Fahse, Tobias and Schmitt, Anuschka 
ORCID: 0000-0003-1101-6529
(2023)
Exploring the synergies in human-AI hybrids: a longitudinal analysis in sales forecasting.
In:
29th Annual Americas Conference on Information Systems, AMCIS 2023.
29th Annual Americas Conference on Information Systems, AMCIS 2023.
AIS.
ISBN 9781713893592
Abstract
Despite the promised potential of artificial intelligence (AI), insights into real-life human-AI hybrids and their dynamics remain obscure. Based on digital trace data of over 1.4 million forecasting decisions over a 69-month period, we study the implications of an AI sales forecasting system’s introduction in a bakery enterprise on decision-makers’ overriding of the AI system and resulting hybrid performance. Decision-makers quickly started to rely on AI forecasts, leading to lower forecast errors. Overall, human intervention deteriorated forecasting performance as overriding resulted in greater forecast error. The results confirm the notion that AI systems outperform humans in forecasting tasks. However, the results also indicate previously neglected, domain-specific implications: As the AI system aimed to reduce forecast error and thus overproduction, forecasting numbers decreased over time, and thereby also sales. We conclude that minimal forecast errors do not inevitably yield optimal business outcomes when detrimental human factors in decision-making are ignored.
| Item Type: | Book Section |
|---|---|
| Additional Information: | © 2023 AMCIS |
| Divisions: | LSE |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Date Deposited: | 16 Oct 2024 16:00 |
| Last Modified: | 20 Dec 2024 00:20 |
| URI: | http://eprints.lse.ac.uk/id/eprint/125788 |
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