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Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Research summary
Mixed-method studies across three datasets found gains from AI assistance, but explanations did not improve complementary performance. Explanations increased acceptance of AI advice whether that advice was correct or not.
Evidence strengths
- Mixed-method user studies
- Three datasets
- Separates acceptance of advice from correctness
Limitations
- Limited task domains
- Explanations and interfaces may not represent newer generative AI systems
Topics
- Human-AI Interaction
- Artificial Intelligence
- Social Intelligence
Connected claims
- Qualifies
Human-AI collaboration does not reliably outperform the better standalone human or AI; results depend strongly on the task and interaction design.
Explanations increased acceptance of AI advice but did not increase complementary team performance.