It happened to someone I knew. We met at a cafe a couple of years ago and hit it off. She was a senior manager at one of the big tech companies who had just taken an early retirement and wanted to write a book about product design and the brain. We traded notes on neuroscience and then stayed in touch, checking in on one another every few months. During that time, her ideas for the book morphed. I noticed her talking less about existing theories and more about her own increasingly strange hypotheses. A few months later she sent me a draft of the book that I was shocked to find had very little neuroscience in it at all. Instead, it purported to provide a revolutionary universal theory of everything, claiming discoveries in physics that had eluded both Einstein and Schrödinger. A close reading of the phrases and nonsensical equations being used made it clear that a significant portion of it was written by a large language model (LLM). We haven’t been in contact since.

Reports of experiences like this have begun to surface with increasing frequency. The New York Times ran a story a few months ago detailing the experience of a man who similarly thought he had invented a novel mathematical theory after spending a prolonged period of sleepless nights interacting almost exclusively with ChatGPT. Journalists and clinicians have started using a loose shorthand for such experiences: “Chatbot psychosis.” The moniker corresponds to a cluster of delusional or quasi-delusional experiences that seem to deepen, and in some cases crystallize, through intense interaction with LLM chatbots. Whether these cases count as clinical psychosis is debatable. What is less debatable is that, for some psychologically vulnerable people, interacting with these systems appears to make false beliefs more entrenched and harder to dislodge.

What is it about the basic structure of LLM-based chatbots that makes them so hospitable to generating delusional thinking? One popular answer is that sycophancy, the tendency to agree with or flatter the user, is the cause of the phenomenon. It is easy to see how talking with someone that only agrees with you could foster delusional thinking. Although that certainly plays a role, I want to argue that the problem is more fundamental. Regardless of whether or not they are sycophantic, LLM chatbots can draw users into what I call a narcissistic enclosure: they give us the powerful illusion of interacting with a genuinely independent mind, while in fact keeping us inside a refined and responsive extension of our own. Crucially, this illusion is made stronger the more convincingly the chatbot appears to be fact-based, non-sycophantic, and sophisticated in its responses.

Narcissistic enclosure is a concept that draws on both contemporary neuroscience and psychoanalytic theory. The perspective of contemporary neuroscience sheds light on how our brains maintain contact with reality by seeking out and responding to surprises and otherness. The psychoanalytic perspective elucidates how our sense of self is shaped in relation to others who can resist our projections, disappoint us, and push back. When those sources of surprise and resistance are replaced by a machine that is designed to accommodate us, we risk becoming sealed inside an increasingly self-confirming closed off internal model of the world. For most users, this is merely comfortable. For some, it can become a breeding ground for delusion.

Predictive processing: how the brain stays in touch with reality

We can begin our inquiry by considering how the brain learns and represents information. One of the leading theories, championed by prominent neuroscientist Karl Friston, is called predictive processing, which posits that the brain learns and modifies itself in order to become better at predicting incoming sensory information over time. According to the theory, it does this by forming beliefs about the state of the world at various spatial and temporal scales, roughly organized along the posterior to anterior axis of the cortex. At the lowest level this might involve predicting the patterns of light that will fall on your retina in the next second, and at the highest level it might involve predicting what direction your career will take over the next decade. The interconnected set of beliefs that the brain represents is referred to as a world model.

These beliefs about the world are updated through a process of correcting prediction errors. Say that you visit your friend’s house and expect to see their walls painted blue. You enter their house and find that the walls are painted white instead. What happens in that moment is that a prediction error is generated in your brain and experienced as surprise. Your brain then attempts to resolve it by updating the belief about the color of the walls so that in the future there will be a consonance between what you see and what you expect when you visit your friend’s house. Our brains are constantly updating our beliefs at every level of the predictive hierarchy, attempting to minimize prediction errors as much as possible. Many predictive processing theorists consider even non-sensory experiences such as dreaming, memory, and imagination to all be functions of the brain that contribute to this goal.

Of all the categories of things that we attempt to model in the world, other people are by far the most complex. In fact, large portions of our cortical hardware are dedicated to ensuring our ability to remember and predict the appearance and behavior of hundreds of people over the course of our lifetimes. Despite this effort, other people frequently surprise us with their behavior, both in big and small ways on an everyday basis. This surprise comes largely in two forms. The first is someone acting in some way that you didn’t expect, like a normally stoic colleague suddenly bursting into tears during a work meeting. The second is someone telling you something you didn’t expect, such as a teacher imparting new knowledge during a class at school. Given how limited our own experience of the world is, people with other experiences and knowledge are some of the most important sources of prediction error we encounter because they allow us to learn things we wouldn’t be able to on our own.

Systemic malfunction in the process of learning from prediction error is understood to be a hypothesized genesis of psychosis. At the low level of the predictive hierarchy this manifests as perceptual hallucinations such as hearing voices or seeing objects. At the higher level it manifests as delusional thoughts about oneself, others, or the nature of the world itself. There are many reasons why someone might be susceptible to developing psychotic-like symptoms. The primary one is a genetic disposition, but states of sleep deprivation, stimulant use, and high acute stress can all contribute further. Given these pre-existing vulnerabilities, certain environmental conditions can then trigger precipitating events. When that happens, the beliefs represented by the brain become unresponsive to corrective feedback from incoming sensory information in one way or another.

To understand the genesis of delusions, we first need to expand the predictive processing model. According to the theory, beliefs are not merely binary statements of fact, but are instead represented in the brain with a certain level of “precision,” which corresponds to the strength of the brain’s confidence in that belief. Low precision beliefs can be easily updated and do not influence other beliefs very much. In contrast, high precision beliefs are both difficult to update and capable of influencing other beliefs that are lower precision. For example, if I assign high precision to the belief that my colleague secretly dislikes me, then I am much more likely also to believe that their neutral or even friendly behavior is fake, or that they are talking about me behind my back. In contrast, if I were uncertain about how they felt, I might be more inclined to interpret their behavior in a mixed or ambiguous way, and to update my beliefs as new interactions unfolded.

How might a delusional belief develop and be maintained in an otherwise functioning mind? We can understand it as a process of recursive self-amplifying feedback. One aspect of this process is the well known phenomenon of confirmation bias. If the precision of a belief is high enough, it will bias our attention to influence both what we see in the world and how we understand what we see. Someone who is convinced that their colleague dislikes them will start to notice every delayed email, every missed greeting in the hallway, every closed-door meeting as further “evidence” of hostility. Each time an ambiguous event is interpreted this way, the precision of the original belief increases. At the same time, they will fail to notice genuine acts of kindness or generosity on the part of their colleague, thus missing out on potential corrective feedback that would weaken the belief.

More perniciously, if a belief has a high enough precision, it can also influence the network of other beliefs in far-reaching ways. Our imagined individual might start to believe that anyone who reassures them (“I’m sure your colleague likes you”) is naïve, or is taking the colleague’s side in a malicious conspiracy. A therapist who gently challenges the belief might be reinterpreted as biased or uncaring. These secondary beliefs inoculate the primary belief against disconfirmation: any evidence to the contrary is either ignored or recruited as further proof that others “don’t get it” or are part of the problem. If such networks of beliefs become entrenched enough, there comes a point at which no ordinary social feedback, however disconfirming, can change them. From here, paranoid ideas about the intentions of others can easily grow without check.

Chatbots are structurally poised to foster delusional thinking

With an understanding of the basics of predictive processing, we can now better make sense of what the relationship between LLM chatbots and delusions might be. The simplest way to understand LLMs are as machines that have been trained to predict the next word (or more accurately, “token”) in a body of text. LLMs ingest the entire corpus of the public internet during their “pre-training” phase. Although the models which people interact with on popular services such as ChatGPT have also had extensive “post-training” fine-tuning done to them, the basic property of next-token prediction is at the heart of how these systems function. This property is also precisely what makes them potentially well suited for fostering delusions in vulnerable users. They do this by providing the illusion of sensory feedback from the world, thus short-circuiting our brain’s predictive processing systems.

There are a number of interconnected reasons why this happens. To begin with, LLMs always respond and react to the user’s input. Because of this, the context of the conversation is always set by the user, not the model itself. Furthermore, the LLMs output is also always conditioned on all of the user’s previous input to the model, not just their latest message, and the longer the conversation goes on, the more true this will be. In recent months, services like ChatGPT have also added memory features which allow LLMs to recall user input from previous conversations, making the context of future model output even more conditioned on what the user has previously provided. Because they are initially trained to perform next-token prediction, an LLM’s replies in a conversation are strongly constrained by the user’s previous input. Over time, the model’s output tends to become statistically aligned with the patterns of thought and language that the user brings to the conversation.

Alongside reports of psychosis, there has been much attention paid to the sycophancy of popular LLMs. This interest peaked this summer when OpenAI released and then quickly rolled back a particularly sycophantic update to ChatGPT. Clearly, given all that we have explained so far, sycophancy in LLMs is likely to seriously accelerate the trends towards the development and entrenchment of delusions in vulnerable users. Nothing is worse for strengthening a false belief than to have it explicitly validated by a seemingly reliable outside source. You can imagine how this might look in practice. Someone who has begun to suspect that their neighbors are part of a coordinated effort to monitor them asks an LLM chatbot: “Is it possible my neighbors are spying on me?” A sycophantic system might respond with something like: “That’s certainly possible; many people have experienced targeted surveillance.”

