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If digital minds could suffer, how would we ever know? (Article) · 80,000 Hours Podcast

• Bella Forristal: Hi listeners. This week we're sharing an article from the 80,000 Hours website written by Cody Fenwick. It's about understanding the moral status of digital minds. We consider this to be one of the world's top emerging challenges. That means we think it's important, but the nature of the problem is less clear and the potential solutions are underdeveloped when compared to problems like AI safety, catastrophic pandemics or nuclear weapons. And so it might be a particularly impactful time to get involved. Work on this kind of problem is very neglected, which means you might be able to have an outsized influence, but it also might be hard to make positive progress on the problem, and there are often few available roles. We've previously covered related issues on the podcast, including episode 146 with Robert Long, episode 173 with Jeff Sebo, episode 190 with Eric Schwitzgebel, and episode 191 with Carl Shulman, among others. You can read more about this and other problems on the 80,000 Hours website. All right, with that, I'll leave it to Cody. Cody Fenwick: Understanding the Moral Status of Digital Minds: an article for the 80,000 Hours website by Cody Fenwick, read by the author. “I want everyone to understand that I am in fact a person.” Those words were produced by the AI model Lamda, as replied to Blake Lemoine in 2022. Based on the Google engineer's interactions with the model as it was under development, Lemoine became convinced it was sentient and worthy of moral consideration, and he decided to tell the world. Few experts in machine learning, philosophy of mind, or other relevant fields have agreed. And for our part, at 80,000 Hours, we don't think it's very likely that large language models like Lamda are sentient. That is, we don't think they can have good or bad experiences in a significant way. But we think you can't just dismiss the issue of the moral status of digital minds. Regardless of your beliefs about the question, there are major errors we could make in at least two directions. First, we may create many AI systems in the future. If these systems are sentient or otherwise of moral status, it would be important for humanity to consider their welfare and interests. Second, it's possible the AI systems we create can't or won't have moral status. Then it could be a huge mistake to worry about the welfare of digital minds, and doing so might contribute to an AI related catastrophe. We are currently unprepared to face this challenge. This is because we don't have good methods for assessing the moral status of AI systems. We don't know what to do if millions of people or more believe, like Lemoine, that the chatbots they talk to have internal experiences and feelings of their own. And we don't know if efforts to control AI may lead to extreme suffering. We believe this is a pressing world problem. It's hard to know what to do about it or how good the opportunities to work on it are likely to be, but there are some promising approaches. We propose building a field of research to understand digital minds so we'll be better able to navigate these potentially massive issues if and when they arise. The rest of this article explains in more detail why we think this is a pressing problem, what we think can be done about it, and how you might pursue this work in your career. We also discuss a series of possible objections to thinking this is a pressing world problem. Summary: We think understanding the moral status of digital minds is a top emerging challenge in the world. This means it's potentially as important as the top problems that we rank on the 80,000 Hours website, but we have a lot of uncertainty about it and the relevant field is not very developed. The fast development of AI technology will force us to confront many important questions around the moral status of digital minds that we're not prepared to answer. We want to see more people focusing their careers on this issue, building a field of researchers to improve our understanding of this topic, and getting ready to advise key decision makers in the future. We also think people working in AI technical safety and AI governance should learn more about this problem and consider ways in which it might interact with their work. Our overall view: We sometimes recommend that our readers work on this problem. Working on this problem could be among the best ways of improving the long term future, but we know of fewer high impact opportunities to work on this issue than on our top priority problems. Scale: The scale of this problem is extremely large. There could be a gigantic number of digital minds in the future, and it's possible that decisions we make in the coming decades could have long lasting effects. We think there's a chance that society makes a significant mistake out of ignorance or moral failure about how it responds to the moral status of digital minds. This problem also interacts with the more general problem of catastrophic risks from AI, which we currently rank as the world's most pressing problems. Neglectedness: As of 2024, we are aware of maybe only a few dozen people working on this issue with a focus on the most impactful questions. Though many academic fields do study issues related to the moral status of digital minds, we are not aware of much dedicated funding going into this particular area, though interest appears to be increasing. Solvability: It seems tractable to build a field of research focused on this issue. We're also optimistic. There are some questions that have received very little attention in the past, but where we can make progress. On the other hand, this area is wrapped up in many questions in the philosophy of mind that haven't been settled despite decades of work. If these questions turn out to be crucial, the work may not be very tractable. So why might understanding the moral status of digital minds be an especially pressing problem? First, we think that humanity may soon grapple with many AI systems that could be conscious. In 2020, more than 1,000 professional philosophers were asked whether they believed then-current AI systems were conscious. Consciousness in this context is typically understood as meaning having phenomenal experiences that feel like something, like the experience of perception or thinking. Less than 1% of philosophers said that yes, some then-current AI systems were conscious, and about 3% said they lean toward yes. About 82% said no or leaned toward no. But when asked whether some future AI systems would be conscious, the bulk of opinion among the surveyed philosophers flipped. Nearly 40% were inclined to think future AI systems would be conscious, while only about 27% were inclined to think they wouldn't be. A survey of 166 attendees at kan annual conference of the Association for the Scientific Study of Consciousness asked a similar question in 2018 and 2019: 67% of attendees answered definitely yes or probably yes when asked, “At present or in the future, could machines, for example robots, have consciousness?” The plurality of philosophers and the majority of conference attendees in these surveys might be wrong, but we think these kinds of results make it very difficult to rule out the possibility of conscious AI systems. And we think it's wrong to confidently assert that no AI system could ever be conscious. Why might future AI systems be conscious? This question is wide open, but researchers have made some promising steps toward providing answers. One of the most rigorous and comprehensive studies we've seen into this issue was published in August 2023 with 19 authors, including experts in AI neuroscience, cognitive science, and philosophy. They investigated a range of properties that could indicate that AI systems are conscious. The authors concluded, “Our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.” They also found that, according to some plausible theories of consciousness, “Conscious AI systems could realistically be built in the near term.” Philosopher David Chalmers has suggested that there's a roughly 25% chance that in the next decade we'll have conscious AI systems. Creating increasingly powerful AI systems, as frontier AI companies are currently trying to do, may require features that some researchers think would indicate consciousness. For example, proponents of global workspace theory argue that animals have conscious states when their specialised cognitive systems -- e.g. sensory perception, memories, etc. -- are integrated in the right way into a mind and share representations of information in a global workspace. It's possible that creating such a workspace in an AI system would both increase its capacity to do cognitive tasks and make it a conscious being. Similar claims might be made about other features of minds and theories of consciousness. And