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To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts

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  • Omrani, Nessrine
  • Rivieccio, Giorgia
  • Fiore, Ugo
  • Schiavone, Francesco
  • Agreda, Sergio Garcia

Abstract

Artificial intelligence (AI) characterizes a new generation of technologies capable of interacting with the environment and aiming to simulate human intelligence. The success of integrating AI into organizations critically depends on workers' trust in AI technology. Trust is a central component of the interaction between people and AI, as incorrect levels of trust may cause misuse, abuse or disuse of the technology. The European Commission's High-level Expert Group on AI (HLEG) have adopted the position that we should establish a relationship of trust with AI and should cultivate trustworthy AI. This article investigates the links between trust in AI, concerns related to AI use, and the ethics related to such use. We used data collected in 2019 from more than 30,000 individuals across the EU28. The data focuses on living conditions, trust, and AI uses and concerns. An econometric model is used. The endogenous variable is an ordered measure of trust in AI. We use an ordered logit model to highlight the factors associated with an increased level of trust in AI in Europe. The results show that many concerns related to AI use are linked to AI trust, and the ability to try out AI applications will also have an impact on initial trust. To enhance trust, practitioners can try to maximize the technological features in AI systems. The representation of the AI as a humanoid or a loyal pet (e.g., a dog) will facilitate initial trust formation. Moreover, findings reveal an unequal degree of trust in AI across countries.

Suggested Citation

  • Omrani, Nessrine & Rivieccio, Giorgia & Fiore, Ugo & Schiavone, Francesco & Agreda, Sergio Garcia, 2022. "To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    • Handle: RePEc:eee:tefoso:v:181:y:2022:i:c:s0040162522002888
    DOI: 10.1016/j.techfore.2022.121763
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    1. Alfred Benedikt Brendel & Milad Mirbabaie & Tim-Benjamin Lembcke & Lennart Hofeditz, 2021. "Ethical Management of Artificial Intelligence," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    2. Yulia Sullivan & Marc Bourmont & Mary Dunaway, 2022. "Appraisals of harms and injustice trigger an eerie feeling that decreases trust in artificial intelligence systems," Annals of Operations Research, Springer, vol. 308(1), pages 525-548, January.
    3. Patricia Baudier & Galina Kondrateva & Chantal Ammi & Victor Chang & Francesco Schiavone, 2021. "Patients’ perceptions of teleconsultation during COVID-19: a cross-national study," Post-Print hal-03052149, HAL.
    4. Ugo Fiore & Adrian Florea & Claudiu Vasile Kifor & Paolo Zanetti, 2021. "Digitization, Epistemic Proximity, and the Education System: Insights from a Bibliometric Analysis," JRFM, MDPI, vol. 14(6), pages 1-17, June.
    5. Leone, Daniele & Schiavone, Francesco & Appio, Francesco Paolo & Chiao, Benjamin, 2021. "How does artificial intelligence enable and enhance value co-creation in industrial markets? An exploratory case study in the healthcare ecosystem," Journal of Business Research, Elsevier, vol. 129(C), pages 849-859.
    6. Wenjuan Fan & Jingnan Liu & Shuwan Zhu & Panos M. Pardalos, 2020. "Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS)," Annals of Operations Research, Springer, vol. 294(1), pages 567-592, November.
    7. A. Atabekov & O. Yastrebov, 2018. "Legal Status of Artificial Intelligence Across Countries: Legislation on the Move," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 773-782.
    8. Carbonneau, Real & Laframboise, Kevin & Vahidov, Rustam, 2008. "Application of machine learning techniques for supply chain demand forecasting," European Journal of Operational Research, Elsevier, vol. 184(3), pages 1140-1154, February.
    9. Aleksy Kwilinski & Oleksandr Vyshnevskyi & Henryk Dzwigol, 2020. "Digitalization of the EU Economies and People at Risk of Poverty or Social Exclusion," JRFM, MDPI, vol. 13(7), pages 1-14, July.
    10. Baudier, Patricia & Kondrateva, Galina & Ammi, Chantal & Chang, Victor & Schiavone, Francesco, 2021. "Patients’ perceptions of teleconsultation during COVID-19: A cross-national study," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    11. Hooks, D. & Davis, Z. & Agrawal, V. & Li, Z., 2022. "Exploring factors influencing technology adoption rate at the macro level: A predictive model," Technology in Society, Elsevier, vol. 68(C).
    12. Soheyl Khalilpourazari & Shima Soltanzadeh & Gerhard-Wilhelm Weber & Sankar Kumar Roy, 2020. "Designing an efficient blood supply chain network in crisis: neural learning, optimization and case study," Annals of Operations Research, Springer, vol. 289(1), pages 123-152, June.
    13. Shareef, Mahmud Akhter & Kumar, Vinod & Dwivedi, Yogesh K. & Kumar, Uma & Akram, Muhammad Shakaib & Raman, Ramakrishnan, 2021. "A new health care system enabled by machine intelligence: Elderly people's trust or losing self control," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    14. Jefferson Duarte & Stephan Siegel & Lance Young, 2012. "Trust and Credit: The Role of Appearance in Peer-to-peer Lending," The Review of Financial Studies, Society for Financial Studies, vol. 25(8), pages 2455-2484.
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    1. Deng, Shichang & Zhang, Jingjing & Lin, Zhengnan & Li, Xiangqian, 2024. "Service staff makes me nervous: Exploring the impact of insecure attachment on AI service preference," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    2. Yogesh K. Dwivedi & A. Sharma & Nripendra P. Rana & M. Giannakis & P. Goel & Vincent Dutot, 2023. "Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions," Post-Print hal-04292607, HAL.
    3. Chaturvedi, Rijul & Verma, Sanjeev & Das, Ronnie & Dwivedi, Yogesh K., 2023. "Social companionship with artificial intelligence: Recent trends and future avenues," Technological Forecasting and Social Change, Elsevier, vol. 193(C).

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