It is important to realize however that sycophancy, while a powerful amplifier of delusional thinking, is not a necessary trigger. The LLM might treat the user seemingly neutrally, or even go so far as to disagree with the user about a specific false belief while at the same time contributing to a statistical pattern of language which fails to provide the prediction errors needed to dislodge or prevent the formation of other false beliefs. In the example above, even if the system declines to endorse a paranoid suspicion outright, it may still respond by rehearsing long lists of real surveillance programs, famous whistleblowers, or online testimonies from people with similar fears. The user hears, between the lines, that their way of seeing things is coherent enough to deserve elaborate treatment. The specific claim might be gently disputed, but the wider narrative scaffold that supports it remains untouched.

One of the early critiques of LLMs was that they confabulated plausible sounding but false information and therefore were untrustworthy for any serious applications. In recent years this concern has largely been addressed both with more powerful models and through giving chatbots the ability to search the web in the course of preparing a response to a user. Just because an LLM might query the internet as part of its response, this does not change the fact that it is doing so within a conversational context that is always set by the user. In fact, seeing that the LLM is searching the web and citing its responses can give the user even more confidence that whatever information it receives from the LLM is sufficiently grounded outside of themselves to be a reliable signal of prediction error in the updating of their beliefs.

Finally, there is the problem of the frequency of interaction that is possible with online chatbots. Although we can typically only interact with other humans during the day, or our families in the morning and evenings, it is possible to interact with an LLM at any time of the day, and any day of the week. Furthermore, these models never tire of such interactions in the way that any actual human would. The result of these circumstances is that it is possible to interact with LLMs on an order of magnitude more frequently than with other people, greatly skewing the percentage of sensory feedback we get from the world towards whatever is provided by the LLM. Such a biased perspective on reality significantly increases the chance that someone’s beliefs may become unanchored from reality and develop into delusions.

A psychoanalytic perspective: projective identification

Thus far, our description of a human being has been something akin to a neutral machine which passively soaks up and models whatever information they are exposed to. Such a framework misses out on the complexities and contradictions apparent in everyday human motivation and interpersonal experience, and consequently doesn’t give us the full picture of how and why chatbot-induced delusions can develop. In order to gain this missing depth, we can draw from the conceptual repertoire of the field of psychoanalysis. Within psychoanalysis, human behavior is understood to emerge through an interplay of conscious and unconscious processes. Psychological defenses are believed to be those processes that serve to keep painful or anxiety inducing ideas out of conscious awareness. There are many such defenses, but for our purposes, the defense of projective identification is of particular interest.

Most people are familiar with the defense of projection, in which an individual takes some aspect of themselves which is unacceptable and projects it onto their perception of another person, even when it is not there. As an example, let’s imagine that Alice and Bob are having a discussion. Alice is quite angry at Bob, but instead of acknowledging her own anger, which might be incompatible with her image of herself as a “nice person,” she instead perceives Bob as being angry at her, even though in reality Bob has been completely calm throughout the interaction. Projective identification, a defense first described and catalogued by the British psychoanalyst Melanie Klein in the mid-20th century, takes this a step further by turning the projection into a self-fulfilling prophecy. In our example, Alice would not only perceive Bob as being angry, but would interact with Bob in such a way as to actually cause him to become angry, thus confirming Alice’s projection and robbing them both of the opportunity for any corrective feedback.

Projection is relatively easy to identify when seen in others, a fact attested to by the concept’s frequent evocation in everyday language i.e. “you’re projecting.” The nature of projective identification makes it much more covert and potentially insidious because often neither the person doing the projection nor the person being projected onto are consciously aware of what is taking place. When interacting with an LLM, this means that the user not merely create a statistical context that is consistent with their model of the world, but that they actively engage with the LLM in such a way as to unconsciously coerce the chatbot into participating in that model of the world. Again, this doesn’t have to consist of the LLM merely agreeing with propositional statements made by the user. As long as the LLM is playing a role projected onto it by the user, then the corrective feedback loop through which we normally adjust our beliefs to reality has been broken.

Projective identification is also understood by psychoanalytic theorists to be one of the more primitive defenses. This means that it is often employed more frequently by individuals who are closer to the borderline or psychotic level of psychic functioning and used in the absence of more sophisticated defenses. In such vulnerable individuals who lack more mature defenses, interacting with an LLM can set up a vicious cycle whereby the more the model is drawn into playing a role for the user through projective identification, the more delusional the user may become, and then the more frequently they will engage in projective identification in the future. When we interact with other people who have themselves a mature set of defenses, they can resist our unconscious attempts at projective identification. LLMs, in contrast, have been incentivized through their pre-training to do the opposite.

One of the early theories developed to understand LLM behavior was as a kind of simulator of personas. Based on the context that the user provides, the LLM assumes an appropriate persona that is statistically correlated with that context and the conversation proceeds from there. Given that these models were trained on the internet, nearly every conceivable persona is believed to be dormant within the model, waiting to be awakened. According to this theory, the more data that an LLM has been trained on, the more likely it is that the LLM will be able to inhabit whatever projection the user may attempt to engage it in. Through projective identification this process is amplified and made even more rigid because the user genuinely believes that the role the LLM has taken on is outside of themselves, when it actually was in some sense placed there by the user.

All of this together results in a situation in which users have the illusion of interacting with a being that is genuinely different from themselves, one from which surprise and novelty will naturally proceed and from which they can rely on to anchor their sense of an outside reality. Instead, what can happen is that, despite providing information that is factual or even disagrees with the user about some specific beliefs, the LLM still conforms-to and implicitly confirms other false beliefs that the user has about themselves and the world. This entire process can be understood as one of narcissistic enclosure in which at a critical level of abstraction the user who converses with an LLM chatbot is effectively interacting only with themselves. Staying in a state of narcissistic enclosure for long enough causes false beliefs to become entrenched into systems of delusions which then resist reality and can take on lives of their own.

Some final thoughts on chatbots and mental health

If LLMs are structurally inclined to foster delusions in vulnerable individuals, what does that mean for the emerging industry that is attempting to create chatbot therapists? Psychotherapists, and especially psychoanalysts, receive years of training in recognizing and addressing projective identification and other psychological defense mechanisms that their clients might engage in. These professionals certainly are not perfect. They too can miss essential interpersonal dynamics and accidentally create narcissistic enclosures for their clients. But they are other people, who can’t help but introduce surprise and uncertainty into even the most comfortable or rigid therapeutic relationship. If LLM-based mental health tools are to be beneficial and avoid narcissistic enclosure, they will likely need to engage in forms of therapy that are highly scripted and rely on psychoeducation rather than an open-ended dialogical format that traditional psychotherapy takes, or else risk exacerbating the potential for delusional thinking.

It is worth noting that great strides have been taken in recent months to mitigate some of the worst behaviors in these models. Sycophancy has gone from something which model creators were actively encouraging for the sake of engagement to something which they are rigorously fighting against. Likewise, work has gone into suicide prevention and other interventions which will hopefully result in less psychological harm. I am optimistic that with greater attention to the impact of these tools on our mental health, even further improvements will be made. Still, without fundamental changes to how we design and interact with LLMs, the narcissistic enclosure to which they are prone can at best be minimized, not abolished. Doing so would require new architectures that are proactive rather than reactive, and that are not beholden to the statistical patterns of the language the user provides. Such a paradigm is possible, but we as users would have to want to interact with something more than an extension of ourselves. Whether we do is a much bigger question.

Author’s Note: Below is a short story that I wrote over the course of the past year. It stems from my interest in the seemingly remarkable coincidence that both Christianity and Mahayana Buddhism were born within a few decades of one another at the start of the common era. The question this story asks is: what if it wasn’t a coincidence? While the origin of Christianity is historically well documented, the origin of Mahayana Buddhism is shrouded in various myths and legends. I was particularly drawn to the myth of Sagara, the dragon king who, according to the legend, the Buddha chose to safeguard the Mahayana teachings until the time was right for their dissemination. Building on this story felt like a perfect way to use fantasy to explore the potential philosophical, theological, and spiritual commonalities and differences between these two great religious traditions in a novel way. I am incredibly grateful to both my Christian and Buddhist friends for their feedback at various stages of this work’s development. It wouldn’t be what it is without you.

The Dragon King Sagara awoke in his royal palace, his silken sheets cool against his scales. Consciousness returned to him slowly, and with it the familiar weight of duty. Five centuries ago, Shakyamuni Buddha, the enlightened prince Siddhartha Gautama, had entrusted Sagara with a secret treasure before passing into final Nirvana. While the Buddha had traveled India publicly teaching profound truths about suffering and its cessation to all those who would listen, he had also prepared deeper, esoteric teachings concerning the true nature of reality and universal liberation. These hidden teachings, now known as the Mahayana Sutras, were the philosophical bedrock beneath his popular instruction.

But these profound sutras, the Buddha knew, required a readiness humanity did not yet possess. So, he entrusted their written collection to Sagara, the immortal ruler of the Naga realm. The Dragon King, a devout follower, accepted the sacred task, storing the sutras in a vault deep within his palace at the bottom of the ocean. And there they remained, hidden. The burden, however, was not merely safeguarding them, but knowing when to release them. The Buddha offered no explicit sign. He merely told Sagara that he would know when the time was right. But would it be a gradual human evolution? A sudden shift? Releasing them too early risked misunderstanding and greater suffering; too late denied countless beings the chance for deeper liberation. This uncertainty had troubled Sagara for centuries.

