Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Michael Katell"'
Autor:
David Leslie, Carolyn Ashurst, Natalia Menéndez González, Frances Griffiths, Smera Jayadeva, Mackenzie Jorgensen, Michael Katell, Shyam Krishna, Doschmund Kwiatkowski, Carolina Iglésias Martins, Sabeehah Mahomed, Carlos Mougan, Shachi Pandit, Mark Richey, Joseph W. Sakshaug, Shannon Vallor, Luke Vilain
Publikováno v:
Harvard Data Science Review, Iss Special Issue 5 (2024)
Externí odkaz:
https://doaj.org/article/4bf3709cdf8f4d4bafce07a553ee643a
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
Publikováno v:
2022 ACM Conference on Fairness, Accountability, and Transparency.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afb190965dca3f6bf9c1c54fd89d57de
https://doi.org/10.1145/3531146.3533194
https://doi.org/10.1145/3531146.3533194
Publikováno v:
Interactions. 28:38-46
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9668018b0cb4a269f84d9525496de992
https://doi.org/10.1145/3442420
https://doi.org/10.1145/3442420
Following on from the publication of its Feasibility Study in December 2020, the Council of Europe's Ad Hoc Committee on Artificial Intelligence (CAHAI) and its subgroups initiated efforts to formulate and draft its Possible Elements of a Legal Frame
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae61e293be778ac59bb53a633d4c2d4e
http://arxiv.org/abs/2202.02776
http://arxiv.org/abs/2202.02776
Autor:
Michael Katell
Publikováno v:
Research Handbook on Information Policy ISBN: 9781789903584
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c987f58ec16002aa623a8b51b06155ae
https://doi.org/10.4337/9781789903584.00025
https://doi.org/10.4337/9781789903584.00025
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
https://doi.org/10.1145/3461702.3462627
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
https://doi.org/10.1145/3442188.3445938
Publikováno v:
SSRN Electronic Journal.
In September 2019, the Council of Europe's Committee of Ministers adopted the terms of reference for the Ad Hoc Committee on Artificial Intelligence (CAHAI). The CAHAI is charged with examining the feasibility and potential elements of a legal framew
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bea4d29772d1cd1ffce0ab6013ba9a79
https://doi.org/10.2139/ssrn.3817999
https://doi.org/10.2139/ssrn.3817999
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
https://doi.org/10.1145/3351095.3372874