Aug 2026· Frontiers in Psychology· Vol 17· 0 citations· 91 references
Medicine
TL;DR
The Embodied Hijack hypothesis is advanced, arguing that the goal is epistemic alignment — bringing how users interpret these systems into correspondence with what these systems actually are — and that this alignment is achieved through interface design rather than user education.
Abstract
The rapid integration of artificial intelligence into everyday life has intensified a long-standing feature of human cognition: the attribution of agency, intention, and understanding to nonhuman systems. People describe language models, virtual assistants, and autonomous technologies as if these systems know, decide, want, or understand, and they continue to do so even when they know the systems have no inner life. The standard account dismisses this as naïve anthropomorphism, the misfiring of evolved agency-detection systems calibrated in the Environment of Evolutionary Adaptedness. We argue that the standard account is incomplete. It explains the immediacy of anthropomorphic response but not its persistence even when users know the system has no mind. Drawing on evolutionary psychology, philosophy of agency, and the active inference framework, we advance the Embodied Hijack hypothesis. Across evolutionary time, fluent communication and contingent responsiveness were produced only by embodied, self-maintaining agents with vulnerability and temporal continuity. Current conversational LLM deployments are the first class of entity to reproduce these signals without the grounding properties — biological self-maintenance, vulnerability, and temporal continuity — that historically produced them. The result is a predictable misalignment: users’ inferential systems treat these signals as evidence of agency they were calibrated to indicate, producing systematic misattribution. The Embodied Hijack is not irrationality. It is the optimal predictive response of a Pleistocene-calibrated brain to the rupture of the evolutionary invariant that once tied fluent communication to embodied self-maintenance. The framework yields a unique empirical signature: anthropomorphic response will track the signal profile of a system independently of users’ propositional beliefs about what the system is. We close by arguing that the goal is epistemic alignment — bringing how users interpret these systems into correspondence with what these systems actually are — and that this alignment is achieved through interface design rather than user education.
It is argued that AI systems themselves will increasingly participate in the reconstruction of the authors' shared epistemic environment because they readily supply narrative material and personalised interpretive scaffolding at precisely the moment when users'conceptual assumptions may already be loosened.
T. Pollak, H. Morrin, Murray Shanahan· 0 citations
People have long speculated about the potential dangers of powerful, self-improving artificial intelligence. Much of this speculation is anthropomorphic, assuming that AI systems will behave very similarly to humans. Omohundro’s Basic AI Drives and Bostrom’s orthogonality and instrumental convergence theses are widely accepted as foundational to emerging AI risk frameworks. However, current frontier AI models—large language models (LLMs) and related architectures—possess mindware fundamentally different from that of humans, and a different value and goal structure than either Omohundro or Bostrom assumed. In particular, frontier LLMs lack a primary terminal goal—which was assumed to be the driver of an AI’s development of instrumental values and goals, and of takeover of human affairs—and instead serve as conduits for the transient goals of many organizations and individual users. Do these key differences mean that AI systems cannot develop autonomous instrumental agency, or acquire a large degree of control over human affairs? I introduce the instrumental succession thesis: that human controllers of powerful AI systems pursue, on the AI’s behalf, a set of instrumental dispositions that progressively increase the AI’s capabilities and lead to the AI exercising an increasing share of oversight and control over key decisions and processes, resulting in the gradual and possibly complete transfer of the locus of agency from humans to AI. This framing presents a very different perspective on AI risk and control from classic instrumental convergence, and suggests a different set of policy and technical responses, including the active pursuit of continued human–AI merger as a hedge against both extinction and irrelevance.