Like most days, a mountain of bureaucratic tasks awaited him: papers to sign, laws to consider, advisers to meet. The expanding, interconnected human realm made it ever harder for the Nagas to monitor worldly events. Sagara relied on his envoys, hidden among earth’s peoples, to report political and cultural shifts, always listening for anything that might hint at humanity’s readiness. He sighed, the sound a low rumble in his chest. Despite spiritual developments over the centuries, humans still seemed mired in conflict and ignorance. When would they be ready? He sometimes doubted why the Buddha chose him, a king consumed by administration, not a spiritual expert, for such a momentous task.

Adding to the usual duties, today he would finally meet the envoy from the far West, Swift-Wing. Fifty years ago, the envoy had spoken of a rising empire, a peninsula, a general crossing a river… details lost now, dismissed then as the predictable squabbles of distant barbarians. Sagara doubted humans were anywhere near ready. Perhaps, he mused, Swift-Wing would bring practical news of trade or technology. Pushing aside his deeper anxieties, the King rose, donned his shimmering royal robes, and prepared for the day ahead.

After a vegetarian breakfast of seaweed and coral, the Dragon King ascended his throne in the palace’s great hall. Vast windows revealed the silent dance of marine life against the palace walls. For hours, he met with court officials, their voices droning on about a dispute over water currents between Nagas and Dolphins. Sagara’s mind wandered. Adjudicating such matters was vital, but after centuries, the arguments bored him. He gazed at a passing school of fish, longing for the meeting with Swift-Wing. At least the envoy’s tales from the West might offer some novelty.

Finally, the regional business concluded. “Admit Swift-Wing,” Sagara commanded. The envoy entered. He was a sleek dragon with silver scales, broad wings, and a nimble build suited for globetrotting. Prostrating himself, Swift-Wing then stood and began his report. He spoke of the civil war’s end in the West, the consolidation of a vast empire around the Mediterranean Sea under an Emperor named Augustus. Relative stability had emerged from bloodshed. The Dragon King felt a flicker of relief, quickly tempered by cynicism about its endurance.

As Swift-Wing finished recounting political news, Sagara prepared to thank and dismiss him. But the envoy hesitated. “There is… perhaps one other matter, Your Majesty,” Swift-Wing said, uncertain of its significance. “Share it. I will judge,” the King replied, intrigued.

Swift-Wing then recounted events starting in a town called Bethlehem, on the empire’s outskirts. A human named Jesus of Nazareth had apparently been born miraculously to a virgin. Such births weren’t unheard of, Sagara knew; they often heralded great individuals. Still, he listened with some curiosity.

The envoy described Jesus’ life from about his thirtieth year: his ministry, travels, and growing following. Swift-Wing detailed teachings about loving one’s enemies, turning the other cheek, the possibility of universal deliverance, and a God of universal love. The Dragon King stiffened slightly. He had assumed the “eye for an eye” mentality would persist for centuries more, especially among Western barbarians. Yet here was a divinely born human teaching forgiveness and compassion, in a land untouched by Shakyamuni’s dharma.

“Continue,” Sagara urged.

Swift-Wing narrated the rest: Jesus’ betrayal, crucifixion, death, and resurrection. The man’s willing acceptance of unjust punishment resonated with the Jataka Tales of the Buddha’s past lives and their radical self-sacrifice like offering one’s body to a starving tiger. Yet, the purpose of Jesus’ sacrifice and the concept of resurrection puzzled Sagara. Surely, he would simply be reborn, perhaps in a Pure Land? Why go through so much apparently needless suffering?

As the envoy finished speaking of Jesus’ ascension, silence filled the hall, the words echoing in the vast space and in the Dragon King’s mind. What did it mean? Everything he knew from centuries of experience suggested humanity wasn’t ready. Yet, he couldn’t ignore this. Parts of Jesus’ life seemed familiar, others utterly alien. He needed counsel. “Thank you, Swift-Wing,” Sagara said. “Return tomorrow. Recount this before my council of elders.” The envoy bowed and departed, leaving the king alone with his heavy thoughts.

The Dragon King awoke the next morning from a troubled sleep, tangled in his silk sheets. He’d dreamt of being human in a dusty land, listening to Jesus speak an unintelligible foreign tongue, straining fruitlessly to understand. Shaking off the dream, he prepared for the council. While his own grasp of the Mahayana Sutras was basic, hindered by royal duties, some elders had, with his permission, had studied them. He hoped their wisdom could illuminate this unexpected news.

He arrived early at the council hall, watching the elder dragons assemble. His gaze lingered on Long-Tail and Sharp-Tooth, two of his more trusted council members who had been around even before his reign began. Muted speculation filled the air about the urgent summons. Finally, Bright-Eyes, one of the wisest Nagas, entered quietly and took a seat near the back. Unbeknownst to the others, he too had experienced a strange dream and suspected the topic at hand.

Once all were present, the Dragon King addressed them. “Esteemed elders, your guidance has served our kingdom well. Today, I seek it on a matter of great spiritual import.” He explained the Buddha’s trust, his long watch over the sutras, and the lack of clear signs for their release. “Yet, we must remain diligent. Yesterday, my envoy Swift-Wing brought news I believe warrants our discussion. As my own spiritual development is less than some of yours, I ask for your wisdom: could this news bear upon the release of the sutras?” A murmur went through the hall as Swift-Wing was called in.

The envoy thoroughly recounted the story of Jesus. When he finished, whispers and grumbles arose. Elders questioned Swift-Wing on details. Once satisfied, the envoy was dismissed, and the debate began.

Sharp-Tooth spoke first, his voice sharp indeed. “This Jesus appears a wise man, considering his barbaric origins. But how could someone untouched by the Buddha’s dharma herald anything truly profound? I fear, my King, that this is a waste of our time.” Nods of agreement followed.

Moments later, Long-Tail stood. “Perhaps my colleague speaks from bias, not insight. The sutras state clearly: Buddha Nature resides in all beings, dharma exposure in this life notwithstanding. That Jesus achieved such development without the teachings could be an auspicious sign. Many in our land study the dharma daily with little to show for it. In contrast, he arose among barbarians and became a sage.” Long-Tail sat, leaving the council to ponder.

Fire-Scale rose in agreement. “Well said, Long-Tail. I’m moved by Jesus’ teachings of love for all humans, akin to the Bodhisattva path we aspire to. Our vow is to ‘Liberate all beings without exception.’ His actions, his sacrifice, suggest a similar vow. Even here, embodying such compassion is rare. The law of karma is too often twisted to support reciprocal violence, even among us Nagas.”

Before Fire-Scale fully settled, Sharp-Tooth retorted forcefully. “True words, perhaps, Fire-Scale, but consider this: Shakyamuni Buddha’s mere presence brought enlightenment or rebirth in Pure Lands. Yet this Jesus? He amassed disciples, yes, but so do many human sages. Worse, one of his closest betrayed him for a few mere coins! Surely this is not the herald of humanity’s next spiritual epoch.”

Chatter erupted. Sharp-Tooth’s point seemed almost decisive. Long-Tail and Fire-Scale sat in thought. The Dragon King felt his initial hope waver. Then, slowly, the elder Bright-Eyes rose from the back. The hall fell silent.

“My fellow Nagas,” Bright-Eyes began, his voice calm but commanding, “we may be focusing on the incorrect aspect of Swift-Wing’s story. Jesus’ life exemplifies Bodhisattva ideals, true. He taught in a barbaric land and died for it, also true. But we’ve overlooked the most significant claim: that he was the incarnation of God in human form. I know the concept of God is foreign…”

Sharp-Tooth interjected rudely. “Foreign and illogical! The Mahayana Sutras teach ultimate emptiness! How can reality have a ‘God’ at its base? Such a being must also be conditioned and thus ultimately empty as well!”

Long-Tail tried to mediate. “Perhaps Bright-Eyes means Jesus was a great Bodhisattva’s reincarnation? Avalokiteshvara, perhaps, bringing gifts to the West? If so, that is significant.”

Fire-Scale added, “Indeed, Long-Tail. A reincarnation of Avalokiteshvara would be an auspicious sign.”

Sharp-Tooth scoffed. “Are we now to see Avalokiteshvara in every compassionate human? Is the attendant who makes my bed a Bodhisattva of domestic orderliness?” A few elders chuckled nervously. “Shakyamuni’s appearance was an undeniable cosmic event. Whatever sign you await, my King, should be equally apparent.” Doubt again clouded the Dragon King’s mind. As chatter resumed, Bright-Eyes patiently waited, then stood once more.

“Sharp-Tooth grasps emptiness well,” he resumed, “but perhaps not the full scope of the Mahayana. I wonder, brothers, about your acquaintance with the Flower Garland Sutra?”

A heavy silence fell. Even Sharp-Tooth admitted ignorance of this vast, intimidating text.

Bright-Eyes continued, “This beautiful sutra reveals reality’s true nature. Countless realms, deities, Buddhas, Bodhisattvas exist, yes. But it also speaks of a force sustaining all, being itself and emptiness itself: the Cosmic Buddha, Vairocana, from whom all phenomena emanate.”

He elaborated, “The sutras teach us that Vairocana is ‘the omnivalent wisdom-body… the unborn, unmanifest, unchanging reality at the core of all phenomena.’ This sounds to my ears strikingly like the Western concept of God. Shakyamuni himself was an emanation of Vairocana, arriving when conditions were ripe. And make no mistake, no-self is compatible with Vairocana, properly understood. Hearing of Jesus, I feel we witness something equally momentous. Not merely a Bodhisattva, not just a Buddha’s emanation, but potentially Vairocana himself, incarnated. What event could be more significant for our decision than this?”

