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Updated: Jun 30, 2025

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

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Published on: December 15, 2017

Limits of Optimization.

Cesare Carissimo¹, Marcin Korecki¹

¹Computational Social Science, ETH Zurich, Stampfenbachstrasse 48, 8006 Zurich, Switzerland.

Minds and Machines

|March 21, 2024

Summary

This summary is machine-generated.

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.

Keywords:

Artificial intelligence Complex systems Epistemology Ethics Optimization Philosophy of science

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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.