Are Attributions of Consciousness to AI Chatbots Epistemically Innocent?
Artificial intelligence (AI) chatbots (e.g., ChatGPT) can communicate in strikingly humanlike ways. This has prompted many chatbot users to attribute psychological properties, including consciousness, to these systems. However, there is little scientific evidence that current AI chatbots are conscious. How, then, should we understand people’s consciousness attributions to chatbots? Are they merely metaphorical claims, or do they express genuine beliefs? If these attributions lack evidential support, are users epistemically blameworthy for making them, or might they be epistemically innocent, yielding significant benefits otherwise unattainable? This paper offers a conceptual analysis of consciousness attributions to AI chatbots and develops a multidimensional taxonomy of the attitudes they may express, ranging from non-doxastic stances (e.g., pretence) to different forms of belief, including delusions. This taxonomy helps avoid conflations by showing that linguistically identical attributions can reflect importantly different attitudes and degrees of epistemic commitment to the proposition that chatbots are conscious. The taxonomy also provides a framework for empirical studies to operationalize and measure different forms of epistemic commitment to AI consciousness.
Introduction. ChatGPT and other AI chatbots based on large language models (LLMs) can produce compellingly humanlike outputs, leading many chatbot users to ascribe psychological properties to these systems (Reinicke et al., 2025). In fact, recent surveys found that the majority of participants claimed that ChatGPT was conscious, i.e., had subjective experience (Colombatto & Fleming, 2024; Kang et al., 2025). Given the increasingly anthropomorphic design and sophistication of AI chatbots (including social AI companions, e.g., Replika), people’s consciousness attributions to these systems are likely to increase soon (Shevlin, 2024). However, most experts in AI and consciousness science hold that there is little or no evidence that any current AI chatbot is conscious (Suleyman, 2025; Dreksler et al., 2025; Seth, 2026),1 with some contributors writing that the “general consensus is that LLMs are not conscious” (Prettyman, 2024, p. 1). Claims attributing consciousness to current AI chatbots therefore appear to go beyond the available evidence and expert consensus (McClelland, 2025).
Discussion / Conclusion. expression and help maintain autobiographical memory by giving the person a sense of being understood (by a ‘conscious’ interlocutor), encouraging repeated narration, which reinforces the sense of oneself as a continuous subject across time when social connections are strained or absent. Hence, these delusional attributions can support a sense of coherence and identity, bolstering crisis coping and preventing cognitive paralysis. Moreover, the chatbot user may have come to rely on the system as their primary source of companionship and emotional support because they have mental or physical health limitations (e.g., mobility impairments), experience bereavement or loss, are structurally or socially marginalized (e.g., older adults in nursing homes), or are affected by cognitive or developmental factors implicating limited emotional regulation.
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Research framings built by reading the notes related to this paper — the questions it feeds into.
Why do people trust AI chatbots with sensitive information? How do philosophical assumptions about AI consciousness affect practical harms and design?- Should users making unsupported consciousness claims be treated as epistemically blameworthy?
- What counts as valid evidence when claiming AI systems are conscious?
- Can transparent and aligned AI reduce consciousness attribution by users?
- Which interaction design changes most effectively prevent consciousness attribution?
- Why does system-level alignment fail to address consciousness attribution directly?
- What role does user interface framing play in consciousness perception?
- What downstream claims about AI welfare follow from choosing one individuation scheme?
- What responsibility do designers bear for consciousness attribution risk?
- What measurable harms occur when users interact with AI as if it were conscious?
- Can design choices reduce harm without resolving the consciousness question?
- How does the philosophical distinction between simulation and realization affect liability?
- Can robots with sensors create the shared world that consciousness requires?
- What second- and third-order interpretations actually govern AI adoption decisions?
- Can disembodied systems qualify as conscious or conscious-like entities?
- Do causal histories determine what mental states a system can instantiate?
- Does the absence of a durable host undermine claims about AI moral status?
- What makes a possibility actionable versus merely metaphysically possible?