Enhancing Complementary Team Performance Through Intelligent Helping

Abstract

Effectively leveraging artificial intelligence (AI) requires aligning human reliance on AI with humans’ cognitive strengths and limitations. Despite the objective advantages of AI in performing specific tasks, humans often struggle to correctly rely on help from AI to maximize the Complementary Team Performance (CTP), exceeding the individual performances by either humans or AI. To address this challenge, we propose the design feature Intelligent Helping, which steers human behavior by strategically providing different types of AI help and thus aligning reliance with AI’s superior judgment while ensuring that humans retain full control. We designed an experiment with four archetypes of task performances and four treatments to modulate human interaction with AI. Our results show that reliance on AI can be shaped by tailored treatments, significantly improving CTP. Intelligent Helping enables high-performing AI in which humans retain full control over decisions, providing new opportunities for effective collaboration between humans and AI.

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