Using Large Language Models in Behavioral Science Interventions: Promise & Risk
Year: 2025
Type: article
Abstract: Many behavioral science-based interventions, such as nudges and so-called psychologically wise interventions, seek to improve people’s lives by using words to shift them toward helpful perspectives and behaviors. Large language models (LLMs) such as OpenAI’s GPT models or Google’s Gemini have the potential to revolutionize these interventions by making them more personalized, scalable, and cost-effective. This article describes how three groups of people—designers of interventions, intermediaries who interact with the intended beneficiaries, and the intended beneficiaries themselves—might use LLMs and identifies potential benefits and risks of those uses for the intended beneficiaries of interventions. We hypothesize that the potential benefits and risks are lowest when designers interact with LLMs, higher when intermediaries interact, and highest when the intended beneficiaries interact directly. We provide suggestions for mitigating the risks so that policymakers can safely deliver on the promise of LLMs.
Source: Behavioral Science & Policy
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid:
OpenAlex ID: W4411796427