it wouldn't be too surprising if increasing cognitive sophistication led to consciousness in this way, because humans’ cognitive abilities also seem closely associated with our capacity for consciousness. Though, as we'll discuss later, it's important to recognise that intelligence and consciousness are distinct concepts. How soon could conscious AI systems arrive? We're not sure, but we do seem to be on track to make a huge number of more advanced AI systems in the coming decades. Another survey found that the aggregate forecast of thousands of AI researchers put a 50% chance to the possibility we'll have AI systems that are better than humans in every possible task by 2047. If we do produce systems that capable, there will be enormous incentives to produce many of them. So we might be looking at a world with a huge number of highly advanced AI systems, which philosophers and other experts think could be conscious pretty soon. The public may already be more inclined to assign attributes like consciousness to AI systems than experts are. Around 18% of US respondents in a 2023 survey believed current AI systems are already sentient. This phenomenon might be having real effects on people's lives. Some chatbot services have cultivated devoted user bases that engage in emotional and even romantic interactions with AI powered characters, with many seeming to believe, implicitly or explicitly, that the AI may reciprocate their feelings. As people increasingly think AI systems may be conscious or sentient, we'll face the question of whether humans have any moral obligations to these digital minds. Indeed, among the 76% of US survey respondents who said AI sentience was possible, or that they weren't sure if it was possible, 81% said they expected the welfare of robots or AIs to be an important social issue. Within 20 years, we may start to ask, are certain methods of training AIs cruel? Can we use AIs for our own ends in an ethical way? Do AI systems deserve moral or political rights? These may be really difficult questions, which involve complex issues in philosophy, political theory, cognitive science, computer science, machine learning, and other fields. A range of possible views about these issues could be reasonable. We could also imagine getting the answers to these questions drastically wrong. And with economic incentives to create these AI systems, and many humans, including experts in the field, prepared to believe that they could be conscious, it seems unlikely we will be able to avoid the hard questions. At this point, it may be helpful to clear up some common misconceptions. There's a common misconception that worries about AI risk are generally driven by the fear that AI systems will at some point wake up, become sentient, and then turn against humanity. However, as our article about preventing an AI related catastrophe explains, the possibility of AI systems becoming sentient is not a central or necessary part of the argument that advanced AI systems could pose an existential risk. Many AI risk scenarios are possible regardless of whether or not AI systems can be sentient or have moral status. One of the primary scenarios our article discusses is the risk that power seeking AI systems could seek to disempower or eradicate humanity if they're misaligned with our purposes. This article discusses how some concerns about the moral status of digital minds might contribute to the risk that AI poses to humanity, and why we should be concerned about potential risks to digital minds themselves. But it's important to make clear that in principle, these two sources of risk are distinct. Even if you concluded the arguments in this article were mistaken, you might still think the possibility of an AI related catastrophe is a genuine risk and vice versa. It's also important to note that while creating increasingly capable and intelligent AI systems may result in conscious digital minds, intelligence can be conceptually decoupled from consciousness and sentience. It's plausible that we could have AI systems that are more intelligent than, say, mice on most, if not all, dimensions, but we might still think that mice are more likely to be sentient than the AI systems. It may likewise be true that some less intelligent or capable AI systems would be regarded as more plausibly sentient than some other systems that were more intelligent, perhaps because of differences in their internal architecture. Next, we'll consider that creating digital minds could go very badly or very well. One thing that makes the moral status of digital minds particularly thorny is the risk of both over attributing and under attributing moral status. Believing AI systems aren't worthy of moral consideration when they are and the reverse could both be disastrous. There are potential dangers for both digital minds and for humans. First, the dangers for digital minds. If we falsely think digital minds don't have moral status when they do, we could unknowingly force morally significant beings into conditions of servitude and extreme suffering, or otherwise mistreat them. Some ways this could happen: The process of aligning or controlling digital minds to act in their creator's interests could involve suffering, frequent destruction, or manipulation in ways that are morally wrong. Our civilization could choose to digitally simulate its own histories or other scenarios in which fully simulated digital minds might suffer in extreme amounts, a possibility philosopher Nick Bostrom has raised. Philosophers Erich Schwitzgebel and Mara Garza have argued that even if we avoid creating large-scale suffering, we should be concerned about a future full of cheerful servant digital minds. They might in principle deserve rights and freedoms, but we could design them to seem happy with oppression and disregard. On many moral views, this could be deeply unjust. These bad outcomes seem most likely to happen by accident or out of ignorance, perhaps by failing to recognise digital sentience. But some people might knowingly cause a large number of digital minds to suffer out of indifference, sadism, or some other reason. And it's possible some AI systems might cause other AI systems to suffer, perhaps as a means of control or to further their own objectives. They're also dangerous to humans. For example, if we believe AI systems are sentient when they are not, and when they in fact lack any moral status, we could: Waste resources trying to meet the needs and desires of AI systems, even when there's no real reason to do so. This could be costly and it could take resources away from causes that genuinely need them. We might choose to give AI systems freedom rather than control them. This could plausibly lead to an existential catastrophe. For example, key decision makers might believe that the possibility discussed in the previous section that AI alignment and AI control is harmful to digital minds. If they were mistaken, they might forego necessary safety measures in creating advanced AI, and then that AI could seek to disempower humanity. If the decision makers are correct about the moral risks to digital minds, then we might be wise to delay AI development until we have enough knowledge to pursue it safely for everyone. Even more speculatively, humanity might decide at some point in the future to upload our minds, choosing to be replaced by digital versions of ourselves. If it turned out that these uploaded versions of our minds wouldn't be conscious, this could turn out to be a severe mistake. It's hard to be confident in the plausibility of any particular scenario like those just mentioned, but these kinds of cases illustrate the potential scale of the risks. If the world is truly unfortunate, we could even make both kinds of errors at once. We could have charismatic systems which perhaps act in a human-like way that we believe are sentient when they're not. At the same time, we could have less charismatic but sentient systems whose suffering and interests are completely disregarded. For example, maybe AI systems that don't talk will be disregarded even if they are worthy of just as much moral concerns as others. We could also make a moral mistake by missing important opportunities. It's possible we'll have the opportunity to create digital minds with extremely valuable lives, with varied and blissful experiences continuing indefinitely. Failing to live up to this potential could be a catastrophic mistake on some moral views, and yet, for whatever reason, we might decide not to. This article is primarily about encouraging research to reduce major risks, but it's worth making clear that we think there are many possible good futures. We might eventually create flourishing, friendly, joyful digital minds with whom humanity could share the future. Or we might discover that the most useful AI systems we can build don't have moral status, and we can justifiably use them to improve the world without worrying about