Computer Science

When combinations of humans and AI are useful: A systematic review and meta-analysis

M. Vaccaro, A. Almaatouq, et al.

In this preregistered systematic review and meta-analysis, researchers Michelle Vaccaro, Abdullah Almaatouq, and Thomas Malone explored when human-AI combinations excel beyond humans or AI on their own. Surprisingly, they found that, on average, these combinations performed worse, especially in decision-making tasks, but hinted at potential advantages in content creation. Their insights unveil the complex dynamics of collaboration between humans and AI.

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Abstract

This preregistered systematic review and meta-analysis of 106 experimental studies (370 effect sizes) investigated when human-AI combinations outperform humans or AI alone. The analysis revealed that, on average, human-AI combinations performed worse than the best of humans or AI alone. However, performance losses were more pronounced in decision-making tasks, while content creation tasks showed potential gains. The relative performance of humans and AI also significantly influenced the results; human-AI combinations outperformed both when humans initially outperformed AI, but underperformed when AI was initially superior. Limitations include potential publication bias and variations in study designs.

Publisher

Nature Human Behaviour

Published On

Dec 01, 2024

Authors

Michelle Vaccaro, Abdullah Almaatouq, Thomas Malone

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