The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context

Bibliographic Details
Main Author: Fortuin, Eva Kim
Publication Date: 2022
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.14/45875
Summary: With the intention of overcoming human decision making biases, organizations are increasingly using AI as decision support. However, to unlock the full potential of AI-based advice to improve decision making, users must be willing to rely on it in the first place. To better understand people’s readiness to accept advice from AI, two experimental studies were conducted in the scope of this research. Study 1 examined whether people rely more on advice coming from AI or a human. People showed algorithm appreciation in both tasks – the performance evaluation of an employee and the closing price prediction of a stock. The effect was fully mediated by people’s trust in the source and varied across different levels of confidence in one’s own decision. Study 2 examined whether people also choose AI advice over human advice when presented with both options and whether they choose equally for themselves and for others. In this setting, algorithm appreciation persisted only for the stock price prediction task, irrespectively of who the decision was made for. Furthermore, several influencing factors were identified that point to domains where AI is most likely to be accepted and ways in which its benefits can be maximized. The results from these studies have clear implications for organizations that turn to Big Data and AI-generated advice to improve decision making, suggesting that AI might be a good addition to their daily operations.
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spelling The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business contextO potencial da inteligência artificial (IA) para melhorar a tomada de decisões : investigar a confiança no aconselhamento sobre IA num contexto empresarialArtificial intelligenceAI adviceStrategic decision makingReliance on adviceJAS paradigmTrustSelf-confidenceInteligência artificialAconselhamento artificialTomada de decisão estratégicaConfiança de aconselhamentoParadigma JASConfiançaAutoconfiançaWith the intention of overcoming human decision making biases, organizations are increasingly using AI as decision support. However, to unlock the full potential of AI-based advice to improve decision making, users must be willing to rely on it in the first place. To better understand people’s readiness to accept advice from AI, two experimental studies were conducted in the scope of this research. Study 1 examined whether people rely more on advice coming from AI or a human. People showed algorithm appreciation in both tasks – the performance evaluation of an employee and the closing price prediction of a stock. The effect was fully mediated by people’s trust in the source and varied across different levels of confidence in one’s own decision. Study 2 examined whether people also choose AI advice over human advice when presented with both options and whether they choose equally for themselves and for others. In this setting, algorithm appreciation persisted only for the stock price prediction task, irrespectively of who the decision was made for. Furthermore, several influencing factors were identified that point to domains where AI is most likely to be accepted and ways in which its benefits can be maximized. The results from these studies have clear implications for organizations that turn to Big Data and AI-generated advice to improve decision making, suggesting that AI might be a good addition to their daily operations.Almeida, Filipa deVeritatiFortuin, Eva Kim2023-01-272022-012025-07-25T00:00:00Z2023-01-27T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.14/45875urn:tid:203252918enginfo:eu-repo/semantics/embargoedAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-13T14:04:10Zoai:repositorio.ucp.pt:10400.14/45875Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T02:01:53.126557Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context
O potencial da inteligência artificial (IA) para melhorar a tomada de decisões : investigar a confiança no aconselhamento sobre IA num contexto empresarial
title The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context
spellingShingle The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context
Fortuin, Eva Kim
Artificial intelligence
AI advice
Strategic decision making
Reliance on advice
JAS paradigm
Trust
Self-confidence
Inteligência artificial
Aconselhamento artificial
Tomada de decisão estratégica
Confiança de aconselhamento
Paradigma JAS
Confiança
Autoconfiança
title_short The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context
title_full The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context
title_fullStr The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context
title_full_unstemmed The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context
title_sort The potential of artificial intelligence (AI) to improve decision making : investigating the reliance on AI advice in a business context
author Fortuin, Eva Kim
author_facet Fortuin, Eva Kim
author_role author
dc.contributor.none.fl_str_mv Almeida, Filipa de
Veritati
dc.contributor.author.fl_str_mv Fortuin, Eva Kim
dc.subject.por.fl_str_mv Artificial intelligence
AI advice
Strategic decision making
Reliance on advice
JAS paradigm
Trust
Self-confidence
Inteligência artificial
Aconselhamento artificial
Tomada de decisão estratégica
Confiança de aconselhamento
Paradigma JAS
Confiança
Autoconfiança
topic Artificial intelligence
AI advice
Strategic decision making
Reliance on advice
JAS paradigm
Trust
Self-confidence
Inteligência artificial
Aconselhamento artificial
Tomada de decisão estratégica
Confiança de aconselhamento
Paradigma JAS
Confiança
Autoconfiança
description With the intention of overcoming human decision making biases, organizations are increasingly using AI as decision support. However, to unlock the full potential of AI-based advice to improve decision making, users must be willing to rely on it in the first place. To better understand people’s readiness to accept advice from AI, two experimental studies were conducted in the scope of this research. Study 1 examined whether people rely more on advice coming from AI or a human. People showed algorithm appreciation in both tasks – the performance evaluation of an employee and the closing price prediction of a stock. The effect was fully mediated by people’s trust in the source and varied across different levels of confidence in one’s own decision. Study 2 examined whether people also choose AI advice over human advice when presented with both options and whether they choose equally for themselves and for others. In this setting, algorithm appreciation persisted only for the stock price prediction task, irrespectively of who the decision was made for. Furthermore, several influencing factors were identified that point to domains where AI is most likely to be accepted and ways in which its benefits can be maximized. The results from these studies have clear implications for organizations that turn to Big Data and AI-generated advice to improve decision making, suggesting that AI might be a good addition to their daily operations.
publishDate 2022
dc.date.none.fl_str_mv 2022-01
2023-01-27
2023-01-27T00:00:00Z
2025-07-25T00:00:00Z
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