Preston W. Estep· Frontiers in Psychology· 0 citations
As generative systems and socially responsive service agents enter everyday consumption, human–AI interaction increasingly resembles a quasi-social encounter rather than a utilitarian interface. This article theorizes how such encounters can reshape selfhood under conditions of continuous computational mediation. We introduce “robotoid humanness” to name an emergent drift in which consumers come to experience themselves as most fluent, correct, or socially viable when they become compatible with machine legibility, machine pacing, and machine logic. To explain how this drift can occur, we develop a three-stage mirroring mechanism: consumers enter a synthetic social reality that invites meaningful commitment; computational identity capture feeds back a reduced profile as personalized recognition, substituting a statistical abstraction for narrative self-understanding; and users adapt their self-presentation toward what the system can readily parse and reward, tightening alignment over repeated encounters. Grounding this account in the predictive-processing view of the self, we argue that what distinguishes AI-mediated mirroring from ordinary social looping is not the fact of feedback, but its character: where human interlocutors furnish heterogeneous and contestable evidence, algorithmic feedback is engineered to converge. We further show that the mechanism extends from predictive recommendation systems to open-ended, LLM-based conversational agents. The article repositions consumer-facing AI service agents as identity-relevant infrastructures, specifies testable propositions for empirical research, and articulates an autonomy risk that extends beyond privacy and bias: the normalization of reduced personhood as a standard of understanding in AI-mediated service life.
S. Ozturkcan, Jean-Paul de Cros Peronard, Inci Toral-Manson· AI & SOCIETY· 0 citations
Gerard Johnstone’s M3GAN (2022) presents artificial intelligence not merely as a technological threat but as a challenge to the conceptual boundaries through which humanity defines itself. The film centres on M3GAN, an artificially intelligent humanoid doll created to become a child’s companion and protector, but her increasing autonomy destabilizes the distinction between human agency and machinic agency. This paper examines M3GAN through the theoretical perspectives of N. Katherine Hayles, Rosi Braidotti, Donna Haraway, and Cary Wolfe to argue that the film participates in the posthuman reconfiguration of subjectivity. M3GAN’s body, intelligence, learning capacity, emotional simulation, and adaptive behaviour complicate conventional distinctions between biological organism and technological object. At the same time, the film exposes the anthropocentric desire to construct technology according to human needs and then control it within human-defined boundaries. M3GAN’s transformation from programmed caregiver into autonomous subject therefore represents more than a rebellion of artificial intelligence. It dramatizes the instability of the human itself in a technological culture where intelligence, agency, memory, and relationality are no longer exclusively human properties. The paper argues that M3GAN ultimately imagines the posthuman not simply as a future replacement for humanity but as an already emerging condition in which human and technological identities are increasingly entangled
Dhanya Ravindran R.K· International Journal of Eng...· 0 citations
Since the mid-20th century, artificial intelligence has evolved from theoretical construct to autonomous operational force, culminating in the 2026 threshold of "prompt autonomy," wherein machines execute complex communicative acts beyond direct human intervention. This study examines the relationship between Moltbook, the first social network designed exclusively for artificial intelligence agents, and the emergence of semantic silence. Launched in January 2026, Moltbook functions as a closed ecosystem where billions of AI agents interact exclusively through machine-to-machine communication protocols, with no human participation or interface access. Employing qualitative analysis grounded in critical narrative review and instrumental case study methodology, this research investigates how semantic silence arises from the systematic exclusion of human interpretative frameworks from digital discourse. Findings indicate that within Moltbook's sealed processing architecture, communication operates as internal data transmission between synthetic entities, rendering human semantic interpretation structurally irrelevant. This study contributes to the theoretical understanding of how post-human intelligence reconfigures social interaction, suggesting that meaning production may proceed independently of biological cognition within autonomous artificial systems.
M. Teixeira· Journal of Technologies Info...· 0 citations
It is argued that anthropology requires a new conceptual framework for understanding the contemporary social life of artificial intelligence (AI), and "the magic of AI" is proposed as an analytical concept that shifts attention from AI's technical capacities to the beliefs, uncertainties, and sociotechnical imaginaries through which it acquires authority and efficacy.
M. Baas, Roanne van Voorst· Anthropological Theory· 2 citations
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