Leverage zones in Responsible AI: towards a systems thinking conceptualization.

Area of Science:

• Artificial Intelligence Ethics
• Systems Thinking
• Sociotechnical Systems

Background:

• Growing debate on the effectiveness of current Responsible AI interventions.
• Risk of Responsible AI becoming a marketing buzzword without addressing core issues.
• Lack of practical guidance for integrating systems thinking into Responsible AI strategies.

Purpose of the Study:

• To propose a novel approach for planning and experimenting with Responsible AI interventions.
• To introduce the Five Ps conceptual framework for constructing holistic interventions.
• To provide practical advice for decision-makers on applying systems thinking to Responsible AI.

Main Methods:

• Adaptation of 'leverage zones' from systems thinking literature.
• Development of the Five Ps conceptual framework.
• Conceptual analysis of intervention levels, from lower-order (e.g., algorithmic tweaks) to higher-order (e.g., redefining foundational structures and purpose).

Main Results:

• The Five Ps framework offers a structured approach to identify and plan interventions.
• The framework facilitates a spectrum of interventions, from technical adjustments to fundamental system redesign.
• It promotes a more comprehensive and potentially impactful approach to achieving Responsible AI.

Conclusions:

• The Five Ps framework serves as a scaffold for transdisciplinary inquiry towards Responsible AI.
• It encourages a shift from superficial fixes to addressing root causes within AI systems.
• Effective Responsible AI requires holistic, systems-level interventions challenging underlying structures and purpose.