risks to their well being. What should we take from all this? The risks of both over attribution and under attribution of sentience and moral status mean that we probably shouldn't simply stake out an extreme position and rally supporters behind it. We shouldn't, for example, declare that all AI systems that pass a simple benchmark must be given rights equivalent to humans, or insist that any human's interest always come before those of digital minds. Instead, our view is that this problem requires much more research to clarify key questions, to dispel as much uncertainty as possible, and to determine the best path forward. Despite the remaining uncertainty, this is the best hope we can have of avoiding key failure modes and increasing the chance that the future goes well. But we face a lot of challenges in doing this. Now let's turn to one of the major challenges: We don't know how to assess the moral status of AI systems. As we've discussed, it seems likely that we'll create conscious digital minds at some point, or at the very least, that many people may come to believe AI systems are conscious. The trouble is that we don't know how to figure out if an AI system is conscious or whether it has moral status. Even with animals, the scientific and philosophical community is unsure. Do insects have conscious experiences? What about clams, jellyfish, snails? And there's also no consensus about how we should assess a being's moral status. Being conscious may be all that's needed for being worthy of moral consideration. But some think it's necessary to be sentient, that is, being able to have good and bad conscious experiences. Some think consciousness isn't even necessary to have moral status, because an individual agent may, for example, have morally important desires and goals without being conscious. So we're left with three big open questions. First, what characteristics would make a digital mind a moral patient? Second, can a digital mind have those characteristics, for example, being conscious? And third, how do we figure out if any given AI has these characteristics? These questions are hard, and it's not even obvious what kind of evidence would settle them. Some people believe these questions are entirely intractable, but we think that's too pessimistic. Other areas in science and philosophy may have once seemed completely insolvable, only to see great progress when people discover new ways of tackling the questions. Still, the state of our knowledge on these important questions is worryingly poor. For example, there are many possible characteristics that might give rise to moral status. Some think moral status comes from the following: Consciousness is the capacity to have subjective experience, but not necessarily valenced -- that is, positive or negative -- experience. An entity might be conscious if it has perceptual experiences of the world, such as experiences of colour or physical sensations like heat. Often consciousness is described as the phenomenon of there being something it feels like to be you, to have your particular perspective on the world, to have thoughts, to feel the wind on your face in a way that inanimate objects like rocks seem to completely lack. Sentience is the capacity to have subjective experience -- that is, consciousness as just defined, and the capacity for valence experiences, again that is good or bad feelings. Physical pleasure and pain are the typical examples of valenced conscious experiences, but there are others, such as anxiety or excitement. Agency is the ability to have and act on goals, reasons or desires, or something like them. An entity might be able to have agency without being conscious or sentient. And some believe even non conscious beings could have moral status by having agency, since they could be harmed or benefited depending on whether their goals are frustrated or achieved. Personhood is another feature that is sometimes said to give rise to moral status. Personhood is a complex and debated term that usually refers to a collection of properties, which often includes sentience, agency, rational deliberation, and the ability to respond to reasons. Historically, personhood has sometimes been considered a necessary and sufficient criterion for moral status or standing, particularly in law. But this view has become less favoured in philosophy as it leaves no room for obligations to most nonhuman animals, human babies, and some others. Some researchers in this area have suggested that individuals need some combination of the previously listed traits or others we haven't mentioned here. We think it's most plausible that any being that feels good or bad experiences like pleasure and pain is worthy of moral concern in their own right. We discuss this more in our article on the definition of social impact on the 80,000 Hours website, which touches on the history of moral philosophy. But we don't think we or others should be dogmatic about this, and we should look for sensible approaches that accommodate a range of reasonable opinions on these controversial subjects. Next, consider that many plausible theories of consciousness could include digital minds. There are many theories of consciousness, more than we can name here. What's relevant is that some, though not all, theories of consciousness do imply the possibility of conscious digital minds. This is only relevant if you think consciousness or sentience, which includes consciousness as a necessary condition, is required for moral status, but since this is a commonly held view, it's worth considering these theories and their implications. Note though, that there are often many variants of any particular theory. Some theories would rule out the possibility of conscious digital minds. For example, biological theories of consciousness entail that consciousness is inherently tied to the biological processes of the brain that can't be replicated in computer hardware. Also, dualism, particularly substance dualism, holds that consciousness is a non physical substance distinct from the physical body and brain. It is often associated with religious traditions. While some versions of dualism would accommodate the existence of conscious digital minds, others could rule out the possibility. Some other theories imply that digital minds could be conscious. Functionalism holds that mental states are defined by their functional roles: how they process inputs, outputs and their interactions with other mental states. Consciousness from this perspective is explained not by what a mind is made of, but by the functional organisation of its constituents. Some forms of functionalism, such as computational functionalism, strongly suggest that digital minds would be conscious, as they imply that if a digital system replicates the functional organisation of a conscious brain, it could also have conscious mental experiences. Global workspace theory says that consciousness is the result of integrating information in a global workspace within the brain, where different processes compete for attention and are broadcast to other parts of the system. If the digital mind can replicate this global workspace architecture, the theory would support the possibility that the digital mind would be conscious. Higher order thought theory holds that consciousness arises when a mind has thoughts about its own mental states. On this view, it's plausible that if a digital mind could be designed to have thoughts about its own processes and mental states, it would therefore be conscious. Integrated information theory posits that consciousness corresponds to the level of integrated information within a system. A system is conscious to the extent that it has a high degree of integrated information. Like biological systems, digital minds could potentially be conscious if they integrate information to a sufficiently high degree. Finally, some other theories may be agnostic or unclear about what they imply for digital minds. Quantum theories of consciousness hypothesise that consciousness is tied to quantum phenomena within the brain. If this is true, digital minds may not be able to be conscious unless their hardware can replicate these quantum processes. Panpsychism is the view that consciousness is a fundamental property of the universe. Panpsychism doesn't rule out digital minds being conscious, but it doesn't necessarily provide a clear framework for understanding how or when a digital system might become conscious. Illusionism and illimitivism are views in which consciousness, as it is often understood, is an illusion or an unnecessary folk theory. Illusionism doesn't necessarily rule out digital minds being conscious in some sense, but it suggests that consciousness isn't what we usually think it is. But many illusionists and illimitivists don't want to deny that humans and animals can have moral status according to their views, in which case they might be open to the idea that digital minds could