Cargando…
Expectations for Artificial Intelligence (AI) in Psychiatry
PURPOSE OF REVIEW: Artificial intelligence (AI) is often presented as a transformative technology for clinical medicine even though the current technology maturity of AI is low. The purpose of this narrative review is to describe the complex reasons for the low technology maturity and set realistic...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9549456/ https://www.ncbi.nlm.nih.gov/pubmed/36214931 http://dx.doi.org/10.1007/s11920-022-01378-5 |
_version_ | 1784805676547047424 |
---|---|
author | Monteith, Scott Glenn, Tasha Geddes, John Whybrow, Peter C. Achtyes, Eric Bauer, Michael |
author_facet | Monteith, Scott Glenn, Tasha Geddes, John Whybrow, Peter C. Achtyes, Eric Bauer, Michael |
author_sort | Monteith, Scott |
collection | PubMed |
description | PURPOSE OF REVIEW: Artificial intelligence (AI) is often presented as a transformative technology for clinical medicine even though the current technology maturity of AI is low. The purpose of this narrative review is to describe the complex reasons for the low technology maturity and set realistic expectations for the safe, routine use of AI in clinical medicine. RECENT FINDINGS: For AI to be productive in clinical medicine, many diverse factors that contribute to the low maturity level need to be addressed. These include technical problems such as data quality, dataset shift, black-box opacity, validation and regulatory challenges, and human factors such as a lack of education in AI, workflow changes, automation bias, and deskilling. There will also be new and unanticipated safety risks with the introduction of AI. SUMMARY: The solutions to these issues are complex and will take time to discover, develop, validate, and implement. However, addressing the many problems in a methodical manner will expedite the safe and beneficial use of AI to augment medical decision making in psychiatry. |
format | Online Article Text |
id | pubmed-9549456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-95494562022-10-11 Expectations for Artificial Intelligence (AI) in Psychiatry Monteith, Scott Glenn, Tasha Geddes, John Whybrow, Peter C. Achtyes, Eric Bauer, Michael Curr Psychiatry Rep Psychiatry in the Digital Age (J Shore, Section Editor) PURPOSE OF REVIEW: Artificial intelligence (AI) is often presented as a transformative technology for clinical medicine even though the current technology maturity of AI is low. The purpose of this narrative review is to describe the complex reasons for the low technology maturity and set realistic expectations for the safe, routine use of AI in clinical medicine. RECENT FINDINGS: For AI to be productive in clinical medicine, many diverse factors that contribute to the low maturity level need to be addressed. These include technical problems such as data quality, dataset shift, black-box opacity, validation and regulatory challenges, and human factors such as a lack of education in AI, workflow changes, automation bias, and deskilling. There will also be new and unanticipated safety risks with the introduction of AI. SUMMARY: The solutions to these issues are complex and will take time to discover, develop, validate, and implement. However, addressing the many problems in a methodical manner will expedite the safe and beneficial use of AI to augment medical decision making in psychiatry. Springer US 2022-10-10 2022 /pmc/articles/PMC9549456/ /pubmed/36214931 http://dx.doi.org/10.1007/s11920-022-01378-5 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Psychiatry in the Digital Age (J Shore, Section Editor) Monteith, Scott Glenn, Tasha Geddes, John Whybrow, Peter C. Achtyes, Eric Bauer, Michael Expectations for Artificial Intelligence (AI) in Psychiatry |
title | Expectations for Artificial Intelligence (AI) in Psychiatry |
title_full | Expectations for Artificial Intelligence (AI) in Psychiatry |
title_fullStr | Expectations for Artificial Intelligence (AI) in Psychiatry |
title_full_unstemmed | Expectations for Artificial Intelligence (AI) in Psychiatry |
title_short | Expectations for Artificial Intelligence (AI) in Psychiatry |
title_sort | expectations for artificial intelligence (ai) in psychiatry |
topic | Psychiatry in the Digital Age (J Shore, Section Editor) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9549456/ https://www.ncbi.nlm.nih.gov/pubmed/36214931 http://dx.doi.org/10.1007/s11920-022-01378-5 |
work_keys_str_mv | AT monteithscott expectationsforartificialintelligenceaiinpsychiatry AT glenntasha expectationsforartificialintelligenceaiinpsychiatry AT geddesjohn expectationsforartificialintelligenceaiinpsychiatry AT whybrowpeterc expectationsforartificialintelligenceaiinpsychiatry AT achtyeseric expectationsforartificialintelligenceaiinpsychiatry AT bauermichael expectationsforartificialintelligenceaiinpsychiatry |