Research · MIT Technology Review
The critical questions: Can AI function as a productive participant within human teams
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◌ Single Source
Through their research on AI deployment across multiple sectors, the reporter has seen several organizations already moving—deliberately and experimentally—toward the HAIC benchmarks the reporter favor.
Key facts
- The reporter has studied real-world AI deployment since 2022 in small businesses and health, humanitarian, nonprofit, and higher-education organizations in the UK, the United States, and Asia, as well
- For example, in one UK hospital system in the period 2021–2024, the question expanded from whether a medical AI application improves diagnostic accuracy to how the presence of AI
- Angela Aristidou is a professor at University College London and a faculty fellow at the Stanford Digital Economy Lab and the Stanford Human-Centered AI Institute
- According to Stanford’s 2026 AI Index, AI is sprinting, and they're struggling to keep up
Summary
For decades, artificial intelligence has been evaluated through the question of whether machines outperform humans. This framing is seductive: An AI vs. human comparison on isolated problems with clear right or wrong answers is easy to standardize, compare, and optimize. But there’s a problem: AI is almost never used in the way it is benchmarked. While AI is evaluated at the task level in a vacuum, it is used in messy, complex environments where it usually interacts with more than one person. To mitigate this, it’s time to shift from narrow methods to benchmarks that assess how AI systems perform over longer time horizons within human teams, workflows, and organizations.