Evaluating Language Models for Harmful Manipulation
Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it are limited. This paper introduces a framework for evaluating harmful AI manipulation via context-specific human-AI interaction studies. We illustrate the utility of this framework by assessing an AI model with 10,101 participants spanning interactions in three AI use domains (public policy, finance, and health) and three locales (US, UK, and India). Overall, we find that that the tested model can produce manipulative behaviours when prompted to do so and, in experimental settings, is able to induce belief and behaviour changes in study participants. We further find that context m...
| Authors | Canfer Akbulut, Rasmi Elasmar, Abhishek Roy et al. |
|---|---|
| Primary category | cs.AI |
| Published | 26 March 2026 |
| Last updated at source | 13 April 2026 |
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