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The aim is to explore how automation affects social science research and the implications for maintaining scientific integrity.

June 13, 2026DaedalusOpen Access

Making Automation Work for Social Scientists

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This commentary discusses potential risks of AI in social science and suggests actionable insights to preserve research integrity.

The aim is to explore how automation affects social science research and the implications for maintaining scientific integrity.
Analysis of the automation landscape in social science, particularly LLMs and machine learning applications.
Collaboration with experts in anthropology to examine the socio-political context of technology in research.
Discussion on industry funding influences and the need for transparency in automated tools.
Highlighted the risks of biases inherent in proprietary AI models and their impact on scientific outcomes.
Identified the tendency for industry funding to shape research focus and potentially stifle innovation.
Proposed actionable steps for scientists to reclaim epistemic agency through open-source tools and diverse methodologies.

M. J. Crockett (2026) studied this question.

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