Akzeptanz einer Künstlichen Intelligenz als organisatorische Führungskraft: Eine Fragebogenstudie

Deborah Petrat; Ilker Yenice; Lukas Bier; Ilka Subtil

doi:10.14512/tatup.31.2.64

Authors

Deborah Petrat Institute for Ergonomics and Human Factors, TU Darmstadt (DE) https://orcid.org/0000-0003-4988-3177 deborah.petrat@tu-darmstadt.de
Ilker Yenice Institute for Ergonomics and Human Factors, TU Darmstadt (DE) https://orcid.org/0000-0002-8234-2455 ilker.yenice@stud.tu-darmstadt.de
Lukas Bier Lumics GmbH & Co. KG (DE) lukas.bier@lumics-consulting.de
Ilka Subtil Institute for Ergonomics and Human Factors, TU Darmstadt (DE) ilka.subtil@tu-darmstadt.de

DOI:

https://doi.org/10.14512/tatup.31.2.64

Keywords:

artificial intelligence, leadership, future of work, acceptance

Abstract

In times of digital transformation and in an increasingly fast-paced corporate landscape, there is an increasing debate among company executives as to whether and how artificial intelligence (AI) can take over management tasks or even replace managers as such. This article provides an initial contribution to this discussion by examining the potential user base’s acceptance levels of and expectations for the adoption of AI technology in organizational leadership roles. For this purpose, employees and managers (N = 74) were surveyed in an online questionnaire that presented three hypothetical scenarios in which AI performs certain managerial tasks, featuring different levels of interaction with potential users. An ANOVA analysis showed that the highest acceptance levels among the scenarios were achieved for AI managers that operate as (digital) cognitive assistants, thus giving support to executives in team supervision and providing a data-driven feedback culture.

References

Adell, Emeli (2010): Acceptance of driver support systems. In: Proceedings of the European conference on human centred design for intelligent transport systems. Vol. 2. Berlin: Humanist VCE, pp. 475–486. Available online at https://www.humanist-vce.eu/fileadmin/contributeurs/humanist/Berlin2010/6_Adell.pdf, last accessed on 23. 05. 2022.

Allen, James; James Root; Andrew Schwedel (2017): The firm of the future. In: Bain & Company. Available online at https://www.bain.com/insights/firm-of-the-future, last accessed on 23. 05. 2022.

Baharum, Aslina; Amirul, Sharifah; Yusop, Nurhafizah; Halamy, Suhaida; Fabeil, Noor; Ramli, Ratna (2017): Development of questionnaire to measure user acceptance towards user interface design. In: Halima Badioze et al. (eds.): Advances in visual informatics. Cham: Springer International Pub-lihsing, pp. 531–543. DOI: https://doi.org/10.1007/978-3-319-70010-6_49

BBC – British Broadcasting Corporation (2014): Algorithm appointed board director. In: BBC News. Available online at https://www.bbc.com/news/technology-27426942, last accessed on 23. 05. 2022.

Bitkom e. v. (2019): Künstliche Intelligenz soll dem Chef helfen – oder ihn ersetzen. In: Bitkom.org. Available online at https://www.bitkom.org/Presse/Presseinformation/Kuenstliche-Intelligenz-soll-dem-Chef-helfen-oder-ihn-ersetzen, last accessed on 23. 05. 2022.

Buitendach, Johanna; Rothmann, Sebastian (2009): The validation of the Minnesota Job Satisfaction Questionnaire in selected organisations in South Africa. In: SA Journal of Human Resource Management 7 (1), pp. 1–8. DOI: https://doi.org/10.4102/sajhrm.v7i1.183

Burridge, Nicky (2017): Artificial intelligence gets a seat in the boardroom. Hong Kong venture capitalist sees AI running Asian companies within 5 years. In: Nikkei Asia. Available online at https://asia.nikkei.com/Business/Artificial-intelligence-gets-a-seat-in-the-boardroom, last accessed on 23. 05. 2022.

Buxmann, Peter; Schmidt, Holger (2019): Künstliche Intelligenz. Mit Algorithmen zum wirtschaftlichen Erfolg. Berlin: Springer Gabler. DOI: https://doi.org/10.1007/978-3-662-57568-0

Chau, Patrick (1996): An empirical investigation on factors affecting the acceptance of CASE by systems developers. In: Information & Management 30 (6), pp. 269–280. DOI: https://doi.org/10.1016/S0378-7206(96)01074-9

Chismar, William; Wiley-Patton, Sonja (2003): Does the extended technology acceptance model apply to physicians. In: Proceedings of the 36th Annual Hawaii International Conference on System Sciences, 8 pp. Big Island, HI: IEEE. DOI: https://doi.org/10.1109/HICSS.2003.1174354

Costello, Katie (2019): Gartner Survey shows 37 percent of organizations have implemented AI in some form. Available online at https://www.gartner.com/en/newsroom/press-releases/2019-01-21-gartner-survey-shows-37-percent-of-organizations-have, last accessed on 23. 05. 2022.