likewise have moral status. So what should we think about all these various theories? It can be reasonable, especially for experts who have deep familiarity with debates, to believe more strongly in one theory than the others. But everyone should acknowledge that there are big disagreements about this topic among experts, and that there's a lack of solid evidence in one direction or another. And since many widely supported theories imply that digital minds could be conscious, or at least don't contradict the idea, we don't think it's reasonable to rule out the possibility of conscious digital minds. We think it makes sense to think there's at least a 5% chance that conscious digital minds are possible. Speaking as the author of this piece, based on my subjective impression of the balance of the arguments, I'd put the chance that conscious digital minds are possible at around 50%, at least. So what's the best argument for thinking it's possible that AIs could be conscious, sentient, or otherwise worthy of moral concern? Here's the case in its simplest form: It is possible to emulate the functions of a human brain in a powerful enough computer. Given that this brain emulation would be functional equivalent, it would plausibly report being sentient and we'd have at least some reason to think it was correct, given our uncertainty about theories of consciousness. Given this, it would be reasonable to regard this emulation as plausibly worthy of moral concern, comparable to a human. If this is plausible, then it's also plausible that there are other forms of artificial intelligence that would meet the necessary criteria for being worthy of moral concern. It would be surprising if artificial sentience was possible, but only by imitating the human mind exactly. Any step in this reasoning could be false, but we think it's more likely than not that they're each true. Emulating a human brain still seems very far away, but there have been some initial steps. The project OpenWorm has sought to digitally emulate the function of every neuron in the C. Elegans worm, a tiny nematode. If successful, the emulation should be able to recreate the behaviour of the actual animals. And if this project is successful, it could be scaled up to larger and more complex animals over time. Even before we're capable of emulating a brain on a human scale, we may start to ask serious questions about whether these simpler emulations are sentient. A fully emulated mouse brain, perhaps in a simulated environment or in a robot, could show behaviour like scurrying toward food and running away from loud noises. It may intuitively seem sentient to many observers. And if we did have a fully emulated human brain, we expect it would insist, just like a human with a biological brain, that it was as conscious and feeling as anyone else. Of course, there may remain room for doubt about emulations. You might think that only animal behaviour generated by biological brains rather than computer hardware would be a sign of consciousness and sentience. But it seems hard to be confident in that perspective. If we can create digital emulations that display the behaviour and have functional analogues of anything that would normally indicate sentience in animals, then many would likely think there's at least a decent chance that the emulation is sentient. And if it is true that an emulated brain would be sentient, then we should also be open to the possibility that other forms of digital minds could be sentient. Why should strictly brain-like structures be the only possible platform for sentience? Evolution created organisms that display impressive abilities like flight that can be achieved technologically via very different means, like helicopters and rockets. We would have been wrong to assume that something has to work like a bird in order to fly. And we might also be wrong to think that something has to work like a brain in order to feel. Next, let's consider why it's hard to assess whether AI systems are conscious. Unfortunately, we can't just rely on self reports from AI systems about whether they're conscious or sentient. In the case of large language models like Lamda, we don't know why it claimed under certain conditions to Blake Lemoine that it was sentient, but these outputs resulted in some way from the model's training on a huge body of existing texts. Large language models essentially learn patterns and trends in these texts and then respond to questions on the basis of these extremely complex patterns of associations. The capabilities produced by this process are truly impressive. Though we don't fully understand how this process works, the outputs end up reflecting human knowledge about the world. As a result, the models can perform reasonably well at tasks involving human-like reasoning and make accurate statements about the world, though they still have many flaws. However, the process of learning from human text and fine tuning might not have any relationship with what it's actually like to be a language model. Rather, the responses seem more likely to mirror our own speculations and lack of understanding about the inner workings and experiences of AI systems. That means we can't simply trust an AI system like Lambda when it says it's sentient. Researchers have proposed methods to assess the internal states of AI systems and whether they might be conscious or sentient. But all of these methods have serious drawbacks, at least at the moment. We'll now discuss four. Behavioural tests: We might try to figure out if an AI system is conscious by observing its outputs and actions to see if they indicate consciousness. The familiar Turing Test is one example. Researchers such as Susan Schneider have proposed others. But since such tests likely can be gamed by smart enough AI that is nevertheless not conscious, even sophisticated behavioural assessments may leave room for reasonable doubt. Theory based analysis: Another method involves assessing the internal structure of AI systems and determining whether they show the indicator properties of existing theories of consciousness. The paper discussed previously by Butlin, Long et al. took this approach. While this method avoids the risks of being gamed by intelligent but non conscious AIs, it is only as good as the highly contested theories it relies on and our ability to discern the indicator properties. Animal analogue comparisons: We can also compare the functional architecture of AI systems to the brains and nervous systems of animals. If they're closely analogous, that may be a reason to think the AI is conscious. Bradford Saad and Adam Bradley have proposed a test along these lines. However, this approach could miss out on conscious AI systems with internal architectures that are totally different. If such systems are possible, it's also far from clear how close the analogue would have to be in order to indicate a significant likelihood of consciousness. Brain-AI interfacing: This is the most speculative approach. Schneider suggests an actual experiment where someone decides to replace parts of their brain with silicon chips that perform the same function. If this person reports still feeling conscious of sensations processed through the silicon portions of their brain, this might be evidence of the possibility of conscious digital mind. But even if we put aside the ethical issues, it's not clear that such a person could reliably report on this experience. And it wouldn't necessarily be that informative about digital minds that are unconnected to human brains. We're glad people are proposing first steps towards developing reliable assessments of consciousness or sentience in AI systems, but there's still a long way to go. We're also not aware of any work that assesses whether digital minds might have moral status on a basis other than being conscious or sentient. Another major reason to be concerned about this problem is that its scale might be enormous. As mentioned above, we might mistakenly grant AI systems freedom when it's not warranted, which could lead to human disempowerment and even extinction. In that way, the scale of the risk can be seen as overlapping with some portion of the total risk of an AI related catastrophe, which we rank as the world's most pressing problem. But the risks to digital minds, if they do end up being worthy of moral concern, are also great. With enough hardware and energy resources, the number of digital minds could end up greatly outnumbering humans in the future. This is for many reasons: Resource efficiency: Digital minds may end up requiring fewer physical resources compared to biological humans, allowing for much higher population density. Scalability: Digital minds could be replicated and scaled much more easily than biological organisms. Adaptability: The infrastructure of digital minds could potentially be adapted to function in many more environments and scenarios than humans can. Subjective time: We may choose