AI Knowledge: Improving AI Delegation through Human Enablement

被引:25
作者
Pinski, Marc [1 ]
Adam, Martin [1 ]
Benlian, Alexander [1 ]
机构
[1] Tech Univ Darmstadt, Informat Syst & E Serv, Darmstadt, Germany
来源
PROCEEDINGS OF THE 2023 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2023 | 2023年
关键词
AI delegation; AI literacy; AI education; AI skill; Cognitive appraisal theory; INFORMATION-TECHNOLOGY; ARTIFICIAL-INTELLIGENCE; BUSINESS MANAGERS; PERSPECTIVES; COMPETENCE; MODEL;
D O I
10.1145/3544548.3580794
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:17
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