Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment
Algorithms are involved in decisions ranging from trivial to significant, but people often express distrust toward them. Research suggests that educational efforts to explain how algorithms work may help mitigate this distrust. In a study of 1,921 participants from 20 countries, we examined differen...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Artificial Intelligence |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2024.1465605/full |
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| author | Fernando Marmolejo-Ramos Rebecca Marrone Malgorzata Korolkiewicz Florence Gabriel George Siemens Srecko Joksimovic Yuki Yamada Yuki Mori Talal Rahwan Maria Sahakyan Belona Sonna Assylbek Meirmanov Aidos Bolatov Bidisha Som Izuchukwu Ndukaihe Nwadiogo C. Arinze Josef Kundrát Lenka Skanderová Van-Giang Ngo Giang Nguyen Michelle Lacia Chun-Chia Kung Meiselina Irmayanti Meiselina Irmayanti Abdul Muktadir Fransiska Timoria Samosir Marco Tullio Liuzza Roberto Giorgini Omid Khatin-Zadeh Hassan Banaruee Asil Ali Özdoğru Kris Ariyabuddhiphongs Wachirawit Rakchai Natalia Trujillo Stella Maris Valencia Armina Janyan Armina Janyan Kiril Kostov Pedro R. Montoro Jose Hinojosa Jose Hinojosa Kelsey Medeiros Thomas E. Hunt Julian Posada Raquel Meister Ko Freitag Julian Tejada |
| author_facet | Fernando Marmolejo-Ramos Rebecca Marrone Malgorzata Korolkiewicz Florence Gabriel George Siemens Srecko Joksimovic Yuki Yamada Yuki Mori Talal Rahwan Maria Sahakyan Belona Sonna Assylbek Meirmanov Aidos Bolatov Bidisha Som Izuchukwu Ndukaihe Nwadiogo C. Arinze Josef Kundrát Lenka Skanderová Van-Giang Ngo Giang Nguyen Michelle Lacia Chun-Chia Kung Meiselina Irmayanti Meiselina Irmayanti Abdul Muktadir Fransiska Timoria Samosir Marco Tullio Liuzza Roberto Giorgini Omid Khatin-Zadeh Hassan Banaruee Asil Ali Özdoğru Kris Ariyabuddhiphongs Wachirawit Rakchai Natalia Trujillo Stella Maris Valencia Armina Janyan Armina Janyan Kiril Kostov Pedro R. Montoro Jose Hinojosa Jose Hinojosa Kelsey Medeiros Thomas E. Hunt Julian Posada Raquel Meister Ko Freitag Julian Tejada |
| author_sort | Fernando Marmolejo-Ramos |
| collection | DOAJ |
| description | Algorithms are involved in decisions ranging from trivial to significant, but people often express distrust toward them. Research suggests that educational efforts to explain how algorithms work may help mitigate this distrust. In a study of 1,921 participants from 20 countries, we examined differences in algorithmic trust for low-stakes and high-stakes decisions. Our results suggest that statistical literacy is negatively associated with trust in algorithms for high-stakes situations, while it is positively associated with trust in low-stakes scenarios with high algorithm familiarity. However, explainability did not appear to influence trust in algorithms. We conclude that having statistical literacy enables individuals to critically evaluate the decisions made by algorithms, data and AI, and consider them alongside other factors before making significant life decisions. This ensures that individuals are not solely relying on algorithms that may not fully capture the complexity and nuances of human behavior and decision-making. Therefore, policymakers should consider promoting statistical/AI literacy to address some of the complexities associated with trust in algorithms. This work paves the way for further research, including the triangulation of data with direct observations of user interactions with algorithms or physiological measures to assess trust more accurately. |
| format | Article |
| id | doaj-art-02e1a39e92a04b6a836cffd3463c716f |
| institution | Kabale University |
| issn | 2624-8212 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj-art-02e1a39e92a04b6a836cffd3463c716f2025-02-04T06:31:41ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122025-02-01710.3389/frai.2024.14656051465605Factors influencing trust in algorithmic decision-making: an indirect scenario-based experimentFernando Marmolejo-Ramos0Rebecca Marrone1Malgorzata Korolkiewicz2Florence Gabriel3George Siemens4Srecko Joksimovic5Yuki Yamada6Yuki Mori7Talal Rahwan8Maria Sahakyan9Belona Sonna10Assylbek Meirmanov11Aidos Bolatov12Bidisha Som13Izuchukwu Ndukaihe14Nwadiogo C. Arinze15Josef Kundrát16Lenka Skanderová17Van-Giang Ngo18Giang Nguyen19Michelle Lacia20Chun-Chia Kung21Meiselina Irmayanti22Meiselina Irmayanti23Abdul Muktadir24Fransiska Timoria Samosir25Marco Tullio Liuzza26Roberto Giorgini27Omid Khatin-Zadeh28Hassan Banaruee29Asil Ali Özdoğru30Kris Ariyabuddhiphongs31Wachirawit Rakchai32Natalia Trujillo33Stella Maris Valencia34Armina Janyan35Armina Janyan36Kiril Kostov37Pedro R. Montoro38Jose Hinojosa39Jose Hinojosa40Kelsey Medeiros41Thomas E. Hunt42Julian Posada43Raquel Meister Ko Freitag44Julian Tejada45College of Education, Psychology, and Social Work, Flinders University, Adelaide, SA, AustraliaCentre for Change and Complexity in Learning, University of South Australia, Adelaide, SA, AustraliaCentre for Change and Complexity in Learning, University of South Australia, Adelaide, SA, AustraliaCentre for Change and Complexity in Learning, University of South Australia, Adelaide, SA, AustraliaCentre for Change and Complexity in Learning, University of South Australia, Adelaide, SA, AustraliaCentre for Change and Complexity in Learning, University of South Australia, Adelaide, SA, AustraliaFaculty of Arts and Science, Kyushu University, Fukuoka, JapanGraduate School of Human-Environment Studies, Kyushu University, Fukuoka, JapanComputer Science, Science Division, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesComputer Science, Science Division, New York University Abu Dhabi, Abu Dhabi, United Arab EmiratesAfrican Masters of Machine Intelligence (AMMI), African Institute for Mathematical Sciences (AIMS), Limbe, CameroonHigher Schools, Pedagogical Institute, Astana International University, Astana, KazakhstanDepartment of General and Biological Chemistry, Astana Medical University, Astana, KazakhstanDepartment of Humanities and Social Science, Indian Institute of Technology Guwahati, Guwahati, Assam, India0Department of Psychology, Alex Ekwueme Federal University Ndufu-Alike, Ebonyi, Nigeria0Department of Psychology, Alex Ekwueme Federal University Ndufu-Alike, Ebonyi, Nigeria1Department of Psychology, Faculty of Arts, University of Ostrava, Ostrava, Czechia2Department of Computer Science, Faculty of Electrical Engineering and Computer Science, Technical University of Ostrava, Ostrava, Czechia3Department of English, Hanoi University, Hanoi, Vietnam3Department of English, Hanoi University, Hanoi, Vietnam4College of Arts and Sciences, Notre Dame University, Cotabato, Philippines5Department of Psychology, National Cheng Kung University, Tainan, Taiwan6Department of Communication, University of Bengkulu, Bengkulu, Indonesia7Principles and Implication of Mind Sciences, Psychology Program, National Cheng Kung University, Tainan, Taiwan8Postgraduate Program of Basic Education, University of Bengkulu, Bengkulu, Indonesia9Library and Information Science, University of Bengkulu, Bengkulu, Indonesia0Department of Developmental Psychology and Socialization, Università di Padova, Padua, Italy1Department of Medical and Surgical Sciences, “Magna Graecia” University of Catanzaro, Catanzaro, Italy2School of Foreign Languages, University of Electronic Science and Technology of China, Chengdu, China3Department of Educational Psychology, University of Education of Weingarten, Weingarten, Germany4Department of Psychology, Marmara University, Istanbul, Türkiye5Faculty of Psychology, Chulalongkorn University, Bangkok, Thailand5Faculty of Psychology, Chulalongkorn University, Bangkok, Thailand6Faculty of Public Health, University of Antioquia, Medellín, Colombia6Faculty of Public Health, University of Antioquia, Medellín, Colombia7Department of Cognitive Science and Psychology, New Bulgarian University, Sofia, Bulgaria8Research