Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Passi, Samir"'
Publikováno v:
ACM CSCW 2024
Mistakes in AI systems are inevitable, arising from both technical limitations and sociotechnical gaps. While black-boxing AI systems can make the user experience seamless, hiding the seams risks disempowering users to mitigate fallouts from AI mista
Externí odkaz:
http://arxiv.org/abs/2211.06753
Autor:
Ehsan, Upol, Passi, Samir, Liao, Q. Vera, Chan, Larry, Lee, I-Hsiang, Muller, Michael, Riedl, Mark O.
Publikováno v:
ACM CHI 2024
Explainability of AI systems is critical for users to take informed actions. Understanding "who" opens the black-box of AI is just as important as opening it. We conduct a mixed-methods study of how two different groups--people with and without AI ba
Externí odkaz:
http://arxiv.org/abs/2107.13509
Autor:
Passi, Samir, Sengers, Phoebe
In this workshop paper, we use an empirical example from our ongoing fieldwork, to showcase the complexity and situatedness of the process of making sense of algorithmic results; i.e. how to evaluate, validate, and contextualize algorithmic outputs.
Externí odkaz:
http://arxiv.org/abs/2102.07844
Autor:
Passi, Samir, Jackson, Steven J.
Publikováno v:
Proc. ACM Hum.-Comput. Interact. 2, CSCW, Article 136 (November 2018), 28 pages
The trustworthiness of data science systems in applied and real-world settings emerges from the resolution of specific tensions through situated, pragmatic, and ongoing forms of work. Drawing on research in CSCW, critical data studies, and history an
Externí odkaz:
http://arxiv.org/abs/2002.03389
Autor:
Passi, Samir, Jackson, Steven J.
Publikováno v:
In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. ACM, New York, NY, USA, 2436-2447
Learning to see through data is central to contemporary forms of algorithmic knowledge production. While often represented as a mechanical application of rules, making algorithms work with data requires a great deal of situated work. This paper exami
Externí odkaz:
http://arxiv.org/abs/2002.03387
Autor:
Passi, Samir, Barocas, Solon
Formulating data science problems is an uncertain and difficult process. It requires various forms of discretionary work to translate high-level objectives or strategic goals into tractable problems, necessitating, among other things, the identificat
Externí odkaz:
http://arxiv.org/abs/1901.02547
Publikováno v:
Conference Proceedings of the First International Conference on Internet Science, April 9-11, 2013 Brussels. Pages 75-78
This paper demonstrates the application of bibliometric mapping techniques in the area of funded research networks. We discuss how science maps can be used to facilitate communication inside newly formed communities, but also to account for their act
Externí odkaz:
http://arxiv.org/abs/1304.5753
Autor:
Ehsan, Upol, Passi, Samir, Liao, Q. Vera, Chan, Larry, Lee, I-Hsiang, Muller, Michael, Riedl, Mark O.
Explainability of AI systems is critical for users to take informed actions and hold systems accountable. While "opening the opaque box" is important, understanding who opens the box can govern if the Human-AI interaction is effective. In this paper,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95fc5a0384defebc8c541d74df3a0ba5
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