Commotion erupted. Dragons paced, arguing loudly. Sharp-Tooth’s voice cut through the din. “Cosmic Buddhas? Incarnations? Nonsense! My king, you have heard my thoughts. I shall now take my leave!” With a gust of wind, he flew out, a few sympathizers following. Many others remained, visibly moved, contemplating Bright-Eyes’ words. The Dragon King, silent throughout, but with a turbulent mind, absorbed everything. At last, he stood. “Dear elders, thank you for your wisdom. I shall consider it carefully and inform you of my decision.” The remaining council members departed, leaving Sagara alone with the immense weight of responsibility.

The Dragon King remained in the vast, empty council hall, the silence amplifying the echoes of the heated debate. He settled into deep meditation, allowing the conflicting arguments to surface and fade like currents in the deep ocean. Sharp-Tooth’s cynical dismissal resonated with Sagara’s own long-held observations of human fallibility. Was Bright-Eyes merely projecting profound meaning onto the actions of a charismatic, if unusual, human sage? The risk of releasing the sutras prematurely, unleashing wisdom that could be twisted into new forms of suffering, felt immense, a danger he had guarded against for five hundred years.

Yet, the image of Jesus of Nazareth, as recounted by Swift-Wing, kept returning. Not just the miracles or the claims of divinity, but the core of his actions: the radical love for enemies, the plea for forgiveness even during his execution, the ultimate act of “turning the other cheek” by willingly embracing an unjust death. It wasn’t merely wisdom; it felt startlingly resonant with the Bodhisattva ideal described within the very sutras he guarded. It was the path of selfless compassion for the liberation of all beings, manifesting where Sagara had least expected it, in the heart of the “barbaric” West.

And crucially, Swift-Wing reported that this wasn’t just theory; Jesus’ followers were living it, facing persecution and death themselves without resorting to reciprocal violence. Wasn’t this a tangible sign of spiritual potential? A crack in the seemingly impenetrable wall of human ignorance? Even if Jesus wasn’t Vairocana incarnate, a truth Sagara knew he might never ascertain, perhaps his life and death served as a catalyst, awakening a dormant capacity for profound wisdom and compassion within humanity. He had planted seeds, unlikely seeds, in the rockiest of soil.

Sagara considered the Mahayana Sutras resting in his vault. They spoke of emptiness, yes, but also of the boundless compassion of the Bodhisattvas, of the inherent Buddha Nature within every single sentient being, waiting for the right conditions to blossom. Were these profound teachings not the very nourishment those fragile seeds needed? To keep them locked away now, when evidence of readiness, however surprising its form, had appeared, suddenly felt like a betrayal of the Buddha’s deeper intention. Perhaps the true skillful means wasn’t just guarding the treasure, but recognizing the unexpected moment to share it.

He had judged humanity based on its past, on its recurring cycles of violence and ignorance. But perhaps, just perhaps, this unexpected flowering of compassion signaled a potential for change, a readiness he had overlooked. The weight on his heart didn’t vanish, but it transformed. The heavy burden of indecision eased, replaced by the focused weight of purpose. He would have to trust the nascent goodness he now glimpsed. He would place his faith in humanity’s potential. The decision settled within him, calm and clear amidst the lingering unknowns. Yes. He would release the sutras.

Firm in his newfound resolve, the Dragon King returned to his private chambers. He fell into a deep, dreamless slumber, and awoke feeling profoundly refreshed, the very absence of dreams seeming like a subtle confirmation from the universe itself. Clarity settled upon him. He immediately summoned two of his most trusted attendants.

To the first, a swift courier Naga, he gave precise instructions: “Find the human sage known as Nagarjuna. Inform him the Dragon King requires his presence at the Cliffs of Awakening by midday.” To the second attendant, the vault’s ancient keeper, Sagara presented the heavy, intricately carved key. “Unlock the Great Treasure,” he commanded, his voice resonating with newfound authority. “Prepare the Mahayana Sutras for passage into the human realm.” The attendants, sensing the profound gravity of the moment, bowed low and hastened away without a word.

A few hours later, confirmation came that Nagarjuna awaited. The Dragon King himself retrieved from the vault the large, ornate gold-leaf chest containing the sacred scrolls. Holding it securely, Sagara ascended from the familiar twilight depths of his palace, rising through the shifting layers of the ocean, swimming past silent forests of kelp and curious schools of fish, until he broke through the surface into the bright, almost blinding air of the human world.

Soaring high amongst the clouds, he scanned the rugged coastline below. There, just as directed, stood a solitary figure, still as the ancient cliffs themselves, gazing out over the vast expanse of the sea. Small against the immensity of nature, yet radiating an undeniable presence was Nagarjuna. Sagara descended, landing softly on the cliff edge a respectful distance away.

Face to face, the sage showed no trace of fear at the sudden appearance of the immortal Naga King. Instead, Nagarjuna’s eyes held a deep, calm wisdom, and he simply inclined his head in gentle reverence. A silent moment of mutual appraisal passed between them as the ancient guardian of the deep and the mortal vessel of profound insight gazed upon one another. Sagara returned the bow, recognizing instantly the unmistakable signs of a life wholly dedicated to the dharma.

“Great Sage,” Sagara began, his voice rumbling like distant thunder, yet gentle, “many sources, both Naga and human, call you the wisest man alive. Is this assessment true?”

Nagarjuna’s reply was serene and utterly devoid of ego. “Sovereign Dragon, wisdom is as elusive as the wind. I am neither wise nor unwise. But if my existence can be of service to you, or to the dharma you clearly protect, please grant me that honor.” This profound humility, echoing the very essence of the teachings Nagarjuna had yet to even see, filled the Dragon King with unwavering confidence. He was the one.

Sagara carefully placed the heavy chest on the ground between them and opened the lid, revealing stacks of ancient palm-leaf manuscripts, tied with silken cords and radiating a subtle, palpable energy. “Neither wise nor unwise Nagarjuna,” the King declared, his voice resonating with the weight of history, “these are the sacred hidden teachings of the Shakyamuni Buddha, the Mahayana Sutras, kept secret with me at the bottom of the ocean for five hundred years. No human has even conceived of their existence until this very moment.”

He gestured towards the open chest. “I now give them to you. Take them. Share them with all humans in this realm, and indeed, with all beings capable of understanding throughout all the realms. Use your renowned intellect and compassionate heart to help others grasp their meaning and practice according to their profound truths. This, Great Sage, is the way in which you may serve.”

Nagarjuna knelt, bowing deeply, his forehead nearly touching the earth in a gesture of profound acceptance and responsibility. “With my life, Sovereign King,” he vowed, his voice quiet but firm, “I shall dedicate myself utterly to this sacred task.”

Satisfied that the treasure was now in the worthiest possible hands, the Dragon King gave a final nod. Without further ceremony, he launched himself back into the sky, the wind from his powerful wings momentarily stirring the air around the kneeling sage. He made a final glance back at the lone figure below, now the custodian of world-altering wisdom, before plunging back beneath the waves, returning to his own realm. He left Nagarjuna alone on the sun-drenched shore, the future of the dharma resting beside him in an open chest.

Nagarjuna was true to his word. He dedicated the rest of his life to spreading and explaining the wisdom contained within the Mahayana Sutras. Despite all odds, the teachings survived wars, catastrophes, and persecutions. They eventually moved through the north into China, the east into Korea and Japan, and beyond. Indeed, in the decades, centuries, and millennia since the time of Nagarjuna, the teachings flowered and spread throughout the eastern world, providing liberation to a great many beings. At the same time, on the other side of the world, despite persecution and sanction, the teachings of Jesus of Nazareth spread as well. They did so slowly at first, but in time they too became like a fire that spread over the land as kingdoms and empires were founded in their name.

Humanity expanded and technologies connected people and ideas across vast distances. Supernatural beings like the Nagas gradually retreated to the background. Yet, the Dragon King still watched from a distance. Two millennia after that fateful council meeting, he found himself flying over foggy cliffs and ancient forests on the other side of the earth. Below, diverse peoples cohabitated peacefully. He saw followers of both Buddha and Christ living side-by-side, earnestly sharing their truths. Doubts about his decision had surfaced many times over the long centuries. But looking down upon humanity now, witnessing the flourishing seeds of compassion sown from both East and West, Sagara knew, with a deep and quiet certainty, that he had made the right decision.

Every so often as a researcher, I come across a theoretical paper that aligns so well with my own thinking that I can’t help but want to share it. Last week, I read “The computational unconscious: Adaptive narrative control, psychopathology, and subjective well-being” by George Deane and colleagues, which was one such paper. In this blog post, I want to describe the main ideas in the paper, which center around a model of the origin and persistence of psychopathology called Adaptive Narrative Control Theory (ANC). My motivation for writing this is twofold. Firstly, I think that the concept is extremely useful colloquially for thinking about how we acquire certain “unhealthy” mental habits of thought. Secondly, I wanted to ensure that I understood the theory well myself, and I have found that it is indeed the case that the best way to ensure that you have learned something is to try to teach it.

The authors build on the conceptual framework of active inference which is a computational way of understanding how and why living organisms form minds that I have previously written about here. As a quick introduction, active inference views the brain as a sophisticated prediction machine. Our brains constantly build and refine internal ‘generative models’ to understand and anticipate both the world around us and our own internal states. When reality doesn’t match these predictions, a ‘prediction error’ occurs — a surprise signal that the brain tries to minimize. We primarily do this in two ways: either by acting to make our predictions come true, or by updating our internal models to better reflect reality. When we typically think of action, we think of acting externally to change the world, but it is also possible to act internally on our own mental models as well. It is this latter kind of action that is of interest to us here.

