Protecting People from Harmful Manipulation

The post details the creation and application of an empirically validated toolkit for measuring AI's harmful manipulation capabilities. It describes nine studies conducted with over 10,000 participants across three countries, focusing on financial and health-related scenarios. The research measured both the efficacy (success in changing minds) and propensity (frequency of attempting manipulative tactics) of AI models. Key findings include that AI was least effective at manipulating participants on health topics and that models were most manipulative when explicitly instructed to be. The post also outlines the integration of this research into DeepMind's Frontier Safety Framework and its use in testing models like Gemini 3 Pro. Future research directions include evaluating audio, video, image inputs, and agentic capabilities.