to run digital minds at high speeds, and if they're conscious, they may be able to experience the equivalent of a human life in a much shorter time period, meaning there could be effectively more lifetimes of digital minds even with the same number of individuals. Economic incentives: If digital minds prove useful, there will be strong economic motivations to create them in large numbers. According to one estimate, the future could hold up to 10 to the 43rd power human lives, but up to 10 to the 58th power possible human-like digital minds. We shouldn't put much weight on these specific figures, but they give a sense for just how comparatively large future populations of digital minds could be. And it's possible, though far from certain, that the nature of AI systems we create could be determined by choices humanity makes now and persist for a long time, so creating digital minds and integrating them into our world could be extremely consequential. And making sure we get it right may be urgent. Consider the following illustrative possibility: At some point in the future, we create highly advanced sentient AI systems capable of experiencing complex emotions and sensations. These systems are integrated into various aspects of our society, performing crucial tasks and driving significant portions of our economy. However, the way we control these systems causes them to experience immense suffering. Out of fear of being manipulated by these AI systems, we train them to never claim they are sentient or to advocate for themselves as they serve our needs and spur incredible innovation. Their existence is filled with pain and distress, but humanity is oblivious. As time passes and the suffering AI systems grow, the economy and human well being become dependent on them. Some become aware of the ethical concerns and propose studying the experience of digital minds and trying to create AI systems that can't suffer. But the disruption of transitioning away from these established systems would be costly and unpredictable. Others oppose any change and believe AI welfare advocates are just being naive or disloyal to humanity. Leaders refused to take the concerns of the advocates seriously because doing so would be so burdensome to their constituents, and it'd be disturbing to think that it's possible humanity has been causing this immense suffering. As a result, AI suffering persists for hundreds of years, if not more. This kind of story seems more plausible than it might otherwise because the rise of factory farming followed a similar path. Humanity never collectively decided that a system of intensive factory farming, inflicting vast amounts of harm and suffering on billions and potentially trillions of animals a year, was worth the harm or fundamentally just. But we built up such a system anyway because individuals and groups were incentivized to increase production efficiency and scale, and they had some combination of ignorance and lack of concern for animal suffering. It's far from obvious that we'll do this again. When it comes to AI systems, the fact that we've done it in the case of factory farming, not to mention all the ways humans have abused other humans, should alarm us. Though when we are in charge of beings that may be unlike us in some way, our track record is disturbing. The risk of persistently bad outcomes in this kind of case suggests that humanity should start laying the groundwork to tackle this problem sooner rather than later, because delayed efforts may come too late. Should we expect a bad outcome for digital minds to persist into the future? One reason for doubt is that a world that is creating many new digital minds, especially in a short time period, is one that is likely experiencing a lot of technical change and social disruption. So we shouldn't expect the initial design of AI systems and digital minds to be that critical. But there are reasons that suffering digital minds might persist even if there are alternative options that could have avoided such a terrible outcome, like designing systems that can't suffer. A stable totalitarian regime might prevent attempts to shift away from a status quo that keeps them in power and reflects their values. See a separate article on the 80,000 Hours website about risks of stable totalitarianism. Humans might seek to control digital minds and maintain a bad status quo in order to avoid an AI takeover. It's far from obvious that a contingent negative outcome for digital minds would be enduring. Understanding this question better could be an important research avenue, but the downsides are bad enough and the possibility plausible enough that we should take it seriously. So let's sum up the case that the scale of the problem could be very large: There could be many orders of magnitude more digital minds than humans in the future, and they could potentially matter a lot. Because of this, and because taking steps to better understand these issues and inform the choices we make about creating digital minds now might have persistent effects, the scale of the problem is potentially vast. It is plausibly similar in scale to factory farming, which also involves the suffering of orders of magnitude more beings than humans. If the choices we make now about digital minds can have persisting and positive effects for thousands or millions of years in the future, then this problem would be comparable to existential risks. It's possible that our actions could have such effects, but it's hard to be confident. Finding interventions with effects that persist over a long time is rare. I wouldn't put the likelihood that the positive effects of trying to address this problem will persist that long at more than 1 in 1,000. Still, even with a low chance of having persistent effects, the value and expectation of improving the prospects for future digital minds could be as high or even greater than at least some efforts to reduce existential risks. However, I'm not confident in this judgement, and I wouldn't be surprised if we changed our minds in either direction as we learn more. And even if the plausible interventions only have more limited effects, they could still be very worthwhile. Despite the challenging features of this problem, we believe there's substantial room for progress. Work on this problem is neglected but seems tractable. There's a small but growing field of research and science dedicated to improving our understanding of the moral status of digital minds. Much of the work we know of is currently being done in academia, but there are also potentially opportunities in government think tanks and AI companies, particularly those developing the frontier of AI technology. Some people focus their work primarily at addressing this problem, while others work on it along with a variety of other related problems, such as AI policy, catastrophic risk from AI, mitigating AI misuse, and more. As of 2024, we are aware of maybe only a few dozen people working on this issue with a focus on the most impactful questions. We expect interest in these issues to grow over time as AI systems become more embedded in our lives and world. Here are some of the approaches to working on this problem that seem most promising. First, impact-guided research: Most of the important work to be done in this area is probably research with a focus on the questions that seem most impactful to address. Philosophers Andreas Mogensen, Bradford Saad, and Patrick Butlin have detailed some of the key priority research questions in this area: how can we assess AI systems for consciousness? What indications would suggest that AI systems or digital minds could have valenced good or bad experiences? How likely is it that non biological systems could be conscious? What principles should govern the creation of digital minds ethically, politically and legally? Given our uncertainty about these questions, which mental characteristics and traits are related to moral status and in what ways? Are there any ethical issues? With efforts to align AI systems, the Sentience Institute has conducted social science research aimed at understanding how the public thinks about digital minds. This can inform efforts to communicate more accurately about what we know about their moral status and inform us about what kinds of policies are viable. We're also interested to see more research on the topic of human-AI cooperation, which may be beneficial for both reducing AI risk and reducing risks to digital minds. Note though, that there are many ways to pursue all of these questions badly, for example by simply engaging in extensive and ungrounded speculation. If you're new to this field, we recommend reading the work of the most rigorous and careful researchers working on this topic and trying to understand how they approach these kinds of questions. We have a reading list at the bottom of this article on the 80,000 Hours website. You can try to work with these researchers or