The Right to Be Forgotten in Artificial Intelligence: Issues, Approaches, Limitations and Challenges

J. Lobo, S. Gil-Lopez, J. Del Ser
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Abstract

The Right To Be Forgotten is widely conceived as a fundamental principle of the human being. It has become a subject of capital importance in domains where sensitive information is collected from individuals, requiring the provision of monitoring, governance and audit tools to control where such information is used. Artificial Intelligence models are not an exception to this statement: since they are learned from data, this fundamental right should allow individuals to have their personal information erased from AI-based systems. However, the application of this right is not straightforward: what does erasing mean in the context of a model learned from data? Is it just a matter of removing the concerned data and retraining the models? This manuscript provides a brief overview of these and more issues, proposing a desiderata for technical advances noted in this direction, and outlining research directions for prospective studies.
人工智能中的被遗忘权:问题、方法、限制和挑战
被遗忘权被广泛认为是人类的一项基本原则。在从个人收集敏感信息的领域,它已成为一个至关重要的主题,需要提供监测、治理和审计工具来控制这些信息的使用地点。人工智能模型也不例外:因为它们是从数据中学习的,这项基本权利应该允许个人从基于人工智能的系统中删除他们的个人信息。然而,这种权利的应用并不直截了当:在从数据中学习的模型的背景下,擦除意味着什么?这只是移除相关数据并重新训练模型的问题吗?这份手稿提供了这些和更多问题的简要概述,提出了在这个方向上指出的技术进步的愿望,并概述了前瞻性研究的研究方向。
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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