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From service design thinking to the third generation of activity theory: a new model for designing AI-based decision-support systems

delete2024-03-21
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OA
AI
S
Silvia Marocco *
A
Alessandra Talamo
F
Francesca Quintiliani
DOI:10.3389/frai.2024.1303691delete
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Abstract

Abstract

En 中文
Introduction The rise of Artificial Intelligence (AI), particularly machine learning, has brought a significant transformation in decision-making (DM) processes within organizations, with AI gradually assuming responsibilities that were traditionally performed by humans. However, as shown by recent findings, the acceptance of AI-based solutions in DM remains a concern as individuals still strongly prefer human intervention. This resistance can be attributed to psychological factors and other trust-related issues. To address these challenges, recent studies show that practical guidelines for user-centered design of AI are needed to promote justified trust in AI-based systems.Methods and results To this aim, our study bridges Service Design Thinking and the third generation of Activity Theory to create a model which serves as a set of practical guidelines for the user centered design of Multi-Actor AI-based DSS. This model is created through the qualitative study of human activity as a unit of analysis. Nevertheless, it holds the potential for further enhancement through the application of quantitative methods to explore its diverse dimensions more extensively. As an illustrative example, we used a case study in the field of human capital investments, with a particular focus on organizational development, which involves managers, professionals, coaches and other significant actors. As a result, the qualitative methodology employed in our study can be characterized as a pre-quantitative investigation.Discussion This framework aims at locating the contribution of AI in complex human activity and identifying the potential role of quantitative data in it.
Keywords:
activity theory
service design thinking
multi-actor decision-making
investments in human capital
organizational development
decision-support systems

Journal

F
Frontiers in Artificial Intelligence
IF:
4.7
Papers:
2.2K
Citations:
4.4K

Organization

S
sapienza university rome
Scholars:
6.2W
Papers: 4.7W
Citations: 381
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