Build confidence and acceptance of AI-based decision support systems - Explainable and liable AI

2020 13th International Conference on Human System Interaction (HSI) Pub Date : 2020-06-01 DOI:10.1109/HSI49210.2020.9142668

C. Nicodeme

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引用次数: 13

Abstract

Artificial Intelligence has known an incredible development since 2012. It was due to the impressive improvement of sensors, data quality and quantity, storage and computing capacity, etc. The promises AI offered led many scientific domains to implement AI-based decision support tool. However, despite numerous amazing results, very serious failures have raised Human mistrust, fear and scorn against AI. In Industries, staff members cannot afford to use tools that might fail them. This is especially true for Transportation operators where security and safety are at risk. Then, the question that arises is how to build Human confidence and acceptance of AI-based decision support system. In this paper, we combine different points of view to propose a structured overview of Transparency, Explicability and Interpretability, with new definitions arising as a consequence. Then we discuss the need for understandable information from the AI system, to legitimate or refute the tool's proposal. To conclude we offer ethical reflexions and ideas to develop confidence in AI.

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建立对基于人工智能的决策支持系统的信心和接受度——可解释和负责任的人工智能

自2012年以来，人工智能取得了令人难以置信的发展。这是由于传感器、数据质量和数量、存储和计算能力等方面的显著改进。人工智能带来的前景促使许多科学领域实现基于人工智能的决策支持工具。然而，尽管人工智能取得了许多惊人的成果，但非常严重的失败引起了人类对人工智能的不信任、恐惧和蔑视。在工业领域，员工不能使用可能使他们失败的工具。对于安全处于危险中的运输运营商来说尤其如此。那么，由此产生的问题是如何建立人类对基于人工智能的决策支持系统的信心和接受度。在本文中，我们结合不同的观点，提出透明度，可解释性和可解释性的结构化概述，并由此产生新的定义。然后我们讨论了人工智能系统对可理解信息的需求，以证明或反驳工具的建议。最后，我们提供了道德反思和想法，以培养对人工智能的信心。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2020 13th International Conference on Human System Interaction (HSI)

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