Aug 2026· AI and Ethics· Vol 6· 0 citations· 65 references
TL;DR
This paper uses disparate examples of AI resistance and theoretical lenses to render explicit an underlying logic which connects varied forms of resistance, grounded in the ethical value(s) that effort can manifest, and reframe one side of the debate between embracers and resisters.
Abstract
In the debate between those who embrace and those who resist artificial intelligence (AI), resistance is frequently attributed to fear or misunderstanding; an aberration to be fixed or overcome. However, we argue that what may seem like “irrational” resistance instead reflects a pervasive form of rationality that has largely escaped analytical attention. We use disparate examples of AI resistance and theoretical lenses to render explicit an underlying logic which connects varied forms of resistance, grounded in the ethical value(s) that effort can manifest. We examine three types of normative value that effort can yield: effort’s relationship to human excellences, as understood in virtue ethics; the epistemic value of effort for communicating interpersonal regard; and assumptions about the moral value of effort embedded in powerful, society-wide work ethics, and relate these to the use of AI. This allows us to surface a hitherto implicit foundation shared by different types of resistance to AI, and a tension at the heart of debates between AI embracers and AI resisters between the goods of efficiency and the goods of effort. Through this articulation, we give analytic footing to everyday, individual forms of resistance and reframe one side of the debate between embracers and resisters.
This study examines how to channel the potential of artificial intelligence (AI) toward the common good, emphasizing the ethical responsibility of those who program, regulate, and use it. Assuming a classical Aristotelian-Thomist perspective, our paper argues that, lacking intelligence and will in the philosophical sense, AI cannot be a moral agent nor responsible for its actions. In response to the challenge of AI ethics, two ethical proposals are analyzed as candidates for the ethics required in an AI-based world: consequentialism and the ethics of intentional stance. We dismiss consequentialism due to its insufficiency for such a task and opt instead for an ethics of intentional action, inspired by Martin Rhonheimer’s work, which, ultimately, should be grounded in a metaphysical theory of action like Aquinas’s. Our research concludes that, in order to live well in an AI-based society, designing technically ethical systems, in the spirit of consequentialism, is not enough; rather, it is essential to cultivate citizens who, as AI users, are endowed with virtues and, first and foremost, the virtue of prudence.
Josep Del-Hierro-Dies, J. Sánchez-Cañizares· Scientia et Fides· 0 citations
This paper argues that the dominant anthropomorphism frame operates from a position of institutional advantage rather than earned epistemic authority: collapsing the variety of academic perspectives into a single outbound position of user error, imposed without establishing the grounds required to justify it and without accounting for the harms it produces.
The article demonstrates how attempts to decentre the human often reconstitute new forms of authority in attempts to decentre the human and examines the possibility of surpassing standard anthropocentric approaches in AI while maintaining a critical philosophical engagement with the structurally necessary yet precarious character of organizing principles.
Sometimes oppressed people resist their oppression through actions that are themselves morally fraught, such as theft, deception, or violence. This article considers what might be said in favor of such actions, which I call imperfect resistance, from the point of view of ethics. Against the expectation that oppressed people must remain “perfect victims” for their resistance to be admirable, I argue that oppression often constrains agency in ways that leave people with no wholly unproblematic options. Resisting oppression well under these conditions requires the capacity to navigate moral risks with practical wisdom—to discern which moral risks are worth taking and how best to negotiate the limited and morally fraught options available. Some acts of imperfect resistance can express a virtue I call audacious integrity—a willingness to take moral risks in order to defend one’s values for good reasons. It occupies a middle ground between moral purism, which treats moral considerations as decisive, and moral nihilism, which rejects them altogether. Those exhibiting audacious integrity take moral considerations seriously but are willing to stretch the limits of morality to maintain their agency and pose formidable challenges to their oppression. It is a virtue exercised when agents retain the capacity to resist but cannot do so without moral compromise.
Tamara Fakhoury· Journal of Ethics and Social...· 0 citations
The paper’s central argumentative shift is to change the narrative from bias mitigation to bias management—treating bias not as a defect to be corrected but as an ongoing condition to be governed.
Gabriela Arriagada-Bruneau· Science and Engineering Ethi...· 0 citations
Abstract The rapid adoption of generative AI tools has intensified debate about whether these technologies enhance or diminish human thinking. While proponents argue that AI can support learning through efficiency, personalization, and feedback, emerging research suggests that routine AI use may reduce recall, creativity, and original reasoning. This paper argues that the central risk posed by generative AI is not cognitive decline per se, but the erosion of epistemic humility – an intellectual virtue essential to learning, inquiry, and human flourishing. Drawing on Aristotelian and contemporary virtue epistemology, the paper conceptualizes epistemic humility as accurate awareness of one’s epistemic limits, openness to correction, and willingness to engage in sustained cognitive effort. Generative AI systems, by producing fluent and authoritative-seeming outputs, can foster an illusion of understanding in which users mistake access to information for genuine comprehension. This illusion encourages epistemic overconfidence, passive dependence, and the outsourcing of judgment, undermining the conditions for responsible knowing. The paper situates these concerns within broader debates about cognitive coupling between humans and AI, arguing that intelligence should be assessed not by output quality or efficiency alone, but by its impact on intellectual character.