Teaming up people with AI can actually lead to worse decisions than if either of them just worked alone.
March 24, 2026
Original Paper
Optimal Human AI Coordination in Decision Workflows: Collaboration Paradox and Automation Cliffs
SSRN · 6417798
The Takeaway
The common assumption is that 'Human + AI' is the gold standard for accuracy, but this paper identifies 'automation cliffs' where human experts stop paying attention or change their behavior. This creates a paradox where the combined system performance actually drops below the baseline of the human or the AI operating independently.
From the abstract
As AI systems are integrated into organizational workflows, decision makers must determine how AI should be used for a given task: whether decisions are made by AI alone, by humans alone, or with AI assistance. We study this problem using a game-theoretic framework in which a coordinator commits to a randomized coordination policy to maximize system performance subject to limited human capacity, while human experts choose their level of involvement to minimize effort subject to a minimum perform