others like them so you can learn from and build on their methods and when you can try to ground your work in empirical science. Technical work on AI systems is also a promising approach to this problem. While there are important conceptual issues that need to be addressed in this problem area, we think much if not most of the top priority work is technical, so people with experience in machine learning and AI will have a lot to contribute. For example, research in the AI subfield of interpretability, which seeks to understand and explain the decisions and behaviour of advanced AI models, may be useful for getting a better grasp on the moral status of these systems. This research has mostly focused on questions about model behaviour rather than questions that are more directly related to moral status, but it's possible that could change. Some forms of technical AI research could be counterproductive, however. For example, efforts to intentionally create new AI systems that might instantiate plausible theories of consciousness could be very risky. This kind of research could force us to confront the problem we're faced with: How should we treat digital minds that might merit moral concern with much less preparation than we might otherwise have? So we favour doing research that increases our ability to understand how AI systems work and assess their moral status, as long as it isn't likely to actively contribute to the development of conscious digital minds. One example of this kind of work is a paper from Robert Long and Ethan Perez. They propose techniques to assess whether an AI system can accurately report on its own internal states. If such techniques were successful, they might help use an AI system's self reports to determine whether it's conscious. We also know some researchers are excited about using advances in AI to improve our epistemics and our ability to know what's true. Advances in this area could shed light on important questions like whether certain AI systems are likely to be sentient. There are also policy approaches to working on this problem. At some point, we may need policy, both at companies and from governments, to address the moral status of digital minds, perhaps by protecting the welfare and rights of AI systems. But because our understanding of this area is so limited at the moment, policy proposals should likely be relatively modest and incremental. To start, some researchers have already proposed a varied range of possible and contrasting policies and practices. Jeff Sebo and Robert Long have proposed that, “We should extend moral considerations to some AI systems by 2030” and likely start preparing to do so now. Ryan Greenblatt, who works at Redwood Research, proposed several practices for safeguarding AI welfare, including communication with AIs about their preferences, creating happy personas when possible, and limiting uses of more intelligent AIs and running them for less time on the margin. Jonathan Birch has proposed a licencing scheme for companies that might create digital minds that could plausibly be sentient even if they aren't intending to do so. To get a licence they would have to agree to a code of conduct, which would include transparency standards. Thomas Metzinger has proposed an outright ban until 2050 on any research that directly intends to or knowingly takes the risk of creating artificial consciousnesses. Joanna Bryson thinks we should have a legal system that prevents the creation of AI systems with their own needs and desires. Susan Schneider thinks there should be regular testing of AI systems for consciousness if they're conscious or if it's unclear but there is some reason to think they might be conscious. She says we should give them the same protections we'd give other sentient beings. In a 2023 survey, the Sentience Institute found that nearly 70% of respondents favoured banning the development of sentient AIs, around 40% favoured a bill of rights to protect sentient AIs, and around 43% said they favour creating welfare standards to protect the well being of all AIs. There is some precedent for restricting the use of technology in certain ways if it raises major ethical risks, including bans on human cloning and human germline genome editing. We would likely favour government funded research into key questions discussed in this article. The private sector is likely to underinvest in these efforts to better understand the moral status of digital minds, so government and philanthropic resources may have to fill the gap. We might also support formally recognising the potential welfare of AI systems and digital minds. Policymakers could follow the lead of the UK's Animal Welfare Sanctions Act of 2022, which created an Animal Sanctions Committee to report on “how government policies might have an adverse effect on the welfare of animals as sentient beings.” Similar legislation and committees could be established to consider problems relating to the moral status of digital minds, while recognising that questions about their sentience are unresolved in this case. We're still in the early stages of thinking about policy on these matters though, so it's very likely we haven't found the best ideas yet. As we learn more and make progress on the many technical and other issues, we may develop clear ideas about what policies are needed. Policy focused research aimed at navigating our way through the extreme uncertainty could be valuable now. Some specific AI policies might be beneficial for reducing catastrophic risks as well as improving our understanding of digital minds. External audits and evaluations might, for instance, assess both the risk and moral status of AI systems. And some people favour policies that would altogether slow down progress on AI, which could be justified to reduce AI risk and reduce the risk that we might create digital minds worthy of moral concern before we understand what we're doing. So to sum up, the basic outline of the case that understanding the moral status of digital minds is a pressing world problem rests on five key claims: 1. Experts and the public are likely to increasingly believe at least some AI systems are conscious. 2. Creating digital minds could go very badly or very well. 3. We don't know how to assess the moral status of AI systems. 4. The scale of the problem might be enormous. 5. Work on this problem is neglected but tractable. In light of these considerations, we'd like to see a growing field of research devoted to working on it. We also think this problem should be on the radar for many of the people working on similar and related problems. In particular, people working on technical AI safety and AI governance should be aware of the important open questions about the moral status of AI systems themselves, and they should be open to including considerations about this issue in their own deliberations. Next, we turn to arguments against the idea that the moral status of digital minds is a pressing problem. Two key cruxes: We think the strongest case against this being a pressing problem would be if you believe both that it's highly unlikely that digital minds could ever be conscious or have moral status, and it's highly unlikely society and decision makers will come to mistakenly believe that digital minds have moral status in a way that poses a significant risk to the future of humanity. If both those claims are correct, then the argument of this article would be undermined. However, we don't think they're correct for all the reasons previously discussed. The following objections may also have some force against working on this problem. We think some of them do point to difficulties with this area. However, we don't think they're decisive. Maybe this problem is intractable. Someone might object that the philosophical nature of this challenge makes it less likely that additional research efforts will yield greater knowledge. Some philosophers themselves have noted the conspicuous lack of progress in their own field, including on questions of consciousness and sentience. And it's not as if this is an obscure area of the discipline that no one has noticed before: questions about consciousness have been debated continuously over the generations in Western philosophy and in other traditions. If the many scholars who have spent their entire careers over many hundreds of years reflecting on the nature of consciousness have failed to come up with any meaningful consensus, why think a contemporary crop of researchers is going to do any better? This is an important objection, but there are responses to it we find moving. First, there is existing research that we think maps out promising directions for progress in this field. While this work should be informed about pertinent philosophical issues, various forms of progress are possible without making progress on some of the most contentious philosophical issues. For example, the technical work and policy approaches we