Abstract
The use of artificial intelligence (AI)-based decision support systems (DSSs) is expected to enable superior human–XAI performance. To enhance decision-making performance, explanations are integrated into such DSSs (XAI DSSs). However, recent studies demonstrate that XAI in DSS does not necessarily result in improved decision-making performance, which is attributed to cognitive biases or to inaccurate heuristics regarding such XAI. There are also noted discrepancies regarding how humans think they will use XAI DSS versus their actual behaviour. Currently, there is no established theoretical framework to explain the cognitive mechanisms that underpin human decision-making when supported by XAI. We propose a theoretical framework that is grounded in the notion of extended self and in the dual-process theory of cognition. Building on existing studies, we explain that human–XAI interaction can change how humans base their decision-making, enabling a form of extended self. This reframing can support efficient design and implementation of XAI in DSS.
| Original language | English |
|---|---|
| Pages (from-to) | 224-255 |
| Number of pages | 32 |
| Journal | Journal of Business Analytics |
| Volume | 7 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2024 |
| Externally published | Yes |
Keywords
- decision support systems
- dual-process theory of cognition
- Explainable artificial intelligence
- extended self
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