Crutzen, Rik; Peters, Gjalt-Jorn Ygram (2017): Scale quality. Alpha is an inadequate estimate and factor-analytic evidence is needed first of all. In: Health Psychology Review 11 (3), pp. 242–247. DOI: https://doi.org/10.1080/17437199.2015.1124240

Davis, Fred (1985): A technology acceptance model for empirically testing new end-user information systems. PhD thesis. Boston, MA: MIT. Available online at https://core.ac.uk/display/4387241, last accessed on 23. 05. 2022.

Fountaine, Tim; McCarthy, Brian; Saleh, Tamim (2019): Building the AI‑powered organization. In: Harvard Business Review July-August, pp. 62–73. Available online at https://hbr.org/2019/07/building-the-ai-powered-organization, last accessed on 23. 05. 2022.

Hamilton, Isobel (2018): Amazon built an AI tool to hire people but had to shut it down because it was discriminating against women. In: Insider. Availa-ble online at https://www.businessinsider.com/amazon-built-ai-to-hire-people-discriminated-against-women-2018-10, last accessed on 23. 05. 2022.

IBM – IBM Cloud Education (2020): Strong AI. Im: IBM Cloud. Available online at https://www.ibm.com/cloud/learn/strong-ai, last accessed on 23. 05. 2022.

Kessler, Sarah (2017): Robots are replacing managers, too. In: Quartz. Available online at https://qz.com/1039981/robots-are-replacing-managers-too, last accessed on 23. 05. 2022.

Microsoft (2019): Microsoft-Studie zu KI & Leadership. Künstliche Intelligenz verändert Führung in Unternehmen. Available online at https://news.microsoft.com/de-de/microsoft-studie-ki-leadership, last accessed on 23. 05. 2022.

King William; He, Jun (2006): A meta-analysis of the technology acceptance model. In: Information & Management 43 (6), pp. 740–755. DOI: https://doi.org/10.1016/j.im.2006.05.003

Kolbjørnsrud, Vegard; Amico, Richard; Thomas, Robert (2016): Leadership development. How Artificial Intelligence will redefine management. In: Harvard Business Review. Available online at https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management, last accessed on 23. 05. 2022.

Mathieson, Kieran (1991): Predicting user intentions. Comparing the technology acceptance model with the theory of planned behavior. In: Information Systems Research 2 (3), pp. 173–191. DOI: https://doi.org/10.1287/isre.2.3.173

McAfee, Andrew; Brynjolfsson, Erik (2012): Big Data. The management revolution. In: Harvard Business Review 90 (10), pp. 60–68.

Manyika, James et al. (2017): A future that works. Automation, employment, and productivity. Executive summery. s.l.: McKinsey: McKinsey Global Institute. Available online at https://www.mckinsey.com/~/media/mckinsey/featured%20insights/Digital%20Disruption/Harnessing%20automation%20for%20a%20future%20that%20works/MGI-A-future-that-works-Executive-summary.ashx, last accessed on 23. 05. 2022.

Moulds, Josephine (2018): Robot managers. The future of work or a step too far? In: The Guardian. Available online at https://www.theguardian.com/business-to-business/2018/apr/06/robot-managers-how-a-firm-automated, last accessed on 23. 05. 2022.

Odgers Berndtson (2019): Neunte jährliche Befragung des Odgers Berndtson Executive Panels in Deutschland, Österreich und der Schweiz. s.l.: s.n. Available online at https://www.odgersberndtson.com/media/8755/odgers-berndtson-manager-barometer-2019-2020.pdf, last accessed on 23. 05. 2022.

Rittershaus, Axel (2020): Künstliche Intelligenz ist Führungssache. In: Axel Rittershaus (ed.): Führungspraxis für Ingenieure und IT‑Experten. Wiesba-den: Springer Fachmedien, pp. 179–188. DOI: https://doi.org/10.1007/978-3-658-26600-4_11

Sahota, Neil; Ashley, Michael (2019): When robots replace human managers. Introducing the quantifiable workplace. In: IEEE Engineering Manage-ment Review 47 (3), pp. 21–23. DOI: https://doi.org/10.1109/EMR.2019.2931654

Venkatesh, Viswanath; Morris, Michael; Davis, Gordon; Davis Fred (2003): User acceptance of information technology. Toward a unified view. In: MIS Quarterly 27 (3), p. 425. DOI: https://doi.org/10.2307/30036540

Vorhies, William (2016): Artificial General Intelligence. The holy grail of AI. In: Data Science Central. Available online at https://www.datasciencecentral.com/artificial-general-intelligence-the-holy-grail-of-ai, last accessed on 23. 05. 2022.

Weinkauf, Katharina; Hoegl, Martin (2002): Team leadership activities in different project phases. In: Team performance management: An Interna-tional Journal 8 (7/8), pp. 171–182. DOI: https://doi.org/10.1108/13527590210452095

Wile, Rob (2014): A venture capital firm just named an algorithm to its board of directors. Here’s what it actually does. In: Insider. Available online at https://www.businessinsider.com/vital-named-to-board-2014-5, last accessed on 23. 05. 2022.