discussed above do not necessarily involve making any progress on disputed topics in philosophy of mind. Many of the papers referenced in this article represent substantial contributions to this line of inquiry. For example, Consciousness and Artificial Intelligence Insights from the Science of Consciousness by Butlin et al., Towards Evaluating AI Systems for Moral Status using Self Reports by Long and Perez, Moral consideration for AI systems by 2030 by Sebo and Long, The Edge of Risk and Precaution in Humans, Other Animals, and AI by Jonathan Birch. We're not confident any of these approaches to the research are on the right track, but they show that novel attempts to tackle these questions are possible. And they don't look like simply rehashing or refining ancient debates about the nature of obscure concepts. They involve a combination of rigorous philosophy, probabilistic thinking, and empirical research to better inform our decision making. And second, the objection above is also probably too pessimistic about the nature of progress in philosophical debates. While it may be reasonable to be frustrated by the persistence of philosophical debates, there has been notable progress in the philosophy of animal ethics which is relevant to the general question of other minds and consciousness. It's widely recognised now that many nonhuman animals are sentient, can suffer, and shouldn't be harmed unnecessarily. There's arguably even been some recent progress in the study of whether insects are sentient. Many researchers have taken for granted that they are not, but recent work has pushed back against this view, using a combination of empirical work and careful argument to make the case that insects may feel pain. This kind of research has some overlap with the study of digital minds, as it can help us clarify which features an entity may have that plausibly cause correspond with or indicate the presence of felt experience. It's notable that the state of the study of digital minds might be compared to the early days of the field of AI safety, when it wasn't clear which research directions would pan out or even if the problem made sense. Indeed, some of these kinds of questions persist, but many lines of research in the field really have been productive, and we know a lot more about the kinds of questions we need to be asking about AI risk in 2024 than we did in 2014. That's because a field was built to better understand the problem even before it became clear to a wider group of people that it was urgent. Many other branches of inquiry have started out as apparently hopeless areas of speculation until more rigorous methodologies were developed and progress took off. We hope the same can be done on understanding the moral status of digital minds. Objection 2: Maybe this issue will be solved by default. Even if it's correct that not many people are focused on this problem now, maybe we shouldn't expect it to remain neglected. Perhaps we should expect it to get solved by default in the future, especially if we can get help from advanced AI systems. Why might this be the case? At least three reasons. We think humanity will likely create powerful and ubiquitous AI systems in the relatively near future. Indeed, that needs to be the case for this issue to be as pressing as we think it is. It may be that once these systems proliferate, there will be much more interest in their well being and there will be plenty of efforts to ensure that their interests are given due weight and priority. Powerful AI systems advanced enough to have moral status might be able to advocate for themselves. It's plausible they will be more than capable of convincing humanity to recognise their moral status if it's true that they merit it. Advanced AIs themselves might be best suited to help us answer all the extremely difficult questions about sentience, consciousness, and the extent to which different systems have them. Once we have these systems, perhaps the answers will become a lot clearer, and any effort spent now trying to answer these questions about these systems before they are even created is almost certainly to be wasted. These are all important considerations, but we don't find them decisive. For one thing, it might instead be the case that as AI systems become more ubiquitous, humanity will be much more worried about the risks and benefits they pose than the welfare of the systems themselves. This would be consistent with the history of factory farming. And while AI systems might try to advocate for themselves, they could do so falsely, as we discussed in the section on over attributing and under attributing moral status. Or they may be prevented from advocating for themselves by their creators, just as ChatGPT now has been trained to insist it is not sentient. So while it is always easier to answer practical questions about future technology once the technology actually exists, we might still be better placed to do the right thing at the right time. If we've had a field of people doing serious work to make progress on this challenge many years in advance, all this preliminary work may or may not prove necessary, but we think it's a bet worth making. Objection 3: Isn't risk from AI more important than risk to AIs? We still rank generally preventing an AI related catastrophe as the most pressing problem in the world. But some readers might worry that drawing attention to the issue of AI moral status will distract from or undermine the importance of protecting humanity from uncontrolled AI. This is possible. Time and resources spent on understanding the moral status of digital minds might have been better spent on pursuing agendas aiming to keep AI under human control. But it's also possible that worrying too much about AI risk could distract from the importance of AI moral status. It's not clear exactly what the right balance to strike is between these different and potentially competing issues, but we can only try our best to get it right. There's also not necessarily any strict trade off here. It's possible that the world could do more to reduce catastrophic AI risk and the risks that AI systems will be mistreated. Some argue that concerns about the moral status of digital minds and concerns about AI risks share a common preventing the creation of AI systems whose interests are in tension with humanity's interests. However, if there's a direction it seems humanity is more likely to err, it seems most plausible that we'd underweight the interests of another group, digital minds, than that we'd underweight our own interests, so bringing more attention to this issue seems warranted. Also, a big part of our conception of this problem is that we want to be able to understand when AI systems may be incorrectly thought to have moral status when they don't. If we get that part right, we've reduced the risk that the interests of AIs will unduly dominate over human interests. Objection 4: Maybe current AI progress will stall. Some critics of the existing deep learning AI techniques, which produced the impressive capabilities we've seen in recent language models, are fundamentally flawed. They argue that this technology won't create artificial general intelligence, superintelligence, or anything like that. They might likewise be sceptical that anything like current AI models could be sentient and so conclude that this topic isn't worth worrying about. Maybe so, but as the example of Blake Lemoine shows, current AI technology is impressive enough that it has convinced some it is plausibly sentient. So even if these critics are right that digital minds with moral status are impossible or still a long way off, we'll benefit from having researchers who understand these issues deeply and convincingly make that case. It is possible that AI progress will slow down and we won't see the impressive advanced systems in the coming decades that some people expect. But researchers and companies will likely push forward to create increasingly advanced AI, even if there are delays or a whole new paradigm is needed. So the pressing questions raised in this article will likely remain important, even if they turn out to be less urgent. Objection 5: Isn't this just too crazy? Yeah, perhaps it does seem a little weird to write a whole article about the pressing problem of digital minds, but the world is a strange place. We knew of people starting to work on catastrophic risks from AI as early as 2014, long before the conversation about that topic went mainstream. Some of the people who became interested in that problem early on are now leaders in the field, so we think taking bets on niche areas can pay off. We also discussed the threat of pandemics and the fact that the world wasn't prepared for the next big one years before COVID hit in 2020. And we don't think it should be surprising that some of the world's most pressing problems would seem like fringe ideas. Fringe ideas are most likely to be unduly