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Systemic Perspective, Leverage Points and Artificial Intelligence—Part II

The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.

By Mauricio Covarrubias
February 9, 2024

This second part focuses on the transformative potential of Artificial Intelligence (AI) in evaluating and implementing leverage points within social systems; these are key to a system transforming itself, which is what is meant by systemic transformation. Donella Meadows observes: “This idea is not unique to systems analysis — it’s embedded in legend. The silver bullet, the trimtab, the miracle cure, the secret passage, the magic password, the single hero who turns the tide of history. The nearly effortless way to cut through or leap over huge obstacles. We not only want to believe that there are leverage points, we want to know where they are and how to get our hands on them. Leverage points are points of power.”

The authors of AI Brings Science to the Art of Policymaking, point out that: “Governments have started to rely on artificial intelligence (AI) to deliver services and improve operations, but the use of it to help shape policy is just beginning. The foundations of policymaking—specifically, the ability to sense patterns of need, develop evidence-based programs, forecast outcomes and analyze effectiveness—fall squarely in AI’s “sweet spot”.  In addition, we advocate for the broader utilization of AI to gain deeper insights into social issues and pinpoint leverage points for their resolution.

AI Makes Complex Systems Legible

AI enables a deep and holistic understanding of social problems, illuminating their complexity and interconnected nature. By processing and analyzing vast amounts of data, AI identifies patterns and relationships within social systems that are critical to identifying the leverage points upon which effective intervention is predicated. Indeed, the ability of AI and big data to pinpoint leverage points offers immense value to the development of well-informed policies and intervention strategies. Armed with the knowledge of where an intervention is likely to be most impactful, policymakers can strategically allocate resources and efforts, thereby maximizing the social good that results and enhancing the overall effectiveness of social interventions and initiatives.

Moreover, the contribution of AI and big data to the identification of leverage points is not purely reactive in nature, i.e. aimed at solving present problems. It is equally effective as a means of prevention, i.e. increasing the resilience of social systems in the face of future threats—which is exceptionally valuable in a world of growing interdependence and unprecedented systemic risks.

Key Contributions of AI in this Process

Large-Scale Data Analysis. AI scrutinizes vast data to identify hidden patterns and correlations, pinpointing key variables as effective leverage points in social systems.

Modeling and Simulation. AI algorithms simulate various policy scenarios and outcomes, assisting policymakers in predicting effects and identifying optimal leverage points.

Prediction and Forecasting. Utilizing historical and current data, AI forecasts the impacts of specific systemic changes, aiding in locating effective leverage points. For example, AI-driven forecasts can assist urban planners in anticipating changes in traffic flow due to new public transit routes.

Analysis of Social Networks and Behaviors. AI analyzes social network interactions to identify influential points for potential change.

Customization of Strategies. AI tailors strategies to meet specific group needs and characteristics, refining the precision and impact of leverage points.

Continuous Evaluation. AI enables ongoing monitoring and assessment of policy impacts, facilitating dynamic adjustments to leverage points for enhanced effectiveness.

AI is not merely a tool for insights; it is a transformative force in public policy management. It addresses the complexities of social systems, leading to more informed and effective interventions.

AI in Public Policy Design

In today’s world, marked by significant technological progress and increasingly complex social issues, it’s imperative to leverage AI as a vital instrument in crafting public policies. AI’s ability to pinpoint influential factors can be remarkably beneficial across diverse policy domains. The ensuing hypothetical examples demonstrate AI’s capacity to offer novel and efficacious approaches in addressing and resolving societal challenges.

Urban Planning and Development. AI can analyze extensive urban data, identifying critical leverage points like public transport hubs or green spaces to enhance urban livability. In urban planning, AI’s analysis could lead to optimized public transport routes that significantly reduce commute times and pollution.

Healthcare System Reform. AI can evaluate patient data, treatment outcomes and resource allocation in healthcare to identify leverage points, potentially focusing on preventive care or resource optimization in hospitals.

Environmental Policy. AI can pinpoint crucial leverage points in ecosystems for conservation efforts, like areas significantly impacting biodiversity preservation.

These examples represent just a sample of what is possible, highlighting the need to continue researching the applications of AI in public policies. The integration of AI into governance is not only promising, but also essential to address the dynamic complexities and challenges of today’s world.


The application of AI in policymaking will likely be developed within the framework of broader data analysis and processing initiatives. In this context, the synergy of systemic perspectives, leverage points and AI presents a novel direction in public policy. By harnessing AI, policymakers gain deeper insights into social systems, facilitating the identification of influential leverage points and policy formulation. This approach, while still evolving, holds the potential to enhance informed, effective and adaptable governance in addressing complex social challenges.

Author: Mauricio Covarrubias is Professor at the National Institute of Public Administration in Mexico.  He is co-founder of the International Academy of Political-Administrative Sciences (IAPAS).  He is the founder and Editor of the International Journal of Studies on Educational Systems (RIESED). Member of the National System of Researchers of CONACYT.  He received his Ph.D. from the National Autonomous University of Mexico.  He can be reached at [email protected] and followed on Twitter @OMCovarrubias

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