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Whose Advice Counts More – Man or Machine? An Experimental Investigation of AI-based Advice Utilization

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Title:Whose Advice Counts More – Man or Machine? An Experimental Investigation of AI-based Advice Utilization
Authors:Mesbah, Neda
Tauchert, Christoph
Buxmann, Peter
Keywords:Artificial Intelligence-based Assistants
artificial intelligence
advice taking
judge-advisor system
distance effects
task-technology fit
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Date Issued:05 Jan 2021
Abstract:Due to advances in Artificial Intelligence (AI), it is possible to provide advisory services without human advisors. Derived from judge-advisor system literature, we examined differences in the advice utilization depending on whether it is given by an AI-based or human advisor and the similarity of the advice and their own estimation. Drawing on task-technology fit we investigated the relationship between task, advisor and advice utilization. In study A we measured the actual advice utilization within a guessing game and in study B we measured the perceived task-advisor fit for this game. The findings show that compared to human advisors, judges utilize advices of AI-based advisors more when the advice is similar to their own estimation. When the advice is very different to their estimation, the advices are used equally. Concluding, we investigated AI-based advice utilization and presented insights for professionals providing AI-based advisory services.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/71113
ISBN:978-0-9981331-4-0
DOI:10.24251/HICSS.2021.496
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Artificial Intelligence-based Assistants


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