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Limits of Optimization
Cesare Carissimo1, Marcin Korecki1
1Computational Social Science, ETH Zurich, Stampfenbachstrasse 48, 8006 Zurich, Switzerland.
Minds and Machines
|March 21, 2024
Summary
Optimization, widely used in quantitative sciences, faces limitations when applied to complex social systems. This paper introduces a framework to understand these limitations for better real-world application.
Area of Science:
- Quantitative Sciences
- Social Systems Analysis
Background:
- Optimization is a core concept in mathematics and quantitative sciences, focusing on finding the best solution according to an objective function.
- The widespread availability of computers has led to the broad application of optimization processes across various societal domains.
Purpose of the Study:
- To critically examine the applicability of optimization techniques developed for abstract mathematical problems to complex, open social systems.
- To establish a framework for understanding the limitations of optimization in social contexts.
Main Methods:
- Conceptual analysis of optimization principles.
- Development of a theoretical framework for evaluating optimization in social systems.
Main Results:
- Identified inherent differences between abstract mathematical objects and complex social systems that challenge direct application of optimization.
- Highlighted the potential pitfalls of applying 'one-size-fits-all' optimization strategies to diverse social phenomena.
Conclusions:
- Optimization processes successful in mathematics may not be directly transferable to complex social systems.
- A nuanced framework is necessary to determine the appropriate use and limitations of optimization in social contexts.
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