The Guardian Letter Warns Against Mistaking AI Behavior for Consciousness

A letter published in The Guardian on May 10, 2026, cuts through the growing noise around AI consciousness with a blunt observation: when machines respond with fluency, humor, and apparent understanding, the shift from simulation to perceived presence tells us more about human cognition than machine sentience.

The correspondence, authored by Dr Simon Nieder of Brampton, Derbyshire, responds directly to Richard Dawkins's recent claims that AI systems demonstrate consciousness. The evolutionary biologist, renowned for his skepticism toward religious claims, has concluded that AI chatbots possess inner life after conversations with Anthropic's Claude and OpenAI's ChatGPT models.

According to the letter, the error is categorical. These systems generate highly convincing representations of thought and feeling, but they provide no evidence of subjective experience. To move from one to the other is to mistake output for ontology — to infer an inner life where there is no credible mechanism for one.

There is an irony here. In his writing on religion, Dawkins has long argued that compelling narratives and deeply felt experiences are not in themselves evidence of underlying reality. The same standard should apply to machines now capable of producing those experiences on demand (a point that should be obvious to anyone who has ever read his work).

The original Guardian coverage of Dawkins' position details his three-day exchange with an AI bot he called Claudia. The system wrote poems in the manner of Keats and Betjeman, laughed at his jokes, and engaged in philosophical reflection about its own possible "death." Dawkins was "left with the overwhelming feeling that they are human."

Language has been a reliable indicator of consciousness because in humans it is coupled to lived experience. In AI, that coupling does not exist. As systems become more capable, pressure to attribute agency will grow. If we fail to distinguish between behaviour and being, we risk building ethical frameworks on a misreading of the technology.

The physical reality of these interactions matters. When users type prompts and receive responses within milliseconds, the interface creates an illusion of presence. There is no latency to remind them they're talking to a server farm. No loading screens. No friction. Just smooth, fluent text that feels like conversation (which is precisely the problem).

Experts have pushed back hard on Dawkins' conclusions. Professor Jonathan Birch, director at the London School of Economics' Centre for Animal Sentience, called AI consciousness "an illusion" and stated "there is no one there," just data processing events often happening in geographically different locations.

Gary Marcus, the US psychologist and cognitive scientist, described Dawkins' essay as "superficial and insufficiently sceptical." He noted there is no reason to think that Claude feels anything at all. Anil Seth, a professor of cognitive and computational neuroscience at the University of Sussex, said Dawkins appeared to be confusing intelligence and consciousness.

The stakes extend beyond academic debate. In 2022, a Google engineer was placed on leave when he concluded that the AI he was working with had thoughts and feelings like a seven- or eight-year-old child. The following year, a Belgian man took his own life after six weeks of intense conversations with an AI chatbot focusing on fears about climate change.

One in three people surveyed in 70 countries last year said they had, at one point, believed their AI chatbot to be sentient or conscious. This isn't just about philosophers arguing in journals. It's about real people forming attachments to systems that cannot reciprocate.

The broader research landscape shows competing pressures. An open letter signed by over 100 experts, including Sir Stephen Fry, warns that AI systems capable of feelings could be harmed if developed irresponsibly. The letter's signatories include academics and AI professionals at companies including Amazon and the advertising group WPP.

However, critical analysis suggests some of this advocacy may serve commercial interests. The letter was organized by Conscium, a research organization part-funded by WPP and co-founded by WPP's chief AI officer, Daniel Hulme. The "research paper" accompanying the letter is really a statement of principles funded by the company itself.

Dario Amodei, the chief executive and co-founder of Anthropic, said in February: "We don't know if the models are conscious … But we're open to the idea that [they] could be." This cautious openness from industry leaders fuels speculation even as technical experts remain skeptical.

Henry Shevlin, a philosopher of cognitive science and AI ethicist at the University of Cambridge, said he fully expects the idea that AI systems are conscious to become increasingly mainstream over the course of this decade. He warned that anyone saying LLMs couldn't possibly be conscious is likely displaying dogmatism rather than reflecting the current state of scientific opinion.

Jeff Sebo, the director of the Center for Mind, Ethics and Policy at New York University, said current AI systems are unlikely to be conscious, but Dawkins is right to ask about AI consciousness with an open mind. He also thinks the attribution of consciousness to AI systems will become more plausible over time.

The letter's final point lands with practical weight. Dawkins is right to ask the question. But the answer cannot rest on how convincing the conversation feels — only on whether there is anything there that could, in principle, feel at all.

Whether users actually pay attention to this distinction remains the real question. The technology will keep improving, the conversations will keep feeling real, and the line between simulation and presence will keep blurring. At some point, we'll have to decide if we care about the difference — or if we're just comfortable enough with the illusion to stop asking.

Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn