The use of publicly available online texts in training AI: an ethical analysis of AI’s right to learn

Abstract

Purpose This paper aims to discuss the ethical permissibility of using publicly available online texts in the training of AI. This practice has facilitated and accelerated the growth of AI technology, but it has also drawn accusations of exploiting authors and violating their intellectual property rights. Design/methodology/approach The discussion is based on the Kantian theory of ethics, a theory that is grounded in the duty to preserve and empower the autonomy of the human will. Findings Following from the duty to support human autonomy, the article makes two claims: First, AI should be granted the right to learn from public texts because the more AI learns, the better it assists humans in expanding their will. Second, AI’s right to learn should be conditional, not absolute. The article articulates three conditions that should be met prior to granting an AI system the right to learn from public texts: AI that uses public data must be freely available to the public, AI (and its developers) ought to educate the public on the uses and misuses of AI, and AI (and its developers) must remove personal information from the training data. Originality/value Under what conditions is it justifiable to use someone’s text without their permission? This very question is currently being examined in courts in the many lawsuits filed against AI companies. An ethical analysis of this question helps bridge the gap between the perspective of AI companies that claim to be using public texts for the public good and the perspectives accusing them of violating authors’ copyrights.

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