What it means
Human-AI collaboration describes how people and AI systems divide and share work, so that each contributes what they do best and the combined result is better than either alone. It covers task allocation, interaction design, trust and responsibility.
Real-world example
In a hospital's radiology department, AI flags scans with possible findings and prioritises the worklist, while radiologists make every diagnosis. The team deliberately designed the interface so radiologists form their own view before seeing the AI's flag on certain scan types, to reduce the risk of simply following the AI.
Why it matters for AI adoption
The value of AI often depends less on the model than on how well the collaboration is designed. Poor design can lead to over-reliance, deskilling or frustration; good design supports people's judgement and keeps responsibility clear.
Questions to ask
- Which parts of the task should AI do, which should people do, and why?
- How do we prevent over-reliance on AI while still benefiting from it?