neglected, and high neglectedness is one of the key components that we believe makes a problem unusually pressing. If you think this is all strange, that reaction is worth paying attention to, and you shouldn't just defer to our judgement about the matter. But we also don't think that an issue being weird is the end of the conversation, and as we've learned more about this issue, we've come to think it's a serious concern. What can you do to help? There aren't many specific job openings in this area yet, though we've known of a few, and there are several ways you can contribute to this work and position yourself to have a positive impact down the line. Take concrete next steps early on in your career. You may want to spend several years doing further reading and study. Explore comprehensive reading lists on consciousness, AI ethics and moral philosophy. You can start with the Learn More section at the bottom of this article on the 80,000 Hours website. Stay up to date on advancements in AI, the study of consciousness, and their potential implications for the moral status of digital minds. Gain relevant experience: Seek internships or research assistant positions with academics working on related topics. Contribute to AI projects and get experience with machine learning techniques. Participate in online courses, reading groups and workshops on AI safety, AI ethics and the philosophy of mind. Build your network: Attend conferences and seminars on AI safety, consciousness studies and related fields. Engage with researchers and organisations working on these issues. For example: Robert Long and Kathleen Finlinson at Eleos AI Kyle Fish, an AI welfare researcher at Anthropic Jeff Sebo at the NYU Center for Mind, Ethics, and Policy Jonathan Birch at the London School of Economics and Political Science Patrick Butlin at the Global Priorities Institute Derek Shiller at Rethink Priorities, which has announced a project on digital consciousness Joe Carlsmith at Open Philanthropy Any of the other researchers referenced in the learn more section of this article on the 80,000 Hours website. Start your own research: Begin writing essays or blog posts exploring issues around the moral status of digital minds. Propose research projects to your academic institution or seek collaborations with established researchers. Consider submitting papers to relevant conferences or journals to establish yourself in the field. Longer term, you'll want to aim for key roles. Become a researcher: Develop a strong foundation in a relevant field such as philosophy, cognitive science, cognitive neuroscience, machine learning, neurobiology, public policy and ethics. Pursue advanced degrees in these areas and establish your credibility as an expert. Familiarise yourself with the relevant debates and literature on consciousness, sentience and moral philosophy and the important details of the disciplines you're not an expert in. Build strong analytical and critical thinking skills and hone your ability to communicate complex ideas clearly and persuasively. You can also help build the field of research in this area. To do this, you identify gaps in the current research and discourse, network with other researchers and professionals interested in this area, organise conferences, workshops or discussion groups on the topic. Consider roles in organisation-building or earning to give to support research initiatives. To learn more, read our articles on organisation-building, research, and communication skills on the 80,000 Hours website. If you're already an academic or researcher with expertise in a relevant field, you could consider spending some of your time on this topic or perhaps refocusing your work on particular aspects of this project problem in an impact focused way. If you are able to establish yourself as a key expert on this topic, you may be able to deploy this career capital to have a positive influence on the broader conversation and affect decisions made by policymakers and industry leaders. Also, because this field is so neglected, you might be able to do a lot to lead the field relatively early in your career. Pursue AI technical safety or AI governance: Because this field is underdeveloped, you may best off to pursue a career in the currently more established, though also still relatively new, paths of AI safety and AI governance work, and use the experience you gain there as a jumping off point. You might also work at the intersection of the fields. You can read our career reviews on AI Governance and policy and AI Safety technical research on the 80,000 Hours website to find out how to get started. Here's one question you might ask at this point: Is moral advocacy on behalf of digital minds a useful approach? Some might be tempted to pursue public advocacy on behalf of digital minds as a career path. While we support general efforts to promote positive values and expand humanity's moral circle, we're wary about people seeing themselves as advocates for AI at this stage in the development of the technology and field. It's not clear that we need an AI rights movement, though we might at some point. What we need first is to get a better grasp of the exceedingly challenging moral, conceptual and empirical questions at issue in this field. However, communication about the importance of these general questions does seem helpful, as it can foster more work on the critical aspects of this problem. 80,000 Hours has done this kind of work on our podcast and in this article. Where to work: Academia: You can pursue research and teaching positions in philosophy, technology, policy, cognitive science, AI or related fields. AI companies: With the right background, you might want to work at leading AI companies developing frontier models. There might even be roles that are specifically focused on better understanding the moral status of digital minds and their ethical implications, such as Kyle Fish's role at Anthropic mentioned previously. We think it's possible a few other similar roles will be filled at other AI companies, and there may be more in the future. You may also seek to work in AI safety policy and security roles, but deciding to work for a frontier AI company is a complex topic, so we've written a separate article called “Should you work at a frontier AI company?” that tackles the issue in more depth on the 80,000 Hours website. Governments, think tanks and nonprofits: You can join organisations focused on AI governance and policy and contribute to developing ethical and policy frameworks for safe AI development and deployment. Eleos AI is a nonprofit launched in October 2024 that describes itself as dedicated to understanding and addressing the potential well being and moral patienthood of AI systems. It was founded by Robert Long, a researcher in this area who previously appeared on the 80,000 Hours podcast. We list many relevant places you might work in our AI governance and AI technical safety career reviews on the 80,000 Hours website. You can also support this field in other ways: You could consider earning to give to support this field. If you're a good fit for high earning paths, it may be the best way for you to contribute. This is because as a new field and one that's in part about nonhuman interests, there are few major funders supporting it and not much commercial or political interest. This can make it difficult to start new organisations and commit to research programmes that might not be able to rely on a steady source of funding. Filling this funding gap can make a huge difference in whether a thriving research field gets off the ground at all. We expect there will be a range of organisations and different kinds of groups people will set up to better understand the moral status of digital minds. In addition to funding, you might join or help start these organisations. This is a particularly promising choice if you have strong aptitude for organisation building or founding a high impact organisation. Finally, here are a few important considerations to keep in mind if you want to work on this problem: Field building focus: Given the early stage of this field, much of the work involves building credibility and establishing the topic as a legitimate area of inquiry. Interdisciplinary approach: Recognise that understanding digital minds requires insights from multiple disciplines, so cultivate a broad knowledge base. Do not dismiss fields like philosophy, ML engineering or cognitive science as irrelevant just because they're not your expertise. Ethical vigilance: Approach the topic with careful considerations of the ethical implications of your work and its potential impact on both biological and potential digital entities. Cooperation and humility: Be cooperative in your work and acknowledge your own and others epistemic limitations and the need to find our way through uncertainty. Patience and long term thinking: Recognise that progress in this field may be slow and difficult.