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<p>This paper explores the integration of machine learning into economics and social sciences, assessing its potential impact and limitations. It introduces fundamental machine learning concepts and principles, highlighting the differences between the two disciplines, particularly the focus on causal inference in economics and prediction in machine learning. The paper discusses diverse applications of machine learning, from extracting insights from unstructured data to creating novel indicators and improving predictive accuracy, while also addressing challenges related to data quality, computational efficiency, and data ownership. It emphasizes the importance of standardization, transparency, and ethical considerations in prediction tasks, recognizing that machine learning is a powerful tool but cannot replace economic theory. Ultimately, researchers remain optimistic about the transformative potential of machine learning in re-shaping research methodologies and generating new insights in economics and social sciences.</p>
</abstract>

This paper explores the integration of machine learning into economics and social sciences, assessing its potential impact and limitations. It introduces fundamental machine learning concepts and principles, highlighting the differences between the two disciplines, particularly the focus on causal inference in economics and prediction in machine learning. The paper discusses diverse applications of machine learning, from extracting insights from unstructured data to creating novel indicators and improving predictive accuracy, while also addressing challenges related to data quality, computational efficiency, and data ownership. It emphasizes the importance of standardization, transparency, and ethical considerations in prediction tasks, recognizing that machine learning is a powerful tool but cannot replace economic theory. Ultimately, researchers remain optimistic about the transformative potential of machine learning in re-shaping research methodologies and generating new insights in economics and social sciences.

Evaluating the Role of Machine Learning in Economics: A Cutting-Edge Addition or Rhetorical Device?

Studies in Logic, Grammar and Rhetoric

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper explores the integration of machine learning into economics and social sciences, assessing its potential impact and limitations. It introduces...

Evaluating the Role of Machine Learning in Economics: A Cutting-Edge Addition or Rhetorical Device?

Data publikacji: 31 gru 2023

Zakres stron: 279 - 293

DOI: https://doi.org/10.2478/slgr-2023-0014

Słowa kluczowe
machine learning, rhetotic in economics, scientific progress

© 2023 Sławomir Czech, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Evaluating the Role of Machine Learning in Economics: A Cutting-Edge Addition or Rhetorical Device?

Data publikacji: 31 gru 2023

Zakres stron: 279 - 293

DOI: https://doi.org/10.2478/slgr-2023-0014

Słowa kluczowemachine learning, rhetotic in economics, scientific progress

© 2023 Sławomir Czech, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
machine learning, rhetotic in economics, scientific progress