madeleine clare elish

@m_c_elish

anthropologist of AI, automation, and robots; research lead at data & society research institute; ebay entrepreneur extraordinaire

brooklyn, ny
Vrijeme pridruživanja: ožujak 2011.

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  1. Prikvačeni tweet
    10. pro 2019.

    Hot off the press: Our case study on AI in healthcare. Tl;dr: developing ML systems is a ⚡️sociotechnical⚡️problem, people and institutions shape use, explainability is not the only means to accountability + much more!

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  2. Poništi
  3. 30. sij

    Beyond honored + thrilled to begin working with Rich Zemel & as co-general chair for (formerly known as FAT*) . Here we go! Please be in touch!

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  4. proslijedio/la je Tweet
    29. sij

    "They may find themselves in the difficult position of prioritizing the universal rights of users located in countries with laws that don’t protect them." Senior Researcher on Facebook's global oversight board for :

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  5. proslijedio/la je Tweet
    29. sij

    Reminder: just a couple days left to apply for ’s summer fellowship! You’ll be paid. You get free lunch everyday. And you get to work on pressing technology + justice issues together with our amazing staff. Apply here by Friday:

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  6. proslijedio/la je Tweet
    29. sij

    "Bringing community in is not the same as defining your problem within the community" - session on creating community-based tech policy with and .

    Systematic tech deployment mismatches that can result from exclusion of community in development of technology. DM if you'd like me to type and send full list as too long for alt text.
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  7. 29. sij

    So so so excited for this! The fair organized by + was one of my 💚favorite events💚 of the past year. So psyched + + all those involved are bringing this event into being!

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  8. 28. sij
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  9. 28. sij
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  10. 28. sij

    Really interesting methodological discussion by m about how to study socio-technical systems: if access to data itself is blocked—investigate the institutional processes that bring it into being and operationalize bias and discrimination.

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  11. 28. sij

    The anthropologist in me worries how much is missed when we study human-AI trust dynamics in the lab, not in real institutional contexts. Maybe we need a “Roles for Lab Experiments in Social Change” paper? Modeled after the must read paper :)

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  12. 28. sij
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  13. proslijedio/la je Tweet

    Really happy that the provocations raised by this paper on 'studying up' in data science is at thanks to the new SSH track. Read it!

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  14. 28. sij

    We need to study real-world cases to understand how decisions are made in social and institutional context!

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  15. 28. sij

    Hi ! Here is the table + our paper link. TL;DR Achieving accountable and trustworthy AI means designing interventions as *socio*-technical systems with constant input from stakeholders and local expertise (not necessarily an explainable model).

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  16. proslijedio/la je Tweet
    28. sij

    Love the conversation about accountability at & wld love to also involve the and communities as lots of thinking over time in those related fields, see definitions of key terms here ;

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  17. proslijedio/la je Tweet
    27. sij

    At ? Want to learn abt a *real-world* ML system integrated into *actual* clinical practice, running live in ED 24/7, & what it took to build trust & accountability w stakeholders to get there? Come to Sess. 2 tmrw 9am on explainability!

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  18. proslijedio/la je Tweet
    25. sij

    Attending FAT*2020? Come to our social at 8:30pm on Tue Jan 28th at the bar of the hotel (conference location). Join us for refreshments, drinks, and lovely company! Allies welcome! 🌈🎉

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  19. proslijedio/la je Tweet
    23. sij

    So excited to share the outputs of our digital ID project with the world!!! I hope these insights will strengthen advocacy on digital ID, and help us all acknowledge the complexities and nuances of digital ID systems. More below! 💕🙌🏾

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  20. 7. sij

    Wise words from my new fave account: management tips from the captain.

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  21. proslijedio/la je Tweet
    19. pro 2019.

    *Job Opportunity!* We're starting an exciting new project on algorithmic harms and experiences of "AI safety" in global contexts. Both post-docs and *practice-based experts* welcome to apply! Questions? DM me!

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