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Leverage zones in Responsible AI: towards a systems thinking conceptualization

There is a growing debate amongst academics and practitioners on whether interventions made, thus far, towards Responsible AI have been enough to engage with the root causes of AI problems. Failure to effect meaningful changes in this system could see these initiatives not reach their potential and...

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Autores principales: Nabavi, Ehsan, Browne, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Palgrave Macmillan UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9984750/
https://www.ncbi.nlm.nih.gov/pubmed/36909257
http://dx.doi.org/10.1057/s41599-023-01579-0
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author Nabavi, Ehsan
Browne, Chris
author_facet Nabavi, Ehsan
Browne, Chris
author_sort Nabavi, Ehsan
collection PubMed
description There is a growing debate amongst academics and practitioners on whether interventions made, thus far, towards Responsible AI have been enough to engage with the root causes of AI problems. Failure to effect meaningful changes in this system could see these initiatives not reach their potential and lead to the concept becoming another buzzword for companies to use in their marketing campaigns. Systems thinking is often touted as a methodology to manage and effect change; however, there is little practical advice available for decision-makers to include systems thinking insights to work towards Responsible AI. Using the notion of ‘leverage zones’ adapted from the systems thinking literature, we suggest a novel approach to plan for and experiment with potential initiatives and interventions. This paper presents a conceptual framework called the Five Ps to help practitioners construct and identify holistic interventions that may work towards Responsible AI, from lower-order interventions such as short-term fixes, tweaking algorithms and updating parameters, through to higher-order interventions such as redefining the system’s foundational structures that govern those parameters, or challenging the underlying purpose upon which those structures are built and developed in the first place. Finally, we reflect on the framework as a scaffold for transdisciplinary question-asking to improve outcomes towards Responsible AI.
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spelling pubmed-99847502023-03-06 Leverage zones in Responsible AI: towards a systems thinking conceptualization Nabavi, Ehsan Browne, Chris Humanit Soc Sci Commun Article There is a growing debate amongst academics and practitioners on whether interventions made, thus far, towards Responsible AI have been enough to engage with the root causes of AI problems. Failure to effect meaningful changes in this system could see these initiatives not reach their potential and lead to the concept becoming another buzzword for companies to use in their marketing campaigns. Systems thinking is often touted as a methodology to manage and effect change; however, there is little practical advice available for decision-makers to include systems thinking insights to work towards Responsible AI. Using the notion of ‘leverage zones’ adapted from the systems thinking literature, we suggest a novel approach to plan for and experiment with potential initiatives and interventions. This paper presents a conceptual framework called the Five Ps to help practitioners construct and identify holistic interventions that may work towards Responsible AI, from lower-order interventions such as short-term fixes, tweaking algorithms and updating parameters, through to higher-order interventions such as redefining the system’s foundational structures that govern those parameters, or challenging the underlying purpose upon which those structures are built and developed in the first place. Finally, we reflect on the framework as a scaffold for transdisciplinary question-asking to improve outcomes towards Responsible AI. Palgrave Macmillan UK 2023-03-04 2023 /pmc/articles/PMC9984750/ /pubmed/36909257 http://dx.doi.org/10.1057/s41599-023-01579-0 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Nabavi, Ehsan
Browne, Chris
Leverage zones in Responsible AI: towards a systems thinking conceptualization
title Leverage zones in Responsible AI: towards a systems thinking conceptualization
title_full Leverage zones in Responsible AI: towards a systems thinking conceptualization
title_fullStr Leverage zones in Responsible AI: towards a systems thinking conceptualization
title_full_unstemmed Leverage zones in Responsible AI: towards a systems thinking conceptualization
title_short Leverage zones in Responsible AI: towards a systems thinking conceptualization
title_sort leverage zones in responsible ai: towards a systems thinking conceptualization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9984750/
https://www.ncbi.nlm.nih.gov/pubmed/36909257
http://dx.doi.org/10.1057/s41599-023-01579-0
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