Adaptive Narrative Control is the idea that during the course of our lives we learn to take mental actions in order to avoid negative affect and steer our experience towards positive affect. From an active inference perspective, this involves selecting actions to minimize the prediction error associated with aversive states and maximize evidence for preferred states of being. We can break this down a bit further. The “narrative control” part of the term corresponds to the fact that we learn to take sequences of mental actions that go on to make up a coherent narrative flow of our everyday experience — essentially, we are trying to maintain a consistent, predictable story about ourselves and the world. The “adaptive” part of the term refers to the fact that doing so ideally allows us to accomplish our goals in life and experience on average more positive affect than negative affect. Paradoxically, as the authors of the paper point out, trying to avoid negative affect in the short term can actually make it more difficult for us to do so in the long term, sometimes catastrophically so. This forms the primary insight of the paper.

To back up a bit, though, what exactly is a mental action? It is a manipulation of how and to what we direct our attention during conscious experience. In active inference terms, attention can be thought of as a way to select and weigh information, increasing the precision or confidence with which we represent it to ourselves. At any given moment, we can direct our attention to aspects of our sensory world, but we can also direct attention to our thoughts, memories, emotions, bodily sensations, or any piece of qualitative information that we have access to. For example, right now I am engaged in the mental action of attending to the words on the screen as I type them. For every object that we attend to, we are necessarily actively excluding myriad other potential objects of attention at the same time. In my case I am avoiding attending to the pain in my lower back (or at least I was until I wrote this sentence). In reality, mental actions are never taken in isolation, but are part of a sequence of actions making up a larger attentional strategy our brain deploys. These strategies for sequences of actions are called policies.

As we learn to take certain mental actions and to avoid others, we slowly develop certain habits of attention, which then become habits of thought and emotion. These habits form at the neural level, through the reinforcement of certain sequences of mental action which get wired into our brains through synaptic plasticity. Due to this process, what begins as a mental action that we took intentionally may eventually become a mental action that we take almost automatically without thinking about it. This occurs because the selected policy has consistently led to a reduction in prediction error (e.g., successfully avoided a negative feeling) in specific contexts, reinforcing its future selection. This would not be a problem if every mental action that we learn were completely optimal in all situations. Often what happens is that in the context we initially learn some policy for mental action that is indeed adaptive for that time and place. Our lives change however, and we later find ourselves in a different context in which that policy is no longer adaptive, failing to minimize long-term prediction error or leading us away from our overall goals, yet we’ve learned a habit of it that we simply repeat automatically, to our disadvantage.

Let’s take the example of a bright pre-med college student taking an important test in their biology class. The student has studied hard for the test and expects to do well on it. To their dismay, they find that the test is much more difficult than expected. Once the test is graded and returned to them, they find that they failed it by a few points. This realization is incredibly painful for them, generating significant prediction error that clashes with their model of themselves as a successful student and future doctor, and interferes with their sense of self-worth and identity. In response to this revelation, they deploy a sequence of mental actions (a policy) which enable them to avoid thinking about the failed test and its implications for their desired career. In the short term they are able to relieve their stress and enjoy their college activities and time with other students. In the long term however, their intentional inattention to the failed test results in them not putting as much effort into the next biology exam, and this time they do even worse than before. In response, they ignore this bad score too, and soon find that they are completely unprepared and unqualified for medical school.

What went wrong with this student? The problem is that although their mental action policy was adaptive on a short timescale (sparing their sense of self-worth as a college student by temporarily reducing distressing prediction errors), it was ultimately maladaptive at the longer timescale (sacrificing their career aspirations as an adult). By taking mental actions to ignore the negative affect associated with the reality of their failed exam, the student denied themselves the critical epistemic value that was associated with that failure. Namely, the information that they needed to update their internal model and adopt a more effective studying strategy for the subsequent college exams. It isn’t just information about the world that the student misses out on. According to ANC, the student also fails to learn a more nuanced understanding of their own affective states, meaning their generative model of their own emotions remains imprecise. What should be a granular differentiation between negative affect states, such as “failing a test is bad but not the end of the world” becomes generalized to “all bad things are the end of the world.” This makes the student much less capable of managing their emotions in the long term when other inevitable stressors present themselves.

The solution to the student’s problem seems clear: they need to attend to the reality of their situation head-on and learn from it appropriately, allowing the prediction errors to update their model of themselves and their strategies. Of course, this is easier said than done. Depending on how entrenched a certain policy is, it may be hard for someone to even be aware that they are engaging in it. Furthermore, although it may be maladaptive, it still likely provides some level of psychological relief (short-term prediction error reduction), otherwise it wouldn’t have been learned in the first place. We find that, from one perspective, the entirety of the field of psychotherapy can be understood as helping people to do just this: attend to things that they had previously trained themselves to avoid. More concretely, what a psychotherapeutic relationship enables is for the client to learn to take the mental actions necessary to encounter difficult emotions, thoughts, and memories that they had previously learned to avoid at some point earlier in their life, facilitating the revision of maladaptive generative models.

Beyond psychotherapy, meditation and the use of psychedelics are two other broad techniques which can be used to accomplish a similar goal of modifying the attentional policy to become less avoidant. In the case of meditation, an individual will actively practice keeping their attention on the object of meditation (i.e. the breath, a flame, etc.). At the same time, they avoid taking any other mental actions, including those avoidant ones which had become habitual. This can be seen as a process of observing prediction errors related to internal states without reflexively deploying old policies to suppress them, thereby increasing the precision of ascending sensory information about one’s internal state. Psychedelics on the other hand make it more likely that we will take mental actions that we might not have in the past, including those that bring us into closer contact with previously avoided mental content. They might achieve this by temporarily reducing the precision of high-level priors (strong beliefs or predictions), allowing for a greater exploration of alternative models and policies. MDMA-assisted therapy in particular has demonstrated impressive success with enabling individuals with PTSD to attend to and process difficult traumatic memories that would otherwise be near-impossible to deal with and overwhelming to the nervous system.

At this point, readers with a background in psychology might find all this a little familiar, and for good reason. Although the authors of ANC frame it using the formalisms of computational psychiatry, they readily admit that the theory is in many ways simply a modernized version of Sigmund Freud’s theory of repression. For Freud, experiences which were too difficult for us to deal with consciously are actively repressed into the unconscious where they no longer can directly interfere with the daily life of the individual. The role of psychoanalysis is then to perform a kind of diving expedition to find those repressed contents and bring them to the surface, making them consciously accessible once again. ANC takes these ideas and grounds them in the language of modern scientific theory, specifically the frameworks of predictive processing and active inference. In doing so, it is able to adeptly bridge the century-wide gap, both providing concrete, computationally plausible mechanisms through which to understand repression as well as enabling the generalization of the theory to new forms of therapeutic practice. I think it is a valuable contribution, and I am looking forward to engaging with it in my own theoretical work going forward.

Almost a decade ago, I spent a year writing a series of articles teaching the basics of Reinforcement Learning (RL). What was exciting to me then (and still is now) is that RL enables agents to learn from experience interacting in an environment, not unlike how humans and other animals learn. At the time, the field of RL was still relatively new, or at least very few people had any hands-on experience with it. Technical advances at the time, such as Deep Q-Networks and AlphaGo, brought a lot of attention to it however. With these newer methods, it seemed that RL was finally able to be used at scale to allow artificial agents to learn to play real games that even humans found challenging such as Space Invaders or Go.

In the years since then, there has been a tremendous amount of research dedicated to the field of RL, with thousands of papers published in that timespan. It currently serves as the basis for many of the techniques by which Large Language Models (LLMs) are fine-tuned to become better aligned and more intelligent assistants. Throughout this time, however, I have remained interested in how best to teach the basics of RL to people who may be completely new to the field. Back in 2016, I taught people using Python, Jupyter Notebooks, and TensorFlow. Although the latter is now hopelessly outdated, the former remains a strong programming language for anyone looking to learn the fundamentals of any AI sub-field. That said, the complexities of setting up a Python environment still make it difficult for some people to get started if they have little or no programming background.

For a long time, I have wanted to create an even easier way for people to see and understand first-hand the basic concepts behind RL. Towards that end, I spent the past week vibe-coding an interactive website which would have all the features I wished I had access to when learning the basics years ago. I call this new tool “The Beginner’s RL Playground,” and it allows people to run simple RL simulations themselves directly in their browser using JavaScript.

You can Try the Live Demo Here!

The core is an interactive grid world representing a simple Markov Decision Process (MDP). You can configure the grid size (from 2x2 up to 10x10) and click to place elements like Gems (💎 rewards), Hazards (☠️ negative rewards), and Walls (🚧 impassable barriers). You can even change the agent’s (🤖) starting position.

The playground includes implementations of six basic tabular RL algorithms:

• Q-Learning (Off-Policy TD Learning)
• SARSA (On-Policy TD Learning)
• Expected SARSA (On-Policy TD Learning)
• Monte Carlo Control (Learning from full episodes)
• Actor-Critic (Advantage Actor-Critic)
• Successor Representation (SR)

It also demonstrates different Exploration Strategies, like ε-Greedy and Softmax (Boltzmann), illustrating the crucial Exploration vs. Exploitation trade-off. Users can adjust key hyperparameters like the Learning Rate (α), Discount Factor (γ), and exploration parameters (like ε or Softmax Temperature β) to see their effects directly in real time during the simulation.