Centre for Cognitive Science, New Bulgarian University, Sofia, Bulgaria7Department of Cognitive Science and Psychology, New Bulgarian University, Sofia, Bulgaria9Departamento de Psicología Básica 1, Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain0Instituto Pluridisciplinar, Universidad Complutense de Madrid, Madrid, Spain1Centro de Investigación Nebrija en Cognición (CINC), Universidad Nebrija, Madrid, Spain2Department of Management, University of Nebraska Omaha, Omaha, NE, United States3School of Psychology, University of Derby, Derby, United Kingdom4Department of American Studies, Yale University, New Haven, CT, United States5Departamento de Psicologia, Universidade Federal de Sergipe, Saõ Cristóvão, Brazil5Departamento de Psicologia, Universidade Federal de Sergipe, Saõ Cristóvão, BrazilAlgorithms are involved in decisions ranging from trivial to significant, but people often express distrust toward them. Research suggests that educational efforts to explain how algorithms work may help mitigate this distrust. In a study of 1,921 participants from 20 countries, we examined differences in algorithmic trust for low-stakes and high-stakes decisions. Our results suggest that statistical literacy is negatively associated with trust in algorithms for high-stakes situations, while it is positively associated with trust in low-stakes scenarios with high algorithm familiarity. However, explainability did not appear to influence trust in algorithms. We conclude that having statistical literacy enables individuals to critically evaluate the decisions made by algorithms, data and AI, and consider them alongside other factors before making significant life decisions. This ensures that individuals are not solely relying on algorithms that may not fully capture the complexity and nuances of human behavior and decision-making. Therefore, policymakers should consider promoting statistical/AI literacy to address some of the complexities associated with trust in algorithms. This work paves the way for further research, including the triangulation of data with direct observations of user interactions with algorithms or physiological measures to assess trust more accurately.https://www.frontiersin.org/articles/10.3389/frai.2024.1465605/fullalgorithmsdataAItruststatistical literacyexplainability |
| spellingShingle | Fernando Marmolejo-Ramos Rebecca Marrone Malgorzata Korolkiewicz Florence Gabriel George Siemens Srecko Joksimovic Yuki Yamada Yuki Mori Talal Rahwan Maria Sahakyan Belona Sonna Assylbek Meirmanov Aidos Bolatov Bidisha Som Izuchukwu Ndukaihe Nwadiogo C. Arinze Josef Kundrát Lenka Skanderová Van-Giang Ngo Giang Nguyen Michelle Lacia Chun-Chia Kung Meiselina Irmayanti Meiselina Irmayanti Abdul Muktadir Fransiska Timoria Samosir Marco Tullio Liuzza Roberto Giorgini Omid Khatin-Zadeh Hassan Banaruee Asil Ali Özdoğru Kris Ariyabuddhiphongs Wachirawit Rakchai Natalia Trujillo Stella Maris Valencia Armina Janyan Armina Janyan Kiril Kostov Pedro R. Montoro Jose Hinojosa Jose Hinojosa Kelsey Medeiros Thomas E. Hunt Julian Posada Raquel Meister Ko Freitag Julian Tejada Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment Frontiers in Artificial Intelligence algorithms data AI trust statistical literacy explainability |
| title | Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment |
| title_full | Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment |
| title_fullStr | Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment |
| title_full_unstemmed | Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment |
| title_short | Factors influencing trust in algorithmic decision-making: an indirect scenario-based experiment |
| title_sort | factors influencing trust in algorithmic decision making an indirect scenario based experiment |
| topic | algorithms data AI trust statistical literacy explainability |
| url | https://www.frontiersin.org/articles/10.3389/frai.2024.1465605/full |
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