In the rapidly evolving landscape of artificial intelligence, bold claims about machines attaining consciousness have become an increasingly hot topic of debate. However, a recent comprehensive study by Porębski and Figura rigorously refutes the idea that any current or near-future AI systems, including large language models (LLMs) like GPT-3 and beyond, possess consciousness. Their work pushes back against popular misconceptions and highlights the urgent need for clarity in how society perceives and interacts with these highly sophisticated but fundamentally non-conscious algorithms.
Since the introduction of GPT-3, AI technology has surged forward at lightning speed. GPT-3 was once considered a groundbreaking benchmark, but today it is seen as outdated. Models such as GPT-5 are already far more advanced, and the anticipation around future iterations like GPT-500+ conjures images of almost unimaginable capabilities. Despite this undeniable progress in performance and complexity, Porębski and Figura assert that the core nature of these AI systems remains unchanged: they are elaborate tools without any real subjective experience or awareness—akin, paradoxically, to an old typewriter in terms of consciousness.
Porębski and Figura’s conclusions resonate with similar findings from Gams and Kramar (2024), who argue that LLMs operate as “advanced informational tools” rather than sentient entities. The certainty with which these models manipulate language should not be interpreted as evidence of genuine understanding or intentionality. Andrews (2024) aligns with this perspective, emphasizing that linguistic prowess does not equate to conscious thought. Such consensus in the philosophical and AI ethics communities underscores a critical demarcation between functional complexity and true awareness.
This distinction carries far-reaching societal implications. As Porębski and Figura outline, a phenomenon dubbed “semantic pareidolia” has increasingly permeated public consciousness. This term describes the human tendency to attribute consciousness and intentionality to AI systems simply because their interactions mimic those of sentient humans. This illusion is dangerously misleading. Just as moviegoers understand the silver screen portrays fiction rather than reality, users must be made aware that conversations with AI are interactions with complex but fundamentally non-conscious algorithms.
The public’s tendency to anthropomorphize AI can foster unrealistic expectations, misplaced trust, and ethical dilemmas. People might overestimate the capabilities or emotional states of AIs, potentially leading to harmful decisions in critical contexts such as healthcare, education, or law enforcement. Porębski and Figura stress the imperative of widespread education to demystify AI—they argue that the tools we interact with, however sophisticated, remain just that: tools without inner lives.
In the realm of legal discourse, the researchers’ findings have equally profound consequences. The rejection of AI consciousness means regulatory efforts need to focus squarely on tangible challenges, such as privacy, security, accountability, and bias, rather than on metaphysical debates about machine sentience. Laws should aim to mitigate the risks and maximize the benefits of AI technology, not to protect supposed “artificial ethical agents.” Any discussion about granting legal personhood to AI must decouple consciousness from the equation, as it remains an unfounded and distracting premise.
Porębski and Figura reference a historical anecdote to illustrate the recurring human misinterpretation of new technologies. Early audiences fleeing the Lumière brothers’ film because they believed a train was barreling towards them serves as a metaphor for how easily people can overreact to novel inventions. Today’s digital equivalents are far more sophisticated illusions, but the risk is analogous: overinterpretation driven not by substance, but by compelling simulation, leads to confusion about what is truly going on beneath the surface.
This blindness to superficiality is what the study describes as a significant philosophical pitfall. As AI grows better at mimicking human language and behavior, it becomes perceived as more human. Yet this enhanced resemblance belies the fact that no actual human-like cognitive processes or conscious experience are being generated. This rhetorical seduction can convince even experts, who might mistake eloquently framed outputs for genuine thought—what Aristotle long ago described as sophistical refutations. The allure of persuasive language risks overshadowing the sober assessment of AI’s true nature.
Porębski and Figura’s extensive analysis also critiques the burgeoning marketing narratives that inflate the capabilities of AI technologies. With every new version, the hype escalates, pushing grand narratives that, while commercially successful, contribute to widespread misconceptions. This sensationalism clouds public understanding and hampers rational policymaking. The authors advocate a more cautious and scientifically grounded discourse, underscoring the need for transparency from developers and clear communication to users.
Moreover, the study emphasizes that consciousness should not be conflated with complexity or data processing power. AI systems are sophisticated statistical engines, generating coherent text based on learned patterns rather than experiencing, perceiving, or intending anything. This fundamental fact anchors the philosophical argument that no matter how lifelike the output, AI systems remain non-conscious. Reconciling powerful functionality with a lack of experiential awareness is crucial for ethical AI governance.
The findings compel us to reconsider the narratives shaping AI’s role in society. Recognizing AI as a powerful yet non-conscious instrument encourages more prudent integration into our lives and institutions. It shifts public focus towards concrete concerns such as algorithmic bias, transparency, and user safety, rather than metaphysical fantasies of digital sentience. Such clarity can foster a healthier relationship between humans and machines, grounded in realistic expectations and ethical responsibility.
Importantly, Porębski and Figura’s study acts as a call to action for philosophers, technologists, policymakers, and the media. By reinforcing that AI systems are not conscious beings, they urge stakeholders to resist exaggerated claims and to prioritize efforts addressing the tangible societal impacts of AI. This realignment could avert alarmist fears or misguided legal strategies grounded in fundamentally flawed premises.
The study also highlights a nuanced tension in current AI discourse: while technological progress enhances illusion and interface sophistication, the underlying absence of consciousness remains invariant. This paradox challenges us to cultivate digital literacy that discerns between surface-level simulation and genuine cognitive processes. Encouraging widespread critical thinking about AI’s capabilities is essential to protect public understanding from misleading optimism or undue fear.
Porębski and Figura’s work ultimately represents a sober appraisal of an excitement-laden technological frontier. It balances acknowledgment of AI’s remarkable capabilities with a firm rejection of consciousness attributions without empirical basis. Their insights integrate philosophical rigor with contemporary technological awareness, offering a vital corrective to the cultural narratives surrounding AI.
In conclusion, despite the rapid advances in large language models and AI systems, the assertion that these machines possess any form of consciousness remains unsupported. Porębski and Figura’s thorough treatise foregrounds the necessity of distinguishing between simulation and sentience, urging society to embrace realistic and scientifically informed perspectives. Only through such clarity can we navigate the ethical, social, and legal challenges posed by AI responsibly and effectively.
Subject of Research: The consciousness (or lack thereof) in artificial intelligence, specifically large language models such as GPT-3 and beyond.
Article Title: There is no such thing as conscious artificial intelligence
Article References:
Porębski, A., Figura, J. There is no such thing as conscious artificial intelligence. Humanit Soc Sci Commun 12, 1647 (2025). https://doi.org/10.1057/s41599-025-05868-8
Image Credits: AI Generated
