Universität zu Köln

Fügener, Andreas ORCID: 0000-0002-4580-7444, Grahl, Jorn, Gupta, Alok ORCID: 0000-0002-2097-1643 and Ketter, Wolfgang ORCID: 0000-0001-9008-142X (2021). Cognitive Challenges in Human-Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation. Inf. Syst. Res., 33 (2). CATONSVILLE: INFORMS. ISSN 1526-5536

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Abstract

We study how humans make decisions when they collaborate with an artificial intelligence (AI) in a setting where humans and the AI perform classification tasks. Our experimental results suggest that humans and AI who work together can outperform the AI that outperforms humans when it works on its own. However, the combined performance improves only when the AI delegates work to humans but not when humans delegate work to the AI. The AI's delegation performance improved even when it delegated to low-performing subjects; by contrast, humans did not delegate well and did not benefit from delegation to the AI. This bad delegation performance cannot be explained with some kind of algorithm aversion. On the contrary, subjects acted rationally in an internally consistent manner by trying to follow a proven delegation strategy and appeared to appreciate the AI support. However, human performance suffered as a result of a lack of metaknowledge-that is, humans were not able to assess their own capabilities correctly, which in turn led to poor delegation decisions. Lacking metaknowledge, in contrast to reluctance to use AI, is an unconscious trait. It fundamentally limits how well human decision makers can collaborate with AI and other algorithms. The results have implications for the future of work, the design of human-AI collaborative environments, and education in the digital age.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Fügener, Andreas UNSPECIFIED orcid.org/0000-0002-4580-7444 UNSPECIFIED Grahl, Jorn UNSPECIFIED UNSPECIFIED UNSPECIFIED Gupta, Alok UNSPECIFIED orcid.org/0000-0002-2097-1643 UNSPECIFIED Ketter, Wolfgang UNSPECIFIED orcid.org/0000-0001-9008-142X UNSPECIFIED
URN:	urn:nbn:de:hbz:38-582261
DOI:	10.1287/isre.2021.1079
Journal or Publication Title:	Inf. Syst. Res.
Volume:	33
Number:	2
Date:	2021
Publisher:	INFORMS
Place of Publication:	CATONSVILLE
ISSN:	1526-5536
Language:	English
Faculty:	Faculty of Management, Economy and Social Sciences
Divisions:	Center of Excellence C-SEB Faculty of Management, Economics and Social Sciences > Business Administration > Information Systems > Chair for Information Systems and Systems Development
Subjects:	Economics
Uncontrolled Keywords:	Keywords Language IN-THE-LOOP; NEURAL-NETWORKS; DEEP; OVERCONFIDENCE; ALGORITHMS Multiple languages Information Science & Library Science; Management Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/58226