The Potential Impact of Emerging Technologies on Democratic Representation: Evidence from a Field Experiment

New Media and Society, Forthcoming

40 Pages Posted: 21 Feb 2023

See all articles by Sarah Kreps

Sarah Kreps

Cornell University - Department of Government

Douglas L. Kriner

Cornell University - Department of Government

Date Written: February 14, 2023

Abstract

Advances in machine learning have created natural language models that can mimic human writing style and substance. Here we investigate the challenge that machine generated content such as that produced by GPT-3 presents to democratic representation by assessing the extent to which machine-generated content can pass as constituent sentiment. We conduct a field experiment in which we send both hand-written and machine-generated letters (a total of 32,398 emails) to 7,132 state legislators. We compare legislative response rates for the human versus machine-generated constituency letters to gauge whether language models can approximate and scale up inauthentic constituency voice. Legislators were only slightly less likely to respond to AI-generated content than to human-written emails; the 2% difference in response rate was statistically significant but substantively small. Qualitative evidence sheds light on the potential perils that this technology presents for democratic representation, but also suggests potential techniques that legislators might employ to guard against AI-sourced astroturfing.

Suggested Citation

Kreps, Sarah and Kriner, Douglas L., The Potential Impact of Emerging Technologies on Democratic Representation: Evidence from a Field Experiment (February 14, 2023). New Media and Society, Forthcoming, Available at SSRN: https://ssrn.com/abstract=4358982

Sarah Kreps (Contact Author)

Cornell University - Department of Government ( email )

Douglas L. Kriner

Cornell University - Department of Government ( email )

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