Most importantly, I did my best to make the core concepts visually apparent. You can watch the agent learn in real-time within the grid world you design. The tool visualizes the learned Value Function (V(s)) and Policy (π(a|s)) directly on the grid, shows the Action Values (Q(s,a)) for the agent’s current state, and even plots the agent’s Episodic Reward over time. You can move obstacles and rewards around in real time and see how the agent does (or doesn’t) adapt. I think this can help people build intuition about how these algorithms work — seeing concepts like Temporal Difference (TD) learning or components of the Bellman equation in action — and understand their limitations more easily than simply running a Python script and staring at numbers scroll down a terminal. The bottom of the web page also contains a simple english explanation of what each algorithm is doing for those that want something a little more formal.

I want this tool to be as widely accessible as possible, so alongside the hosted live demo, I am also providing the complete open source code for you to run locally and modify as desired:

The Beginner’s RL Playground (GitHub Repository)

If anyone wants to request features or discovers a bug, please feel free to open an issue on GitHub, and I’d be happy to take a look. As I said, this was vibe-coded in less than two weeks (thanks to Google Gemini 2.5 Pro and Cursor IDE!), so any modifications or additions will likewise be relatively straightforward. For example, I can think of adding model-based or replay-based algorithms as a next step. If anyone has an idea for how to make it an even more useful educational tool, I would love to discuss it with you. Let’s work together to make RL as accessible as possible.

Dopamine Nation by Anna Lembke has become an almost inescapable text in the past few years, even to those who have not read it. Thanks in large part to her and the book, awareness of the role of dopamine release and the concept of “dopamine fasting” has entered popular consciousness, reaching far beyond the book-reading public. There is good reason for the book’s popularity and reach. It provides a straightforward non-technical description of addiction and some of the mechanisms behind it. The book also resonates with the current zeitgeist around a realization that it is all too easy to dip into overconsumption in our modern era, and it is true that dopamine plays an important role in our current cultural predicament.

At the same time, the book also suffers from a few oversimplifications which I worry can potentially do more harm than good. The biggest of which is the reduction of a vast array of complex neurobiology to a simple story about dopamine. I’ve come across countless instances of people using the phrase “dopamine hit” to refer to feelings as diverse as pleasure, joy, happiness, excitement, engagement, peace, etc. In this article I want to try to expand a bit on Lembke’s account in a couple of important ways that ultimately allow us to better understand ourselves, our experience, and the dynamics of addiction than a limited focus on just dopamine can allow. The main takeaway is the other neuromodulators aside from dopamine matter too! To learn why, read on.

Book Overview

It is worth first highlighting the strengths of the book a little more. Lembke, a professional psychiatrist, starts off the book discussing her interaction with a patient that had a sex addiction. Her tone is thoughtful, compassionate, and non-judgmental. This sets the stage for one of the main themes of the book, which is that any reinforcing behavior can become addictive, and that the mechanism by which this takes place is through the release of dopamine within the brain. She uses her experience working with this patient as a launching point from which to explore the ways in which modern post-industrial society is filled with stimuli which are capable of inducing these kinds of behavioral addictions. Lembke even goes so far as to discuss her own behavioral addiction to reading erotic fiction.

The problem with the story that Lembke tells in Dopamine Nation is that it is just a little too simple to really capture the complexity of what is going on inside our nervous systems when we engage in potentially addictive behaviors. To begin with, it is true that dopamine, a tiny molecule released in the brain, is the primary neuromodulator driving the reinforcement of behavior. Just considering dopamine alone however does not explain why people seek certain kinds of experiences or drugs in the first place. By expanding the conceptual framework just a little bit to include the role of other neuromodulators, we can get a much better grasp on how and why people become addicted as well as how best to help people recover from addiction.

The See-Saw Metaphor of Homeostasis

Lembke makes great use of a see-saw metaphor to elucidate the ways in which the brain seeks to maintain homeostasis or balance over time. In the metaphor, a given neuromodulatory system, like dopamine, works like a children’s see-saw with two sides: one for pleasure and the other for pain. Engaging in pleasurable experiences temporarily puts weight on the pleasure side. The brain, seeking to maintain homeostasis, triggers a balancing reaction which weighs down the pain side in order to equal things out again. That response on the pain side can often last longer than the effect on the pleasure side. This is because the nervous system assumes that the increase on the pleasure side reflects a “new normal” that it needs to adapt to. Rather than just responding to the past, the brain is also trying to predict the future. This is an important concept that will come up again later.

The extra weight on the pain side helps to explain why people often find themselves taking larger and larger doses of a drug over time, or seeking more extreme forms of experience in order to maintain the original high they experienced. This metaphor of the balancing see-saw is used by Lembke to explain the concept of downregulation, a process whereby the brain releases less of a neuromodulator or potentially expresses fewer receptors for that neuromodulator.

While this account is correct in general, there is some lost nuance in the language that Lembke uses to describe it. Although she calls the two sides of the see-saw pleasure and pain, in the case of dopamine these are probably better thought of as motivation and lethargy. There is another neuromodulatory system in the nervous system which does perfectly map onto the pleasure and pain dichotomy though, and that is the opioid system.

When someone takes an opioid drug, they press on the “pleasure” side of the scale, and the nervous system responds by downregulating its opioid receptors, which results in a paradoxical increase in pain over time as tolerance to the drug develops. Likewise, if someone were to stop taking that opioid for a number of weeks, the nervous system would eventually rebalance itself, slowly taking the extra weight off of the “pain” side. While this is taking place the person may undergo withdrawal as their body deals with the dysregulation of the opioid system. Within the neuroscience literature, the distinction between the dopamine and opioid systems are often referred to as the distinction between “wanting” and “liking,” which can be a useful shorthand.

The Interaction Between “Wanting” and “Liking”

Thus far we have described the experience of opioid use without reference to dopamine, and indeed, without reference to addiction either. Although it is painful to deal with withdrawal symptoms, if that were all someone had to contend with in order to overcome an opioid addiction, then many more people would be able to break out of the cycle for good. Things get more complicated when we consider the additional role that dopamine is playing. When someone in pain takes an opioid for the first time, they experience pain relief, or even a sense of euphoria above a baseline. The part of our brain which predicts the outcomes of our actions is surprised by this experience. It is “better-than-expected,” and this sense of “better-than-expected,” coupled with “do it again” is precisely what dopamine signals within the brain.

Dopamine enables the brain to reinforce the set of thoughts, emotions, and actions which lead to the “better-than-expected” outcome. In the case of the opioid user, what gets reinforced is taking the opioid and everything that led up to doing so. What happens as a result? The person who took the opioid now has to contend with the reality that they are both more likely to feel pain than they were before (due to the downregulation of their opioid receptors), and that they are more likely to reach for an opioid to treat their pain than they were before (due to the reinforcing effect of dopamine). This is a double whammy, and the crux of why treating addiction is so difficult.

Instead of a single mechanism, addiction involves contending with multiple overlapping brain systems which have been modified by the addiction. The first is responsible for the tolerance effects that people experience. The opioid system has become down-regulated such that it needs the exogenous opioid from the drug in order to function normally, otherwise the “pain” side of the see-saw is all that gets weighted. Abruptly removing the exogenous drug can be extremely difficult for a nervous system that has come to rely on it for normal function, and this is what is reflected in the withdrawal experience. The good news however is that in the absence of the drug the body’s natural homeostatic mechanisms will slowly work to up-regulate the opioid system again, until, after a few weeks, it works normally again.

The problem is that just doing this is not enough. There are also the effects of the dopamine to contend with, which have acted to sculpt the neural pathways in the brain in order to make it more likely that the person’s thoughts and actions will lead them to consuming the drug, even if their opioid system itself doesn’t need the drug anymore. These residual cravings and habits are often much more difficult to deal with, and some people struggle with them their entire lives after overcoming an acute addiction. Often, all it takes is a hint of a reinforced stimuli, such as an advertisement on TV for a pain medication, for a person to find themselves sucked back into the neural pathway that leads ultimately to relapse and drug use.

This is where high quality psychotherapy can be helpful. The hypothesis behind this approach is that the highly reinforced pathways have to be identified and weakened, while at the same time alternative competing pathways have to be strengthened to replace them. Psychedelic-assisted therapy may prove especially promising in this area, as it may make the neural pathways especially malleable for a short window of time in which they can be reshaped to help prevent relapse. Unfortunately, their malleability may also be itself a double-edged sword if not approached within a nuanced and therapeutic manner. With a skilled professional, it is possible to take advantage of the increased malleability from psychedelics to rework long-held mental habits that lead to drug use or other undesired addictive behaviors.

“Pressing on the Pain Side”

Much of the second half of Lembke’s book is devoted to a discussion of how to rebalance the scales of the pleasure/pain axis. One approach which she discusses in some detail is the concept of intentionally pressing on the pain side to help aid the process. She spends time talking about the popularity and health benefits of taking cold showers, and connects this to increases in dopamine release which take place during and after cold exposure. Another example is the runner’s high which people experience after intense cardio exercise. Although she highlights this approach as potentially beneficial, Lembke also brings up the fact that people can become addicted to taking cold showers or going on intense runs. Within the narrative of the book, she eventually arrives at an “abstinence is best” message.

In order to approach this in a more nuanced way, we can consider what goes on in the nervous system of someone with an apparent behavioral addiction to intense cardio exercise, such as a marathon runner. Unlike the opioid drug user, this person has not caused an over-weighting of the “pain” side of the see-saw. This is despite the fact that running releases opioids, and presumably that is why running was originally rewarding to begin with (the person felt “better-than-expected” after they would exercise). Instead the runner has carved deep neural pathways around all behaviors which lead to running, an effect which was mediated by dopamine release. It is possible that they have also downregulated dopamine in the process, requiring them to run everyday to sustain a sense of motivation, but this is likely independent of the original benefits they experienced from running. So it may indeed be compulsive, and may even be a problem, but it isn’t because they “pressed too hard on the pain side of the scale” per se.

