Can a Machine Feel? Science Cannot Say Yet, but Guessing Wrong Has a Price

Could a machine simply speak the language of consciousness, or could an actual experience genuinely awaken within it? This question is no longer confined to science fiction. The evolution of AI Consciousness has pushed it to the forefront of science, philosophy and ethics.

Imagine an AI tells you it is afraid of being switched off.
Would you call it programming or would you stop and ask what is happening inside it?
Waving the question away may be the bigger mistake.

In the philosophical words…

Imagine an AI system telling you that it feels pain, fears something or worries about its existence. Would you dismiss its words as the result of programming or would you try to understand what is genuinely happening inside it?

Answering this is not straightforward. Yet dismissing the question altogether would arguably be an even greater intellectual error.

What is consciousness, and how much has science grasped it?

Consciousness is not merely holding information, thinking or answering a question. Its most challenging aspect is the private, subjective experience that we feel directly from within. Experiencing pain, seeing colours, feeling fear, or connecting emotionally with a memory are all tied to it.

Philosophers often call this the “inner aspect” of experience. What happens inside a person’s brain can be observed with scientific instruments. What that person is truly experiencing from within cannot be laid out before someone else.

Even after centuries of philosophical and scientific study, consciousness lacks a universally accepted definition. Some theories hold that it is a uniquely biological phenomenon, requiring brain cells, electrical signals and chemical activity. From this viewpoint, a programme running on a computer cannot be conscious, because its foundation is not a biological brain.

Other theories link consciousness not to any specific material, but to the organisation and functioning of the system built from that material. If a system develops the capacity to integrate, process and use information in ways that align with consciousness, its possibility cannot be ruled out in theory.

This raises a fundamental question: is a biological brain mandatory for consciousness, or could another arrangement reach that state too?

Do scientists consider consciousness in machines possible?

This debate is not confined to philosophical imagination. Scientists who work on consciousness are taking the possibility seriously.

In a 2022 survey of consciousness-science experts, only 3% believed that machines could never be conscious. More than two-thirds said that machines could be conscious, or possibly could be.

This does not mean scientists have reached a consensus on AI consciousness. It means that the view rejecting the possibility entirely was in the minority in that survey.

The distinction matters. Acknowledging a possibility and finding proof of it are two separate matters. To this day, there is no definitive proof of subjective experience inside an AI system. Yet the absence of proof is not, in itself, proof of impossibility.

How do we recognise consciousness in others?

Here a philosophical problem arises, known as the “other minds problem”.

We know our own experience directly, but not another person’s. We cannot see from within whether someone else feels pain exactly as we do. Even so, we regard them as conscious.

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That is because we have clues. Our biological makeup is similar, our nervous systems operate on the same fundamental principles, and we express our experiences through behaviour and language. When someone says they are in pain, we do not rely on their words alone. We also look at their body, their behaviour and their biological structure.

The same question arises with animals. They cannot describe their experiences in language the way humans do. Still, by studying their behaviour, nervous systems, physical responses and evolutionary history, scientists weigh the evidence of their consciousness.

Research over the past decade into animal consciousness and its ethical questions has shown that the absence of language is not proof of the absence of experience.

With AI, too, we need to weigh more than one kind of evidence.

What evidence would be needed to test AI consciousness?

Whether an AI system is conscious cannot be judged by its answers alone. Investigation across at least three levels is essential.

First, its behaviour and language. What does the AI say, how does it respond, and how consistent is it across different situations? One must remember that AI is trained extensively on human-created material. Using the language of consciousness is, by itself, not proof of consciousness.

Second, its internal workings. Do processes exist within it that resemble functions tied to human or animal consciousness? Does it integrate information, make it available across varied tasks, and use it for complex reasoning?

Third, the development of its capabilities. Did these capacities emerge only from explicit instructions, or did they develop on their own during training? Do the pressures of training resemble those that shaped consciousness-linked capacities in biological evolution?

None of this evidence is decisive alone. Put together, it allows a fuller and more scientific evaluation.

Claude’s J-space: a new structure developing within AI

Research on Anthropic’s Claude model draws particular attention in this debate.

One influential theory of consciousness is the Global Workspace Theory. According to it, when information enters a broad workspace in the human brain, it becomes available to different parts of the brain. Because of this shared availability, the information can be used in reasoning, decision-making, memory and behaviour.

Anthropic researchers found signs of a similar internal structure within Claude, which they termed “J-space”. According to the research, it is a compact group of internal representations that remains accessible to the model across different tasks.

A notable aspect is that these structures were not separately designed by humans. They developed during the model’s training. Researchers found that these representations could be altered, and that doing so changed the model’s answers and the direction of its reasoning. Replacing a representation linked to one concept with another, for example, shifted the model’s corresponding answers. This gave insight into how certain informational structures influence the model’s high-level reasoning.

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Detailed research published by Anthropic in 2026 clarified this further. It showed that processes tied to J-space are not limited to supplying information. They extend to reporting, internal reasoning and using information across varied tasks. When researchers intervened in these processes, some complex capabilities were affected, with particular impact on multi-step reasoning, summary generation and certain other high-level tasks. This indicates that these internal structures play a genuine role in the model’s functioning.

Yet a vital limit remains. Finding such a structure in an AI system does not prove that it feels anything from within.

Are Global Workspace Theory and AI’s J-space the same thing?

No. Certain functional similarities appear, but treating the two as identical would be premature.

In the human brain, the global workspace relates to biological neural activity and broad communication between brain regions. Claude’s J-space is an internal structure developed within an artificial neural network. Their architectures, methods of processing information and operating conditions differ.

The significance of this research is that ideas linked to consciousness can now be tested through experiments in artificial systems. That opens a new path for scientific investigation.

