ImpactBench is an evolving, expert-guided benchmark that currently evaluates frontier AI models across 800 metrics and 26 rigorous benchmarks. These data points are then distilled into an AI Nutrition Label, a simple, at-a-glance rating. The labels reveal how a given AI system scores on avoiding harms, like factual hallucination, sycophancy, and toxicity, and how it is actively promoting beneficial behaviors, such as user agency.
Nutrition labels tell people what’s inside the food they eat, yet the AI systems increasingly shaping how people think, decide, and connect come with no equivalent. Drawing on the MIT Media Lab’s 40 years of work at the intersection of technology and human experience, and on more than 80 experts across more than 40 institutions, the Advancing Humans with AI research program is building one: a nutrition label for the systems shaping our future. At a pivotal moment for AI, these labels give people clear information to choose technology that supports their wellbeing, and gives decision makers evidence to act on.
Each benchmark begins as an open submission from a clinician, educator, legal scholar, or community advocate, then moves through a multi-turn simulation designed to surface behaviors that may only emerge over the course of a full conversation, not a single exchange.
Researchers, domain experts, and organizations are invited to use the platform, suggest new benchmarks, validate existing ones, and help shape how results are presented. Visit impactbench.media.mit.edu to explore the benchmark and contribute.
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