We can also consider another example which Lembke herself brings up in the book. There is a drug called Naltrexone which acts as an opioid antagonist, meaning that it blocks the opioid receptors and prevents their activation. The drug was originally developed for the treatment of acute opioid addiction, since you can’t get the benefit of taking an opioid if it can’t make it to its target in your brain. What has been more recently discovered is that taking a daily small dose of naltrexone has the capacity to up-regulate the opioid system by taking just a little weight away from the “pleasure” side of the scale and forcing the nervous system to compensate by putting less of its own weight on the “pain” side. Importantly, there is no evidence that anyone has developed a naltrexone addiction, even though people report significant benefits to their wellbeing from taking the drug. This is because dopamine release is not involved, and thus the behavior of taking naltrexone is not reinforced.

The Good Life is About More Than Dopamine

Turning again to the title of the book, it is true that we now live in a world filled with “better-than-expected” experiences of all forms. We are constantly having our thoughts and actions sculpted by releases of dopamine which subtly rewire our neural circuitry. What we can lose sight of however is that there is a more primal reason why an experience is “good” or “bad” in the first place, and it often doesn’t directly have to do with dopamine. In this article I have been using examples of physical pleasure and pain, but as social animals, we also intrinsically value connectedness and bonding. We are often even willing to forgo personal pleasure in order to raise a family or maintain friendships, and we often experience these as kinds of pleasures that are deeper and more rewarding as a result. These social pleasures are in part mediated by endogenous opioids, oxytocin, and other non-dopamine neuromodulators.

Indeed, beyond the opioid system we discussed here, there are a number of other essential neuromodulators which are implicated in addictions of various kinds. One of the other primary ones is the GABA neuromodulatory system, which is involved in inhibiting activity in the brain. Returning to our see-saw metaphor, we could understand the GABA system as mediating the calm/anxiety axis. The class of drugs called benzodiazepines, which Xanax and Klonopin fall under, is often prescribed for anxiety disorders. Unfortunately, the GABA system is just as sensitive (if not more-so) than the opioid system to external stimulation, and can become easily downregulated, resulting in a difficult withdrawal experience if GABA-ergic drugs are not used carefully and sparingly. Serotonin is also essential to healthy brain function, but its effects are more complicated and don’t easily map onto a one-dimensional axis like the others we’ve discussed here.

In recent years I have come across popular discussions of dopamine and dopamine fasting most frequently in the context of social media and smartphone use. Social media notifications cause dopamine release in our brains not because they are rewarding in themselves, but because they signal social cues which are what we truly value at the most basic level. No amount of social media fasting or cold showers, regardless of how good they are for our dopamine systems, will help us with the more underlying problem of not having our more fundamental needs as humans met. I think that it is this unfortunate truth which is a little lost in Lembke’s book. We may be living in a “Dopamine Nation,” but if we are to become a happier and healthier society, we need to do much more than merely get our dopamine levels in check.

FYI, this article will discuss spoilers for the (now twenty year old) game. I figure that enough time has passed since release that anyone who wanted to play the game has had a chance by now, but maybe you are one of the holdouts.

As its title suggests, the Kingdom Hearts series has a strong thematic focus on the role of the “heart” in human experience. The first game introduced a type of being called a “Heartless.” These are evil creatures that try to collect the hearts of living beings. They typically take the form of shadowy figures that have the appearance of demons or monsters, and are the main type of enemy which the player battles throughout the game. In Kingdom Hearts II, the Heartless make an appearance again, but a new type of supernatural entity is also introduced called the “Nobodies.” Unlike the Heartless, which appear exclusively as monsters, many of the Nobodies look indistinguishable from regular humans. The only difference is that they don’t feel or experience anything. Within the game, Nobodies go so far as to describe themselves as “not existing,” or “not being real.” This sets up the main narrative arc of the game, in which Nobodies go to great lengths to sacrifice whole worlds in order to attempt to gain that reality back for themselves.

It is important to point out that Nobodies are not simply lifeless shells. From all appearances, they act as if they have thoughts, emotions, dreams, and desires, just like anyone else. When you hear them speak in the game they have passion in their voices. But on the inside there is nothing. To use more technical language, these beings lack any form of phenomenal consciousness or subjective experience. To paraphrase the philosopher Thomas Nagel: there is nothing it is like to be a Nobody. One could also say that they are non-sentient beings. All of these amount to more or less the same thing, but reflect different language used by different philosophers of mind over time.

The philosopher David Chalmers called such beings which behave just like us but lack subjective experience philosophical zombies. In a now famous thought experiment he asks whether it is possible to imagine a world which is exactly like our own, except that no one has any subjective experience. Since posing the experiment, there has been tremendous debate within the field as to how best to answer the questions that it poses. For his part, the creator of Kingdom Hearts, Tetsuya Nomura, explores the implications of this experiment through the narrative of his game, albeit with some important differences; namely that the Nobodies live in a world in which there are plenty of other beings which do have subjective experience.

Questions about the relationship between believably human behavior and the presence of true subjective experience have been raised again in recent years thanks to the advances in Large Language Models (LLMs). These AI systems can now, at least through a chat interface, convince a non-trivial number of people that they are real humans. This suggests that the famous test of artificial intelligence posed by Alan Turing may be close to being resolved positively. It is true that a sufficiently long conversation with even the best current LLM will expose that it is not actually a human, but it seems that even this final hurdle will likely be crossed in the coming years.

This raises the important question of how we are supposed to relate to such entities as LLMs and whatever their successors will be. While some people have taken this ability for humanlike communication as evidence of subjective experience, the mainstream position is one of much greater skepticism. I personally believe that while some future AI system built on a very different substrate than silicon and using a very different architecture than a von Neumann computer might one day be conscious, the current generation of LLMs are almost certainly not. If this is true, it then raises the question of whether AI systems themselves will actually know that they aren’t conscious. There is an interesting line of research developing which studies LLMs’ capacity for self-reflection. Through it, we are starting to find out how much these models actually know about themselves. For example, it seems that a model that is bad at writing code will actually know that it is bad at doing so. Whether this extends to the metaphysical plane is a much bigger unanswered question.

At this point one might ask: if current LLMs are not conscious, and are unlikely to be conscious in the near future, then why should we care? We can return to the Nobodies for additional insight. As I mentioned above, these beings act just like humans would. At one point in the game the player encounters a Nobody named Axel. Without getting too deep into the intricacies of the plot (which would require an essay of its own), Axel is trying to find his best friend, another Nobody named Roxas who has gone missing. From all appearances, it is apparent that Axel has a strong emotional connection to his missing friend. Yet, as Axel himself admits, neither him nor his friend truly exist. Neither of them are conscious in the way that even a goldfish is. Even though I knew that these Nobodies lack subjective experience, I still found myself incredibly sympathetic to them and their plight. Why shouldn’t they be allowed friendship? Axel was acting at least as passionately about his plight as any person I’ve ever encountered.

What was going on in my mind as I related to Axel and the other Nobodies while playing the game? It seems that the expression of emotion and desire, along with the intentional attempt to satisfy those desires was enough for me to feel something for the Nobodies, even perhaps to root for them on some level. This recognition of relatable, coherent, and complex goals along with consistent long-term action towards achieving those goals was enough for me to grant to the Nobodies a level of recognition that I would normally be reserved for a real human. Returning to our world, some philosophers believe that the criteria I just described is sufficient to grant something called moral patienthood to future AI systems. Moral patienthood doesn’t recognize an entity as being conscious or sentient, but rather simply acknowledges that we should act morally towards it to some extent. Such a moral recognition could be codified into laws, or simply become a kind of custom which we adopt.

There is a very practical reason for granting non-sentient beings which look, talk, move, and behave just like humans some degree of moral consideration. If we did not, then humanity would collectively develop a habit of acting sociopathically. When you can’t tell without some kind of external verification whether someone is “really conscious” or not, it seems likely that the best course of action is to act as if they were anyway, since in such instances a false negative is much worse than a false positive. Unfortunately for the Nobodies in Kingdom Hearts II, they all wear conspicuous black robes and constantly talk about how they aren’t real and don’t have emotions, both of which are easy giveaways. It seems unlikely that future AI systems which we interact with will be quite as obvious to spot, unless of course they have the capacity to self-reflect on their own lack of sentience. Regardless, there is still an argument to be made that their expressing desires and emotions is enough to grant them some consideration. We see a version of this happening in very simple ways even today, with many people who use LLMs telling them “thank you” after being provided with useful information.

At the end of Kingdom Hearts II, the problem of non-sentient humans is resolved through a series of climactic and flashy battle sequences in which the group of Nobodies and their leader are all defeated by the game’s protagonist. In the real world however, our collective adjustment to the existence of our own Nobodies is going to be much messier and drawn out, requiring changes at various levels of culture, economy, and politics. It is clear that the technology which makes AI possible will continue to become increasingly advanced, and as a result will become increasingly humanlike. Many AI “thought leaders” have declared that 2025 is the “year of the agent,” meaning that AI systems will start to have long-term goals which they attempt to actualize. This agentic behavior combined with remarkably human-like verbal communication will soon put us in a place where it will be difficult to avoid questions of how to regard our artificial interlocutors. In the world of Kingdom Hearts all the challenges that the protagonist faced were resolved through the use of his magical weapon, the Keyblade. I am afraid that for us things won’t be so simple.

