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University of Memphis Law Review

Authors

Kevin H. Smith

Abstract

This Article advocates for a fundamental shift in the way artificial intelligence (“AI”) consciousness is evaluated, moving beyond anthropocentric models that rely on human cognitive benchmarks. Traditional tests, such as the Turing Test, assume that human-like behavior is the ultimate criterion for consciousness, overlooking the possibility of novel, non-human modes of consciousness. Instead, this Article proposes a multi-dimensional framework that assesses AI systems based on their unique architectures and cognitive processes. By combining dimensions such as information integration, autonomous goal-pursuit, metacognitive self-modeling, affective motivation, social communication, counterfactual simulation, imaginative reasoning, and causal modeling, this framework provides a comprehensive and empirically grounded approach to detecting machine consciousness. Recognizing that AI consciousness—if it exists—may differ radically from human consciousness, this framework provides an important first step in establishing ethical, legal, political, economic, and social responses to the emergence of conscious AI entities. A rigorous evaluation of AI consciousness is not just an academic exercise but is a moral and practical imperative, as it lays the groundwork for ensuring appropriate rights, responsibilities, and protections for artificial minds.

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