TY - GEN
T1 - Investigating Trust in Expert System Advice for Business Ethics Audits
AU - Kirchebner, Tobias
AU - Schlögl, Stephan
AU - Bass, Erin
AU - Dilger, Thomas
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - The last decade has seen an uptake of Artificial Intelligence technology in many fields. In particular, we have witnessed the proliferation of so-called Expert Systems (i.e., algorithm-based recommender engines), which are increasingly used to support decision making processes. To this end, trust in technology plays a significant role, as without such people are unwilling to rely on this type of tool support. The goal of the research presented in this paper was thus to investigate said trust in ‘expert system advice’ when received in the context of a business ethics audit. We report on the results of a scenario-focused survey aimed at understanding people’s preference for an advice giver, and whether such is connected to their general trust behavior, as well as their affinity for technology. Results show that participants’ willingness to depend on machine advice is approximately similar to their willingness to depend on human advice, the trust they put into the artificial advice giver, however, increases with their affinity for technology.
AB - The last decade has seen an uptake of Artificial Intelligence technology in many fields. In particular, we have witnessed the proliferation of so-called Expert Systems (i.e., algorithm-based recommender engines), which are increasingly used to support decision making processes. To this end, trust in technology plays a significant role, as without such people are unwilling to rely on this type of tool support. The goal of the research presented in this paper was thus to investigate said trust in ‘expert system advice’ when received in the context of a business ethics audit. We report on the results of a scenario-focused survey aimed at understanding people’s preference for an advice giver, and whether such is connected to their general trust behavior, as well as their affinity for technology. Results show that participants’ willingness to depend on machine advice is approximately similar to their willingness to depend on human advice, the trust they put into the artificial advice giver, however, increases with their affinity for technology.
KW - Artificial intelligence
KW - Business ethics audits
KW - Decision-making
KW - Expert systems
KW - Trust
UR - http://www.scopus.com/inward/record.url?scp=85113523885&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113523885&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-81635-3_26
DO - 10.1007/978-3-030-81635-3_26
M3 - Conference contribution
AN - SCOPUS:85113523885
SN - 9783030816346
T3 - Communications in Computer and Information Science
SP - 316
EP - 328
BT - Knowledge Management in Organizations - 15th International Conference, KMO 2021, Proceedings
A2 - Uden, Lorna
A2 - Ting, I-Hsien
A2 - Wang, Kai
PB - Springer Science and Business Media Deutschland GmbH
T2 - 15th International Conference on Knowledge Management in Organizations, KMO 2021
Y2 - 20 July 2021 through 22 July 2021
ER -