Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866929337709625344 |
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| author | Haag, Felix Stingl, Carlo Zerfass, Katrin Hopf, Konstantin Staake, Thorsten |
| author_facet | Haag, Felix Stingl, Carlo Zerfass, Katrin Hopf, Konstantin Staake, Thorsten |
| contents | Information systems (IS) are frequently designed to leverage the negative effect of anchoring bias to influence individuals' decision-making (e.g., by manipulating purchase decisions). Recent advances in Artificial Intelligence (AI) and the explanations of its decisions through explainable AI (XAI) have opened new opportunities for mitigating biased decisions. So far, the potential of these technological advances to overcome anchoring bias remains widely unclear. To this end, we conducted two online experiments with a total of N=390 participants in the context of purchase decisions to examine the impact of AI and XAI-based decision support on anchoring bias. Our results show that AI alone and its combination with XAI help to mitigate the negative effect of anchoring bias. Ultimately, our findings have implications for the design of AI and XAI-based decision support and IS to overcome cognitive biases. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2405_04972 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support Haag, Felix Stingl, Carlo Zerfass, Katrin Hopf, Konstantin Staake, Thorsten Computers and Society Artificial Intelligence Human-Computer Interaction Machine Learning General Economics Economics Information systems (IS) are frequently designed to leverage the negative effect of anchoring bias to influence individuals' decision-making (e.g., by manipulating purchase decisions). Recent advances in Artificial Intelligence (AI) and the explanations of its decisions through explainable AI (XAI) have opened new opportunities for mitigating biased decisions. So far, the potential of these technological advances to overcome anchoring bias remains widely unclear. To this end, we conducted two online experiments with a total of N=390 participants in the context of purchase decisions to examine the impact of AI and XAI-based decision support on anchoring bias. Our results show that AI alone and its combination with XAI help to mitigate the negative effect of anchoring bias. Ultimately, our findings have implications for the design of AI and XAI-based decision support and IS to overcome cognitive biases. |
| title | Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support |
| topic | Computers and Society Artificial Intelligence Human-Computer Interaction Machine Learning General Economics Economics |
| url | https://arxiv.org/abs/2405.04972 |