Universität zu Köln

Lehmann, Cedric A., Haubitz, Christiane ORCID: 0000-0002-7126-0606, Fügener, Andreas ORCID: 0000-0002-4580-7444 and Thonemann, Ulrich ORCID: 0000-0002-3507-9498 (2022). The risk of algorithm transparency: How algorithm complexity drives the effects on the use of advice. Prod. Oper. Manag., 31 (9). S. 3419 - 3435. HOBOKEN: WILEY. ISSN 1937-5956

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Abstract

Although algorithmic decision support is omnipresent in many managerial tasks, a lack of algorithm transparency is often stated as a barrier to successful human-machine collaboration. In this paper, we analyze the effects of algorithm transparency on the use of advice from algorithms with different degrees of complexity. We conduct a set of laboratory experiments in which participants receive identical advice from algorithms with different levels of transparency and complexity. Our results indicate that not the algorithm itself, but the individually perceived appropriateness of algorithmic complexity moderates the effects of transparency on the use of advice. We summarize this effect as a plateau curve: While perceiving an algorithm as too simple severely harms the use of its advice, the perception of an algorithm as being too complex has no significant effect. Our insights suggest that managers do not have to be concerned about revealing algorithms that are perceived to be appropriately complex or too complex to decision-makers, even if the decision-makers do not fully comprehend them. However, providing transparency on algorithms that are perceived to be simpler than appropriate could disappoint people's expectations and thereby reduce the use of their advice.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Lehmann, Cedric A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Haubitz, Christiane UNSPECIFIED orcid.org/0000-0002-7126-0606 UNSPECIFIED Fügener, Andreas UNSPECIFIED orcid.org/0000-0002-4580-7444 UNSPECIFIED Thonemann, Ulrich UNSPECIFIED orcid.org/0000-0002-3507-9498 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-660526
DOI:	10.1111/poms.13770
Journal or Publication Title:	Prod. Oper. Manag.
Volume:	31
Number:	9
Page Range:	S. 3419 - 3435
Date:	2022
Publisher:	WILEY
Place of Publication:	HOBOKEN
ISSN:	1937-5956
Language:	English
Faculty:	Faculty of Management, Economy and Social Sciences
Divisions:	Center of Excellence C-SEB
Subjects:	Economics
Uncontrolled Keywords:	Keywords Language IMPROVING JUDGMENT; FORECASTS; AUTOMATION; INFORMATION; AVERSION; TRUST Multiple languages Engineering, Manufacturing; Operations Research & Management Science Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/66052