Zobrazeno 1 - 10 of 25 pro vyhledávání: '"Meg Young"'
1
Akademický článek
Carbon Emissions in the Tailpipe of Generative AI
Autor: Tamara Kneese, Meg Young
Publikováno v: Harvard Data Science Review, Iss Special Issue 5 (2024)
Externí odkaz: https://doaj.org/article/9b9e6f4979574b0b80dfd96fc53ddf28
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2
Akademický článek
Municipal surveillance regulation and algorithmic accountability
Autor: Meg Young, Michael Katell, P. M. Krafft
Publikováno v: Big Data & Society, Vol 6 (2019)
A wave of recent scholarship has warned about the potential for discriminatory harms of algorithmic systems, spurring an interest in algorithmic accountability and regulation. Meanwhile, parallel concerns about surveillance practices have already led
Externí odkaz: https://doaj.org/article/123a0ed68c624a34981559503520d94b
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6
Does big data serve policy? Not without context. An experiment with in silico social science
Autor: Chris Graziul, Alexander Belikov, Ishanu Chattopadyay, Ziwen Chen, Hongbo Fang, Anuraag Girdhar, Xiaoshuang Jia, P. M. Krafft, Max Kleiman-Weiner, Candice Lewis, Chen Liang, John Muchovej, Alejandro Vientós, Meg Young, James Evans
Publikováno v: Computational and mathematical organization theory.
The DARPA Ground Truth project sought to evaluate social science by constructing four varied simulated social worlds with hidden causality and unleashed teams of scientists to collect data, discover their causal structure, predict their future, and p
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a5af14bfbfde7d1103487f67e9e4e97
https://pubmed.ncbi.nlm.nih.gov/36471867
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8
Face Mis-ID: An Interactive Pedagogical Tool Demonstrating Disparate Accuracy Rates in Facial Recognition
Autor: Daniella Raz, Michael Katell, Vivian Guetler, Dharma Dailey, Peter M. Krafft, Bernease Herman, Meg Young, Corinne Bintz, Aaron Tam
Publikováno v: AIES
This paper reports on the making of an interactive demo to illustrate algorithmic bias in facial recognition. Facial recognition technology has been demonstrated to be more likely to misidentify women and minoritized people. This risk, among others,
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::10290a5b7ca873a93e21bd3d97d550ae
https://doi.org/10.1145/3461702.3462627
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9
An Action-Oriented AI Policy Toolkit for Technology Audits by Community Advocates and Activists
Autor: Meg Young, Peter M. Krafft, Vivian Guetler, Bernease Herman, Corinne Bintz, Aaron Tam, Shankar Narayan, Bissan Barghouti, Dharma Dailey, Franziska Putz, Pa Ousman Jobe, Jennifer Lee, Micah Epstein, Brian Robick, Michael Katell, Daniella Raz
Publikováno v: FAccT
Motivated by the extensive documented disparate harms of artificial intelligence (AI), many recent practitioner-facing reflective tools have been created to promote responsible AI development. However, the use of such tools internally by technology d
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d870daac1fa7a0b60b33f8ae86afd913
https://doi.org/10.1145/3442188.3445938
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10
Toward situated interventions for algorithmic equity
Autor: Vivian Guetler, Meg Young, Corinne Bintz, Aaron Tam, Dharma Dailey, Michael Katell, Peter M. Krafft, Bernease Herman, Daniella Raz
Publikováno v: FAT*
Research to date aimed at the fairness, accountability, and transparency of algorithmic systems has largely focused on topics such as identifying failures of current systems and on technical interventions intended to reduce bias in computational proc
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cdf5bc98bc071e63c8780527df2be05f
https://doi.org/10.1145/3351095.3372874
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