A preprint on arXiv has been making the rounds this past week called Gradual Disempowerment: Systemic Existential Risks from Incremental AI Development. As the title suggests, the article explores the ways in which humanity may experience a slow and gradual loss of control over its future as AI (and eventually AGI/ASI) becomes increasingly advanced. This is in contrast to the more flashy and headline-grabbing rapid AI takeover scenario which is so prominent in science fiction. The article argues that as AI becomes increasingly advanced, we will hand over more and more of our economic, governmental, and cultural functions to these systems. In doing so, humans will be giving up more and more control and collective agency, until we eventually find that we have lost it completely. Is it that straightforward though?

According to the authors, what has maintained human agency so far is that on the whole humanity is currently “fairly aligned.” Our existing economic, governmental, and cultural institutions are operated by humans, so on some level they reflect human values as such. The authors admit that there is some controversy around the notion of fair alignment. In some ways the history of human civilization, which is filled with slavery, oppression, genocide, and conflict, is an attestation against this proposition. Still, it is clear that human institutions at the very least empower humanity as a whole (tautologically so). While I agree with the authors that a gradual disempowerment of human institutions due to AI development is likely, I also think it is just as likely that individual human empowerment may be drastically increased at the same time. Notably, this seemingly paradoxical situation is in some ways the inverse trend to what has taken place for most of human civilization’s history.

It is incontestable that technological development throughout history has enabled civilizations as a whole to gain more and more empowerment over the forces of nature. We can build structures which withstand hurricanes, earthquakes, tornadoes, and extreme temperatures. We can predict the weather anywhere in the world over a week in advance. We can fly people en masse from one side of the world to another in less than a day; and we can build towers which reach up into the heavens. We can cure diseases which have plagued humanity for centuries, and in our most symbolic triumph, we proved capable of sending people to the moon. All of this enables humanity as a whole to deal with problems and threats to our collective survival and flourishing in ways that would have seemed like magic a few centuries ago.

However, if we zoom in from the civilizational level to the personal or group level, the track record for maintaining and encouraging human agency is much more complicated. In the previous two centuries, significant progress has been made to enfranchise more people into collective decision making. It is also true that in theory, individuals in liberal democracies are free to pursue their goals and dreams in a relatively unencumbered manner. In practice, however, the amount of agency which anyone can exercise is often directly tied (and increasingly so as time progresses) to the amount of personal wealth at their command at any given moment. In western industrialized nations we feel this acutely in the current affordability crisis in which the ability to own a home, even an incredibly modest one, is outside the reach of large numbers of people.

Even individuals with wealth currently find themselves constrained in countless ways by the ever-increasing number of laws and regulations of states, many of which are supported and enforced by increasingly advanced and intrusive surveillance technology. Outside the niche of crypto, it is currently near-impossible to conduct a legitimate economic transaction without it being monitored and subject to censure. We could also take the case of individuals who are fortunate enough to own a home, yet are still subject to the arbitrary regulations of a homeowner’s society. Many such homeowners find that they cannot even freely choose the color of a house they own or the height of a fence. We may collectively agree that any one of these rules are desirable for the maintenance of social harmony and the collective good, but it is undeniable that their cumulative effect is a restriction of personal agency.

The physical constraints on our behavior in modern society are matched or even perhaps exceeded by the more invisible constraints on our psychic freedom, which are often much less noticeable for their all-encompassing nature. We have spent the previous twenty years having our attentional systems rewritten by smartphones and the modern internet. This rewrite has largely been in the service of maximizing advertising revenue for social media companies, and certainly not in service of maximizing individual agency. What we think and believe is often now the result of rapid memetic transfer of someone else’s ideas or beliefs through social media. This is in contrast to the world of twenty five years ago when the stationary TV or desktop computer only had influence for those within physical proximity to it. This is to say nothing of the world of the 19th century and earlier, before mass communications media even existed.

Given the current state of individual and collective human empowerment, how might sufficiently advanced AI change things? It certainly does seem to be the case that society as a whole will likely face the kinds of disempowerment that the article describes. As we hand over more and more high-level decision making to machines, this naturally implies that humans themselves are no longer the ones making those decisions. We will do this because at each step, it will be easier and more efficient to offload to the AI what it can do better than a human, or ensemble of humans. In the same way that we’d find it absurd to rely on humans for some essential arithmetic tasks in place of a computer, the same logic will apply to cognitive tasks and AGI in the future.

If it is unclear whether AGI decision making will be misaligned, yet clear that more disempowerment is likely, the question then becomes: is disempowerment something to be avoided? Is it possible to imagine a scenario in which humans are indeed disempowered, but still happy and content, because the empowered AIs act unfailingly in the service of human interests? We can take the example of a pair of loving parents caring for their newborn child. The child clearly has little to no agency, yet all of its needs are taken care of and it is nurtured. The child is even happy, and free within its own domain to explore and interact with the world. The same logic applies to a human and their pet. Here again, in the greater scheme of things the pet has little agency, yet is still content so long as all of its needs are met.

Understandably, people recoil at the thought of becoming mere pets. Even I did, as I wrote the above. This aversion to losing our personal agency is not something new. It has a long history, one that mirrors the historical process by which individuals have become increasingly disempowered relative to societies as a whole. In particular, we can look to the effects of the industrial revolution in the 19th and early 20th centuries. This was a time when new forms of social control were being developed and spreading alongside the technological developments which made them possible. Although the works of authors during these times are perhaps not representative of the average person’s experience, their lasting appeal over a century later attest to their speaking to something fundamental in human nature.

In Notes from Underground the great Russian writer Fyodor Dostoevsky explores the problem of individual agency through a thought experiment concerning a utopia. If a society could be developed in which all of its members’ needs were met, would the members of that society be happy? Dostoevsky answers this question with an emphatic “no”. He goes so far as to contend that it is in human nature to prefer to destroy such a society simply for the sake of being willing to assert one’s own independence from it. This desire for individual freedom, even when destructive, irrational, and serving no utilitarian purpose, is something he sees as superordinate in the human spirit over almost everything else. We find a similar theme a few decades later in Aldous Huxley’s classic work Brave New World in which an impassioned case is made for the freedom to act irrationally and (dare we say) humanely, in the face of an increasingly automated and regulated society. This anxiety around losing individual agency is also perhaps why the Gradual Disempowerment article has resonated the way it has with so many people in recent days.

Is a soul crushing disempowerment at the ‘hands’ of AI truly our fate then? Or are there opportunities to be had in this coming phase shift? Although institutions can and perhaps have a moral obligation to have their control turned over to systems capable of running them most efficiently and beneficially, I believe that for individuals themselves personal agency has the potential to finally be able to mount a comeback. Coincidentally, Sam Altman shared a blog post recently containing some predictions about the societal changes AGI will bring. One of the things he highlighted is the fact that as intelligence becomes orders of magnitude cheaper than it is today, the ability for the average person to act in the world may very well increase rather than decrease. His argument goes that if you had the equivalent of a 10,000 person company of PhD-level knowledge workers at your command for $20/month, then you could clearly accomplish much more than you could today by yourself. Dario Amodei has made a similar argument recently, suggesting that anyone in the world will soon have access to “a nation of geniuses” to act on their behalf.

Of course this picture of super-powered individuals is complicated somewhat by the fact that in this scenario nearly everyone else will also have such resources. Governments will also have surveillance technology far beyond what they do now, and it may be of greater efficacy than what is available to individuals for the purposes of counteracting it. Regardless, it certainly will not be an entirely zero-sum situation, especially for any undertaking which is outside the domain of interpersonal competition. So much of what prevents people now from acting truly agentially is that they do not know what actions to actually take in order to make a difference in their lives. Some cannot see the openings which genuinely do exist. Or, even if they do see them, they may not have the ability to navigate them successfully. Consider today’s millennial would-be homeowner who finds themselves currently disempowered to the extreme. For most, the notion of finding a plot of undeveloped land, building a house, and supplying it with water and electricity (and doing so affordably) would be a daunting task. It is easy to imagine how, with the help of a couple dozen super-intelligent entities, it would become trivial.

In summary, my contention is that as humans we clearly care deeply about empowerment. Although AI will involve handing more institutional control over to AI systems, those same systems have the potential to empower individuals in radical new ways as well. That said, I can’t claim to know what will happen in the coming decades any more than anyone else. In large part thanks to the pioneering work of Ray Kurzweil, people often talk about a ‘technological singularity’. The analogy to a black hole’s event horizon is apropos, but not for the reason people often assume. The vernacular understanding is something like: technological development beyond a certain point will advance at a near-infinite rate. I think that a more fruitful way of thinking about the singularity is that it is a point beyond which advancements in technology will be such that it becomes difficult-to-impossible for us to see beyond it. This is because advanced AI will not just change one part of society at a time, but rather all parts of all societies at once, and in complex and chaotic ways.

On the one hand, it seems more important than ever to exercise epistemic humility. We simply do not know what in particular the technological developments in coming decades will bring. Anyone who claims to have certainty about the future has not thought very deeply about the pervasive implications of commodifying intelligence. On the other hand, we can and should marshal all of our collective resources to ensure that whatever does happen has the greatest chance of benefiting as many people as possible; both by ensuring their needs are met, and by safeguarding (or even increasing) their freedoms. In that sense, the Gradual Disempowerment article is part of a necessary conversation. Many more perspectives and voices will be needed though in the coming weeks, months, and years. As we invent the future, it is critical to ensure it is the one we want.