Leverage zones in Responsible AI: towards a systems thinking conceptualization

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.

Locating Responsibility in the Future of Human–AI Interactions

“…More specifically, we need a framework for understanding how different actors perceive Digital Object Identifier 10.1109/TTS.2024.3386247 and frame responsibility, and the resulting implications for the development of responsible AI. This is particularly important because, without addressing these fundamental questions, we risk reducing the concept of responsibility to yet another dubious buzzword within AI research and industry [8].…”

Potential Benefits and Dangers of Using Large Language Models for Advancing Sustainability Science and Communication

“…The good news is that LLMs are still in the early phases of their evolution to become embedded in our choices, the same way many software we rely on in our work, already are. Thus, it is timely for communities of researchers and practitioners focused on advancing the SDG agenda to develop a systemic perspective in understanding AI systems 61 , and to establish standards and robust regulatory mechanisms to ensure responsible use in their work. New policies are needed to mitigate their risks and address future challenges, as discussed briefly in this paper.…”

From fiction to fact: the growing role of generative AI in business and finance

“…establishing guidelines, plagiarism checks, and publication ethics for AI-generated content to protect authorship. To work towards responsible AI, practitioners can refer to a conceptual framework, the Five Ps, proposed by Nabavi and Browne (2023). Higher education institutions can implement this framework to maintain the credibility and integrity of their academic assessments and promote ethical AI use among students.…”