Antonio Chella
Confirmatory factor analysis showed that the hypothesized four-factor model fit the data better than alternative models, providing preliminary evidence for the empirical distinctiveness of the focal constructs. Liking of AI and perceived emotional support each served as significant mediators in this association. In addition, the sequential indirect path from perceived anthropomorphism to liking of AI, perceived emotional support, and belongingness need was significant.
The possibility of sentient artificial intelligence has moved from speculative philosophy to a practical interdisciplinary problem for AI, robotics, and human-robot interaction. Large language models, multimodal agents, and embodied robots can now produce first-person reports, maintain dialogue, use tools, act through sensors and effectors, and participate in socially meaningful contexts. These capacities invite two symmetrical errors: anthropomorphic over-attribution and premature dismissal. This Perspective proposes a prolegomenal framework for future research on sentient AI. Its distinctive contribution lies in operationally integrating four elements that have largely been developed in separate literatures: conceptual disambiguation, multi-theory indicator profiles, causal-mechanistic testing, and robotics-specific evidence and governance. The paper distinguishes sentience, consciousness, self-modeling, metacognition, agency, moral patienthood, and AI welfare; separates evidence about an AI system from evidence about human attribution; and proposes domain-specific ordinal evidence levels rather than binary verdicts or an aggregate sentience score. It further specifies welfare- and valence-relevant tests, a preregistered rating procedure, and a concrete protocol for an embodied care robot using sensorimotor lesions, self-location manipulations, memory ablations, and anti-anthropomorphism controls. The aim is not to offer a definitive test for machine sentience, but to show how research could become more scientifically tractable, psychologically informed, robotics-relevant, and ethically responsible.