Zobrazeno 1 - 10
of 1 031 113
pro vyhledávání: '"A. A. Harms"'
Autor:
Sollund, Ragnhild Aslaug
The fields of environmental crime and speciesism are of increasing interest to social scientists. This increase reflects the great concern many people-academics as well as non-academics-now feel for the situation of our planet and its vanishing speci
Publikováno v:
RSF: The Russell Sage Foundation Journal of the Social Sciences, 2024 Jun 01. 10(2), 30-68.
Externí odkaz:
https://www.jstor.org/stable/48775324
Autor:
Wang, Andy Z.1
Publikováno v:
University of Chicago Law Review. Nov2024, Vol. 91 Issue 7, p2093-2137. 45p.
Autor:
Papaioannou, Diana1 (AUTHOR) d.papaioannou@sheffield.ac.uk, Sprange, Kirsty2 (AUTHOR), Hamer-Kiwacz, Sienna1 (AUTHOR), Mooney, Cara1 (AUTHOR), Moody, Gwenllian3 (AUTHOR), Cooper, Cindy1 (AUTHOR)
Publikováno v:
Trials. 3/4/2024, Vol. 25 Issue 1, p1-13. 13p.
Autor:
Li, Tianjing1,2 (AUTHOR) tianjing.li@cuanschutz.edu, Mayo-Wilson, Evan3 (AUTHOR), Shaughnessy, Daniel1,2 (AUTHOR), Qureshi, Riaz1,2 (AUTHOR)
Publikováno v:
Trials. 6/20/2024, Vol. 25 Issue 1, p1-5. 5p.
Autor:
Ovalle, Anaelia, Pavasovic, Krunoslav Lehman, Martin, Louis, Zettlemoyer, Luke, Smith, Eric Michael, Williams, Adina, Sagun, Levent
Natural-language assistants are designed to provide users with helpful responses while avoiding harmful outputs, largely achieved through alignment to human preferences. Yet there is limited understanding of whether alignment techniques may inadverte
Externí odkaz:
http://arxiv.org/abs/2411.03700
As conversational AI systems increasingly permeate the socio-emotional realms of human life, they bring both benefits and risks to individuals and society. Despite extensive research on detecting and categorizing harms in AI systems, less is known ab
Externí odkaz:
http://arxiv.org/abs/2410.20130
Large language models (LLMs) are increasingly integrated into a variety of writing tasks. While these tools can help people by generating ideas or producing higher quality work, like many other AI tools they may risk causing a variety of harms, dispr
Externí odkaz:
http://arxiv.org/abs/2410.00906
Autor:
Brickley, Bryce1 (AUTHOR) bryce.brickley@flinders.edu.au, Moore, Samuel1 (AUTHOR), Tari-Keresztes, Noemi1 (AUTHOR), Brand, Anthea2 (AUTHOR), Bower, Madeleine3 (AUTHOR), Bonson, Jason G.1 (AUTHOR), McEntee, Alice4,5 (AUTHOR), Bartram, Ashlea J.4,5 (AUTHOR), Bovopoulos, Nataly6 (AUTHOR), McPhie, Skye6 (AUTHOR), Martin, Craig6 (AUTHOR), Wright, Cassandra7,8,9 (AUTHOR), Bowden, Jacqueline4,5 (AUTHOR), Smith, James A.1 (AUTHOR)
Publikováno v:
Harm Reduction Journal. 9/20/2024, Vol. 21 Issue 1, p1-18. 18p.
Recommender systems have become integral to digital experiences, shaping user interactions and preferences across various platforms. Despite their widespread use, these systems often suffer from algorithmic biases that can lead to unfair and unsatisf
Externí odkaz:
http://arxiv.org/abs/2409.06916