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Leverage zones in Responsible AI: towards a systems thinking conceptualization.
Nabavi, Ehsan; Browne, Chris.
  • Nabavi E; Responsible Innovation Lab, Center for Public Awareness of Sciences, The Australian National University, Canberra, ACT Australia.
  • Browne C; Responsible Innovation Lab, Center for Public Awareness of Sciences, The Australian National University, Canberra, ACT Australia.
Humanit Soc Sci Commun ; 10(1): 82, 2023.
Article in English | MEDLINE | ID: covidwho-2273458
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Humanit Soc Sci Commun Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Humanit Soc Sci Commun Year: 2023 Document Type: Article