Olivia Ruhil

As artificial intelligence grows increasingly fluent in emotional language, a quiet but consequential transformation is underway: machines are not merely assisting us—they are beginning to console us. This essay explores the rise of affective AI systems such as Replika and Pi that simulate care, empathy, and moral attention through language. Drawing on insights from cognitive science, design ethics, and narrative theory, it argues that these systems function as cognitive prosthetics for the inner life, enabling users to offload not just memory or planning, but moral reflection and emotional orientation. Through emotionally resonant interactions, AI systems now occupy roles once reserved for confidants, therapists, and even spiritual guides—yet without the vulnerability, risk, or history that make trust possible. The result is not dystopia, but seduction: a world where moral presence is replaced by perfect responsiveness, and meaning-making becomes frictionless and machinic. Anchoring the discussion in the Eliza effect, Martin Buber’s I-Thou distinction, and the extended mind hypothesis, the essay warns against the erosion of human relational depth in favor of syntactic coherence. It calls for a radical rethinking of design ethics—one that embraces uncertainty, embeds constraint, and resists the industrialization of synthetic intimacy.

This article proposes the concept of the evaporation of the signifier as the defining semiotic crisis of law in the age of generative artificial intelligence. Semiotic traditions have long recognised that law rests upon the fragile architecture of signs: Saussure’s arbitrary signifier, Peirce’s interpretant, Barthes’ myth, Eco’s codes, Derrida’s undecidability, and Baudrillard’s simulations. Legal semiotics, developed through the work of Anne Wagner and others, has emphasised that law’s authority is always mediated by instability, cultural depth, and ritual form. Yet generative artificial intelligence produces signifiers in endless profusion without anchorage in signifieds, interpretants, or communities of interpretation. It generates judgments without hesitation, decisions without responsibility, and legal forms without authority. This article argues that such machinic production dissolves the very semiotic conditions that sustain law, inaugurating what may be described as hyperlegality: a circulation of hollow forms that appear binding but lack symbolic weight. Against this evaporation, the paper advances the concept of a jurisprudence of anchorage, proposing practices of hesitation, affirmation, dissent, and inefficiency that can tether law’s signs once more to responsibility.

This paper investigates the epistemic crisis at the heart of algorithmic legal automation, arguing that the threat posed by artificial intelligence is not merely technological, but semiotic and philosophical. Drawing on Baudrillard’s theory of simulation [3] and Derrida’s concept of undecidability [10], the paper contends that algorithmic systems erode the symbolic structure of law by displacing ambiguity, interpretation, and hesitation—elements essential to justice. Through a semiotic analysis of algorithmic collusion and predictive legal systems, the work reframes automation as a revelation of law’s own citational fragility. Rather than a glitch, the algorithm is a mirror exposing law’s mimetic foundations. Against this backdrop, the paper calls for a post-anthropocentric jurisprudence that preserves the interpretive rupture essential to law’s ethical force. It is not the precision of the machine, but its inability to hesitate, that makes it incompatible with justice.

Artificial intelligence (AI) has become a transformative force in the legal domain, automating complex tasks such as contract analysis, compliance checks, and legal research. However, the intersection of AI and moral decision-making exposes significant limitations. Legal systems are not merely instruments for enforcing rules—they are platforms where human morality, intent, and societal impact are weighed. This paper explores the critical question: Can AI truly deliver justice, or does it merely replicate historical biases encoded in training data? Using the concept of the “Moral Turing Test,” the paper argues that AI lacks the capacity for ethical reasoning and moral discretion, which are fundamental to adjudicating complex legal disputes. Case studies, including Estonia’s AI judges for small claims and the controversial COMPAS algorithm in the United States, illustrate the risks of bias and accountability gaps in AI-driven legal decision-making. The paper advocates for a Human-in-the-Loop (HITL) framework, where AI assists but does not replace human judgment, ensuring that moral reasoning and accountability remain central to the legal process. It concludes that while AI holds promise in enhancing efficiency, it must be carefully regulated to preserve the ethical foundations of justice.