On Two XAI Cultures: A Case Study of Non-technical Explanations in Deployed AI System

• URL: http://arxiv.org/abs/2112.01016v1
• Date: Thu, 2 Dec 2021 07:02:27 GMT
• Title: On Two XAI Cultures: A Case Study of Non-technical Explanations in Deployed AI System
• Authors: Helen Jiang, Erwen Senge
• Abstract summary: Not much of XAI is comprehensible to non-AI experts, who nonetheless are the primary audience and major stakeholders of deployed AI systems in practice. We advocate that it is critical to develop XAI methods for non-technical audiences. We then present a real-life case study, where AI experts provided non-technical explanations of AI decisions to non-technical stakeholders.
• Score: 3.4918511133757977
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Explainable AI (XAI) research has been booming, but the question "$\textbf{To whom}$ are we making AI explainable?" is yet to gain sufficient attention. Not much of XAI is comprehensible to non-AI experts, who nonetheless, are the primary audience and major stakeholders of deployed AI systems in practice. The gap is glaring: what is considered "explained" to AI-experts versus non-experts are very different in practical scenarios. Hence, this gap produced two distinct cultures of expectations, goals, and forms of XAI in real-life AI deployments. We advocate that it is critical to develop XAI methods for non-technical audiences. We then present a real-life case study, where AI experts provided non-technical explanations of AI decisions to non-technical stakeholders, and completed a successful deployment in a highly regulated industry. We then synthesize lessons learned from the case, and share a list of suggestions for AI experts to consider when explaining AI decisions to non-technical stakeholders.

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