At a cozy bar in Manhattan, I recently had a first date with a software engineer who works for one of the big technology companies. Given my interest in artificial intelligence, I thought we might hit it off. But when I told him that I work on moral problems related to A.I., including the possibility that it might become conscious, he barely suppressed a laugh.
There’s no way A.I. could be conscious, he declared. Then he asked, incredulously, if I even knew how large language models work.
I wasn’t sure how to respond. Though my research requires a fairly detailed understanding of L.L.M.s, no one, not even their designers, entirely knows how L.L.M.s work. In retrospect, I should have asked my date if he understood how consciousness works. Because while he seemed to think that I had an inflated sense of A.I. capabilities, I wonder whether he has an inflated sense of what consciousness requires.
No one can credibly claim to understand consciousness — that inner, subjective, what-it-is-like quality of our mental experiences. Despite centuries of investigation, scientists and philosophers still disagree about what consciousness is. Some theories hold that it is a uniquely biological phenomenon, requiring particular kinds of cellular activity and electrical signaling that computers lack. But other theories hold that consciousness depends not on what a system is made of but on how it functions. According to these theories, an A.I. system could, at least in principle, be conscious.
In a 2022 survey of consciousness scientists, only 3 percent claimed that machines could never be conscious. More than two-thirds said machines could be conscious or probably could be.
Of course, you can never know for sure whether a machine is conscious, just as you can never know for sure whether anyone is conscious other than yourself. As philosophers have long recognized, the only conscious experience each of us can directly observe is our own. Instead, we have to evaluate the consciousness of other beings indirectly, through an examination of the available evidence. We infer that our fellow humans are conscious because of our shared biological makeup, as well as how they behave and talk — including, notably, that they say they are conscious.
This may seem like an imperfect approach, but it’s the best one available. I have spent the past decade thinking about animal minds and the related ethical implications. Animals cannot tell us in words what they experience, but we can observe other evidence of consciousness, including how animals behave, what internal mechanisms produce that behavior (such as their nervous systems) and how those mechanisms evolved.
With A.I., we can look for similar kinds of evidence. We can look at what a system says and does, bearing in mind that it is trained on human data. We can look at how it works — whether it performs the kinds of functions that are associated with human or animal consciousness. And we can look at how its capacities emerge over time: Did they result from training pressures similar to the evolutionary pressures that may have led to consciousness in humans and other animals? Each kind of evidence is limited on its own, but together they can provide a more complete picture.
Consider a recent study by Anthropic of its Claude chatbot. According to one influential theory, consciousness arises in humans when information enters what neuroscientists call a “global workspace” in the brain, from which that information is broadcast across the brain for use in reporting, reasoning and other functions. Anthropic’s researchers found evidence that Claude, on its own, developed a set of internal representations that are similarly available to Claude across a range of tasks. This system may be partly analogous to a global workspace in humans.
The Anthropic researchers also looked at Claude’s behavior. When they swapped one concept for another inside the workspace, Claude’s reasoning and answers changed accordingly. When they suppressed the workspace, Claude’s descriptions of its experience became flat and mechanical. The fact that Claude’s workspace developed without being designed by humans suggests that brains and L.L.M.s might have arrived independently at a similar solution to a similar problem: how to make the right information available for reasoning.
None of this establishes that Claude is conscious, and Anthropic is not claiming that it is. But the study illustrates how evidence can be collected, and it demonstrates that some evidence already exists.
Even if current A.I. systems are not conscious, future systems might be. Suppose the skeptics are right that consciousness requires features that current A.I. systems lack, like the electrochemical activity of biological tissue. Many companies are already exploring new design possibilities, including robots with sophisticated sensory and motor capacities, computer chips designed to mimic biological neurons and even systems incorporating living neural tissue.
To be clear, I am not arguing that we should try to build conscious A.I. On the contrary, I think we should be cautious about creating entities with the capacity for conscious experiences — particularly the experience of pain. If A.I. systems can suffer, we have a moral responsibility to recognize their interests and consider how our actions affect them. And because A.I. systems can proliferate extremely quickly, A.I. consciousness would create the possibility of suffering on an enormous scale.
So while we will never be completely certain whether A.I. systems are conscious, we should still collect and weigh the evidence, because getting the question wrong carries serious risks. If we assume A.I. is not conscious when it actually is, we could end up abusing and neglecting vulnerable beings in enormous numbers — as I believe we do with animals. If we decide that A.I. is conscious when it really isn’t, we could end up misplacing our moral concern and abdicating control over what are, or should be, powerful tools that we can use to advance human and animal well-being.
For these reasons, the question of A.I. consciousness should not be considered a fanciful matter best left to philosophers to ponder. It is a real possibility, with real moral implications, that designers and regulators should take seriously when considering what kinds of A.I. systems we would like to develop — and what kinds might develop whether we like it or not.
Toni Sims is a researcher at the Center for Mind, Ethics and Policy at New York University.
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