Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Jeff Hancock"'
Autor:
Xun Sunny Liu, Jeff Hancock
Publikováno v:
Computers in Human Behavior: Artificial Humans, Vol 2, Iss 2, Pp 100079- (2024)
This research proposes and investigates the presumed allo-enhancement effect of social robot perceptions, a tendency for individuals to view social robots as more beneficial for others than for themselves. We discuss this as a systematic bias in the
Externí odkaz:
https://doaj.org/article/623d579595df43bfa19f1e82f35c5b66
Publikováno v:
Frontiers in Psychiatry, Vol 10 (2019)
Conversational artificial intelligence (AI) is changing the way mental health care is delivered. By gathering diagnostic information, facilitating treatment, and reviewing clinician behavior, conversational AI is poised to impact traditional approach
Externí odkaz:
https://doaj.org/article/fd8f2663ec5e40a7b0800ff18235eb94
Publikováno v:
Proceedings of the ACM Web Conference 2023.
Autor:
Adam S. Miner, Scott L. Fleming, Albert Haque, Jason A. Fries, Tim Althoff, Denise E. Wilfley, W. Stewart Agras, Arnold Milstein, Jeff Hancock, Steven M. Asch, Shannon Wiltsey Stirman, Bruce A. Arnow, Nigam H. Shah
Publikováno v:
npj Mental Health Research. 1
Although individual psychotherapy is generally effective for a range of mental health conditions, little is known about the moment-to-moment language use of effective therapists. Increased access to computational power, coupled with a rise in compute
Autor:
Adam S Miner, Scott L Fleming, Albert Haque, Jason A Fries, Tim Althoff, Denise E Wilfley, W. Stewart Agras, Arnold Milstein, Jeff Hancock, Steven M Ash, Shannon Wiltsey Stirman, Bruce A. Arnow, Nigam H. Shah
Although individual psychotherapy is generally effective for a range of mental health conditions, little is known about the moment-to-moment language use of effective therapists. Increased access to computational power, coupled with a rise in compute
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac446ef4f91e4489c2cea0a8bd1e384d
https://doi.org/10.1101/2022.04.24.22274227
https://doi.org/10.1101/2022.04.24.22274227
Autor:
Mitchell L. Gordon, Michelle S. Lam, Joon Sung Park, Kayur Patel, Jeff Hancock, Tatsunori Hashimoto, Michael S. Bernstein
Whose labels should a machine learning (ML) algorithm learn to emulate? For ML tasks ranging from online comment toxicity to misinformation detection to medical diagnosis, different groups in society may have irreconcilable disagreements about ground
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2865f23c887fff6a9cba54227e01a28
http://arxiv.org/abs/2202.02950
http://arxiv.org/abs/2202.02950
Publikováno v:
Science (New York, N.Y.). 375(6578)
An account of privacy’s evolutionary roots may hold lessons for policies in the digital age
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
Journal of Online Trust and Safety. 1
Introducing the Journal of Online Trust and Safety