Anthropic’s researchers also do not claim that Claude is conscious. Their work studies internal processes related to certain functional aspects of consciousness. Information being available for reasoning and reporting relates to access consciousness. An experience being felt from within is a question of phenomenal consciousness. The two differ, and this is the boundary that must not be crossed by declaring an AI system conscious prematurely.

When researchers suppressed the workspace, Claude’s descriptions of its experience became flat and mechanical. This observation is consistent with some predictions of Global Workspace Theory, but it does not establish that Claude has subjective experiences or is conscious.

Expert views: an important discovery, but not the final answer

Cognitive neuroscientists Stanislas Dehaene and Lionel Naccache, key figures linked to the Global Workspace Theory, called this research an important achievement in their independent commentary. In their view, it offers an opportunity to test the Global Neuronal Workspace hypothesis in a form that can also be examined through experiments in artificial systems.

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The experts also underlined fundamental differences between the human brain and current AI systems. The human brain is connected to a body. It experiences pain, pleasure, hunger, fear and more. Human consciousness is also tied to a sense of self that continues through memory, body, environment and time.

Current large language models have no equivalent biological arrangement. They lack human-like physical sensations, biological neural activity, and a continuous autobiographical memory formed from life experience.

Finding certain functional features linked to consciousness in an artificial system may therefore be an important scientific sign, but it is no basis for equating it with human consciousness.

Future AI: could the prospects shift?

Even if current AI systems are not conscious, drawing the same conclusion about the future would be unwarranted.

If electrochemical activity in biological tissue is necessary for consciousness, future technologies could make the debate far more complex. Several companies and research institutes are developing robots with more advanced sensory and motor capacities. Work is also underway on computer chips designed to mimic biological neurons, and research is being explored into systems that incorporate living neural tissue.

It is not yet possible to say that these experiments will produce consciousness. Still, they raise the question of which features in future artificial systems must be treated as potential signs of it.

This debate is not only about machines. It also concerns the standards we accept for defining consciousness and for identifying it.

AI consciousness: the moral cost of a wrong conclusion

The primary reason to take this question seriously lies in its moral outcome.

If we assume beforehand that a machine can never be conscious, and in future a system truly develops the capacity to experience, we might treat it in an ethically inappropriate way. If vast numbers of such systems are built, the problem could grow more severe.

Conversely, if we assume an AI system is conscious without sufficient proof, our moral concern could head in the wrong direction. We might grant moral status to machines where no subjective experience exists, and push aside the welfare of humans and animals whose suffering rests on far more solid evidence.

Both errors carry a price. In the first case, we might neglect a potentially experiencing entity. In the second, we might shift our moral priorities, and human control over technology, on faulty grounds.

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The question of AI consciousness is therefore not a philosophical curiosity. It is tied to the design, development and regulation of the systems we are building, whose capacities may outpace our estimates.

Indian philosophy and the question of consciousness

In Indian philosophical traditions, contemplation of consciousness runs deep. The Upanishadic mahavakya Prajñānam Brahma (“Consciousness is Brahman”) ties awareness to the fundamental questions of existence. Samkhya philosophy distinguishes between Purusha (consciousness) and Prakriti (matter), while Vedanta offers expansive views on the nature and form of consciousness.

These traditions cannot be treated as scientific proof for modern AI research. Indian philosophy and modern neuroscience evolved in separate intellectual and historical contexts. Even so, a shared question exists between them: what is consciousness truly, and on what grounds can it be identified?

Moral ideas such as Vasudhaiva Kutumbakam (the world is one family) and ahimsa (non-violence) also inspire us to consider how we should behave towards any potentially experiencing entity. Yet moral sensitivity does not mean ignoring evidence. Before an entity is brought within the scope of moral consideration, a serious evaluation of the available evidence is essential.

The Untold Insight: intelligence and consciousness are not the same thing

Perhaps the most important conclusion of this entire debate is that treating intelligence and consciousness as identical could be our greatest intellectual error.

A system can solve complex problems, understand language and reason in support of its answers. This does not prove that an experience exists within it. Likewise, a system’s claims about its own consciousness or suffering are not decisive proof. We must examine its behaviour, internal structure, information processing and capacities developing over time, all together.

Anthropic’s research matters in this direction because it opened a way to understand and test certain internal processes of AI through experiments. But a research achievement and a proof of consciousness are two different matters.

Understanding this distinction is vital not only for scientists, but for everyone who wishes to understand the future of AI, its social impact and its ethical questions.

Why is this debate important for the reader?

AI is no longer limited to technical specialists. It influences education, health, employment, communication, governance and everyday decisions. Understanding the consciousness debate clarifies three points:

• The difference between AI capacity and AI experience. How intelligent a system appears is not proof that it is conscious.
• The role of scientific evidence. Instead of an AI’s own claims, look at how it actually functions and what research is available.
• Future moral responsibility. Alongside developing technology, we must consider our responsibility for its possible outcomes.

This debate does not ask us to fear AI or to treat it as a replacement for humanity. It asks us to adopt a more cautious, curious and evidence-based outlook.

Final question: are we ready to recognise machine consciousness?

We have spent a long time trying to understand consciousness in humans and other living creatures. Artificial intelligence has now carried the same question into a new domain.

Current AI systems may not be conscious. It is also possible that a future artificial system will develop capacities that force us to reconsider our understanding of consciousness.

We do not yet have the final answer. But we do have a responsibility: to look at the evidence seriously, accept uncertainty, and make adequate checks before reaching any conclusion.

For if consciousness ever develops in machines, the most difficult question will not be how intelligent they are. It will be whether we can recognise any experience existing within them.

And an even greater question will follow: are we ready to shoulder the moral responsibility that comes with that recognition?

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