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AI Implementation Science for Social Issues: Pitfalls and Tips

The social implementation of knowledge and technologies that are effective in epidemiological and observational studies is essential for solving social issues. In particular, there have been few attempts to implement clinical practices and information communication technologies that utilize data in...

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Detalles Bibliográficos
Autor principal: Takaoka, Kota
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japan Epidemiological Association 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918616/
https://www.ncbi.nlm.nih.gov/pubmed/35095090
http://dx.doi.org/10.2188/jea.JE20210278
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author Takaoka, Kota
author_facet Takaoka, Kota
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description The social implementation of knowledge and technologies that are effective in epidemiological and observational studies is essential for solving social issues. In particular, there have been few attempts to implement clinical practices and information communication technologies that utilize data in the field. We describe the four stages of social implementation: 1) redefining social issues as solvable problems, 2) finding technological solutions to solvable problems, 3) social implementation contributing to the solutions, and 4) horizontal deployment of effective methods for solving social issues. Introducing a use case of artificial intelligence (AI) social implementation in child-abuse response conducted by our team, we discuss pitfalls and tips as a frame of reference to demonstrate data utilization as social infrastructure for solving social issues and to consider practical solutions in a logical manner.
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spelling pubmed-89186162022-04-05 AI Implementation Science for Social Issues: Pitfalls and Tips Takaoka, Kota J Epidemiol Special Article The social implementation of knowledge and technologies that are effective in epidemiological and observational studies is essential for solving social issues. In particular, there have been few attempts to implement clinical practices and information communication technologies that utilize data in the field. We describe the four stages of social implementation: 1) redefining social issues as solvable problems, 2) finding technological solutions to solvable problems, 3) social implementation contributing to the solutions, and 4) horizontal deployment of effective methods for solving social issues. Introducing a use case of artificial intelligence (AI) social implementation in child-abuse response conducted by our team, we discuss pitfalls and tips as a frame of reference to demonstrate data utilization as social infrastructure for solving social issues and to consider practical solutions in a logical manner. Japan Epidemiological Association 2022-04-05 /pmc/articles/PMC8918616/ /pubmed/35095090 http://dx.doi.org/10.2188/jea.JE20210278 Text en © 2022 Kota Takaoka. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Special Article
Takaoka, Kota
AI Implementation Science for Social Issues: Pitfalls and Tips
title AI Implementation Science for Social Issues: Pitfalls and Tips
title_full AI Implementation Science for Social Issues: Pitfalls and Tips
title_fullStr AI Implementation Science for Social Issues: Pitfalls and Tips
title_full_unstemmed AI Implementation Science for Social Issues: Pitfalls and Tips
title_short AI Implementation Science for Social Issues: Pitfalls and Tips
title_sort ai implementation science for social issues: pitfalls and tips
topic Special Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918616/
https://www.ncbi.nlm.nih.gov/pubmed/35095090
http://dx.doi.org/10.2188/jea.JE20210278
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