Xinling Zhang
School of Foreign Studies, University of Science and Technology Beijing, Beijing, China

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Anti-Art Narrative and Human-Machine Property Justice in Machines like Me Xinling Zhang; Xiaohui Liang
International Journal of Education and Humanities Vol. 6 No. 2 (2026): International Journal of Education and Humanities (IJEH)
Publisher : Ilmu Inovasi Nusantara

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Abstract

The novel Machines Like Me by Ian McEwan has generated diverse readings concerning artificial intelligence ethics, posthuman subjectivity, and political allegory. However, existing scholarship has largely overlooked a crucial dimension: the ethics of property justice embedded in the narrative. As AI technologies increasingly disrupt traditional labor and ownership frameworks, the novel’s depiction of property distribution crises becomes a pressing real-world concern. To address this gap, the paper systematically critiques and reconceptualizes the property relations presented in the novel, moving beyond moral intuition toward a structured theory of justice. Employing the Frankfurt School’s theory of aesthetic negativity, the analysis traces how the novel’s formal self-negation—particularly through the actions of the AI Adam and the human characters Charlie and Benn—unveils and challenges hidden injustices. The findings reveal three key movements: first, a diagnostic layer where Charlie’s labor is separated from possession, normalized by conventional morality; second, a negative moment where Adam’s act of donation shatters this concealment by benefiting “the least advantaged members of society”; and third, a constructive proposal where Benn’s tax scheme institutionalizes individual justice into an operable legal framework. Through a layered analysis of “diagnosis—concealment—negation—construction,” this paper demonstrates how aesthetic critique does not remain confined to interpretation but offers a viable pathway from literary imagination to institutional reform, providing a practical response to property injustice in the age of intelligent machines