AI Knowledge: Improving AI Delegation through Human Enablement

要旨

When collaborating with artificial intelligence (AI), humans can often delegate tasks to leverage complementary AI competencies. However, humans often delegate inefficiently. Enabling humans with knowledge about AI can potentially improve inefficient AI delegation. We conducted a between-subjects experiment (two groups, n = 111) to examine how enabling humans with AI knowledge can improve AI delegation in human-AI collaboration. We find that AI knowledge-enabled humans align their delegation decisions more closely with their assessment of how suitable a task is for humans or AI (i.e., task appraisal). We show that delegation decisions closely aligned with task appraisal increase task performance. However, we also find that AI knowledge lowers future intentions to use AI, suggesting that AI knowledge is not strictly positive for human-AI collaboration. Our study contributes to HCI design guidelines with a new perspective on AI features, educating humans regarding general AI functioning and their own (human) performance and biases.

著者
Marc Pinski
Technical University of Darmstadt, Darmstadt, Germany
Martin Adam
Technical University of Darmstadt, Darmstadt, Germany
Alexander Benlian
Technical University of Darmstadt, Darmstadt, Germany
論文URL

https://doi.org/10.1145/3544548.3580794

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: AI, Cognition & Bias

Hall C
6 件の発表
2023-04-25 20:10:00
2023-04-25 21:35:00