Paper Number

1338

Paper Type

short

Description

While artificial intelligence (AI) has great potential to transform how we work, it’s clear that in many contexts, humans and AI will work side by side. According to recent research, humans’ ability to capture complementarities while working collaboratively with AI is critically constrained by our limited ability to assess what we know, i.e., metaknowledge. However, extant research has largely overlooked a critical difference between human and AI: Human behavior is shaped by personality. I explore how differences arising from personality traits impact metaknowledge and delegation behavior towards AI. Using an image classification experiment, I find that higher levels of conscientiousness improve, while higher levels extraversion harm humans’ ability to work collaboratively with AI. Differences in metaknowledge help to explain this relationship. These findings motivate further research on personality in human-AI collaboration and the design of collaborative systems which foster metaknowledge and improved performance.

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09-HCI

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Dec 11th, 12:00 AM

Exploring Personality-based Heterogeneity in Metaknowledge and Human-AI Collaboration

While artificial intelligence (AI) has great potential to transform how we work, it’s clear that in many contexts, humans and AI will work side by side. According to recent research, humans’ ability to capture complementarities while working collaboratively with AI is critically constrained by our limited ability to assess what we know, i.e., metaknowledge. However, extant research has largely overlooked a critical difference between human and AI: Human behavior is shaped by personality. I explore how differences arising from personality traits impact metaknowledge and delegation behavior towards AI. Using an image classification experiment, I find that higher levels of conscientiousness improve, while higher levels extraversion harm humans’ ability to work collaboratively with AI. Differences in metaknowledge help to explain this relationship. These findings motivate further research on personality in human-AI collaboration and the design of collaborative systems which foster metaknowledge and improved performance.

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