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Talk · International Conference on Computer Science and Engineering · September 1, 2026

Beyond the Trolley Problem: Dostoevsky's Crime and Punishment as a Framework for AI Ethics

Guzaliya Haydarova, Gulnoza Salimova

Gulnoza Salimova
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Abstract

Autonomous systems in transport, medicine, and defence increasingly select actions in situations where every available option harms someone, yet many decision architectures scalarise heterogeneous harms into one objective and return a confident optimum. This paper asks what design requirements follow when that confidence is itself a failure mode. Using a qualitative interdisciplinary method—hermeneutic reading of Fyodor Dostoevsky's Crime and Punishment, conceptual mapping to AI decision contexts, and targeted thematic synthesis of peer-reviewed AI ethics literature—we develop three design claims. First, consequentialist language can operate as post-hoc rationalisation; therefore, the deployed objective should be audited against its stated ethical justification. Second, some individual-level harms should be encoded as aggregation-invariant constraints rather than weighted terms. Third, responsibility gaps should be treated as design defects requiring logged and attributable human decision points. We consolidate these claims into a moral confidence threshold: an abstention rule, related to selective prediction and safe reinforcement learning, that blocks autonomous execution when the best available action exceeds a deliberatively set individual-harm ceiling or when competing actions are morally indistinguishable. The mechanism is a conceptual design proposal, not a validated result; a simulator-based validation protocol is specified. The framework's Christian-personalist basis is a stated limitation requiring cross-tradition testing.

Ethics and Social Impacts of AIEthics in Business and EducationPhilosophical Ethics and TheoryAI ethicsautonomous decision-makingtrolley problem

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