Systemic Perspective, Leverage Points and Artificial Intelligence: Part I
The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.
By Mauricio Covarrubias
January 12, 2024
In the intricate landscape of public policies, the adoption of a systemic approach and the identification of leverage points are essential elements for effectively addressing social challenges. This column explores the concepts of the systemic approach and leverage points, emphasizing their relevance and application in the design of public policies, with a forward-looking perspective supported by artificial intelligence (AI).
The systemic approach enables an understanding of social reality as a system—a set of interrelated elements with a common goal (Bertalanffy, 1976). This involves identifying components, relationships, functions and behaviors of the social system, as well as the environment in which it exists (Churchman, 1971). Additionally, it entails analyzing the emergent properties of the system—those that cannot be deduced from the properties of its parts but arise from their interaction (Wheatley, 2006).
The concept of leverage points allows for identifying optimal alternatives for intervening in a system, aiming to generate positive and lasting changes (Meadows, 2009). It involves recognizing that not all actions have the same impact and prioritizing those that affect the most strategic and sensitive elements of the system (Senge, 2006). It also implies evaluating the direct and indirect effects, both short and long-term, of state interventions, considering possible scenarios and system feedback (Williams & Hummelbrunner, 2011).
Breaking Down the Concept of Leverage Points:
A leverage point is a variable or factor that can modify the behavior of a social system, leading to significant changes in its outcomes. Leverage points can be of different natures such as norms, incentives, values, beliefs, capabilities, structures, processes, etc. (Meadows, 2009 and Senge, 2006).
Leverage points can be classified according to their level of effectiveness, with the most effective ones affecting the paradigms, objectives and rules of the system, and the less effective ones affecting the parameters, flows and stocks of the system.
- Paradigms are ideas, principles and beliefs that determine how the system is perceived and understood, guiding the decisions and actions of system actors.
- Objectives are goals, purposes and aims that guide the functioning and behavior of the system, defining criteria for success and evaluation.
- Rules are norms, laws and protocols regulating the relationships and interactions between the elements of the system, establishing limits and constraints.
- Parameters are variables, indicators and factors describing and characterizing the state and performance of the system, modifiable or adjustable by system actors.
- Flows are inputs, outputs and transfers of information, energy, materials, resources, etc., occurring within and outside the system, determining the dynamics and change of the system.
- Stocks are quantities, volumes and accumulations of information, energy, materials, resources, etc., stored or preserved in the system, determining the stability and resistance of the system.
The systemic approach and the concept of leverage points are highly useful conceptual and methodological tools for the design of public policies, enabling the understanding and transformation of social reality from a holistic, complex and dynamic perspective. However, these concepts alone are insufficient to guarantee the success of public policies, as other factors influence their formulation, implementation and evaluation, such as political, economic, social and cultural contexts, available resources, institutional capacity, political will, citizen participation, accountability, etc.
Therefore, it is recommended that the systemic approach and the concept of leverage points be complemented with other tools and approaches, adapting to the context and characteristics of each problem and public policy.
Revealing Leverage Points with AI
In the pursuit of advancing our comprehension of leverage points and their application in the design of public policies, various avenues of future research hold the potential to contribute significantly. One particularly promising line of inquiry involves the development and refinement of methods to identify leverage points, with a specific focus on harnessing the capabilities of AI. The integration of AI in this context presents a transformative opportunity to enhance the efficiency and accuracy of identifying strategic leverage points within complex societal systems.
Traditional methods for pinpointing these leverage points often entail substantial costs and laborious processes. The application of artificial intelligence offers a novel approach by leveraging machine learning algorithms and data analytics to process vast and intricate datasets efficiently. AI has the capacity to analyze multifaceted relationships, discern patterns and identify nuanced leverage points that might be challenging for conventional methods to uncover. This not only streamlines the research process but also opens up new possibilities for uncovering subtle yet influential factors within the intricate web of social systems.
The topic will continue in the next column.
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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Systemic Perspective, Leverage Points and Artificial Intelligence: Part I
The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.
By Mauricio Covarrubias
January 12, 2024
In the intricate landscape of public policies, the adoption of a systemic approach and the identification of leverage points are essential elements for effectively addressing social challenges. This column explores the concepts of the systemic approach and leverage points, emphasizing their relevance and application in the design of public policies, with a forward-looking perspective supported by artificial intelligence (AI).
The systemic approach enables an understanding of social reality as a system—a set of interrelated elements with a common goal (Bertalanffy, 1976). This involves identifying components, relationships, functions and behaviors of the social system, as well as the environment in which it exists (Churchman, 1971). Additionally, it entails analyzing the emergent properties of the system—those that cannot be deduced from the properties of its parts but arise from their interaction (Wheatley, 2006).
The concept of leverage points allows for identifying optimal alternatives for intervening in a system, aiming to generate positive and lasting changes (Meadows, 2009). It involves recognizing that not all actions have the same impact and prioritizing those that affect the most strategic and sensitive elements of the system (Senge, 2006). It also implies evaluating the direct and indirect effects, both short and long-term, of state interventions, considering possible scenarios and system feedback (Williams & Hummelbrunner, 2011).
Breaking Down the Concept of Leverage Points:
A leverage point is a variable or factor that can modify the behavior of a social system, leading to significant changes in its outcomes. Leverage points can be of different natures such as norms, incentives, values, beliefs, capabilities, structures, processes, etc. (Meadows, 2009 and Senge, 2006).
Leverage points can be classified according to their level of effectiveness, with the most effective ones affecting the paradigms, objectives and rules of the system, and the less effective ones affecting the parameters, flows and stocks of the system.
The systemic approach and the concept of leverage points are highly useful conceptual and methodological tools for the design of public policies, enabling the understanding and transformation of social reality from a holistic, complex and dynamic perspective. However, these concepts alone are insufficient to guarantee the success of public policies, as other factors influence their formulation, implementation and evaluation, such as political, economic, social and cultural contexts, available resources, institutional capacity, political will, citizen participation, accountability, etc.
Therefore, it is recommended that the systemic approach and the concept of leverage points be complemented with other tools and approaches, adapting to the context and characteristics of each problem and public policy.
Revealing Leverage Points with AI
In the pursuit of advancing our comprehension of leverage points and their application in the design of public policies, various avenues of future research hold the potential to contribute significantly. One particularly promising line of inquiry involves the development and refinement of methods to identify leverage points, with a specific focus on harnessing the capabilities of AI. The integration of AI in this context presents a transformative opportunity to enhance the efficiency and accuracy of identifying strategic leverage points within complex societal systems.
Traditional methods for pinpointing these leverage points often entail substantial costs and laborious processes. The application of artificial intelligence offers a novel approach by leveraging machine learning algorithms and data analytics to process vast and intricate datasets efficiently. AI has the capacity to analyze multifaceted relationships, discern patterns and identify nuanced leverage points that might be challenging for conventional methods to uncover. This not only streamlines the research process but also opens up new possibilities for uncovering subtle yet influential factors within the intricate web of social systems.
The topic will continue in the next column.
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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