcher, a clinician, an anthropologist, a bioethicist, and many others walk into a workshop. 🤪 Mad props to and for a brilliant Fairness in ML in Health meeting ✨ – mjesto: Data & Society Research Institute

    , , i još njih 6
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  15. proslijedio/la je Tweet
    19. stu 2019.
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  16. proslijedio/la je Tweet
    19. stu 2019.

    There are no null results. There are results that establish useful upper bounds, there are results that establish useful lower bounds, there are results that do both, and there are results that do neither.

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  17. proslijedio/la je Tweet
    12. stu 2019.
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  18. proslijedio/la je Tweet
    31. lis 2019.

    Very excited to see ACM CHIL running!!! Plan to submit and be in Toronto on April 2-4!

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  19. proslijedio/la je Tweet
    30. lis 2019.

    Announcing an exciting new conference: "Foundations of Responsible Computing" (FORC). Here is the call for papers: . The deadline is February 11, and (if I can say so myself :-) it has an absolutely amazing steering and program committee. 1/

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  20. proslijedio/la je Tweet
    27. lis 2019.

    Speaking of productive self-criticism. When we demonstrate a new capability, let's also demonstrate its limits by showing instances of functional failures. Much of the criticism is a reaction to the hype generated by researchers and the organizations they work for. 7/

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  21. 20. lis 2019.
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