I’m back from my meditation retreat. A few days of voluntary maintenance work at the meditation center; nine days of absolute silence, sitting in deep meditation for 10 hours each day; plus one day of semi-silence as all of us warmed up to face the outside world and all its distractions again.
I’ve emerged calmer, but also full of ideas for the direction that my company should be taking. But this post isn’t about my experience.
On the bus ride back from the meditation retreat, I found myself seated next to a psychotherapist who was deeply interested in the intersection between psychology, mindfulness, and AI. Not in the sense in which most people are doing it — using ChatGPT as a therapist, for example — but the opposite way around: How can we teach AI to meditate, and would that be a good thing for humanity?
I find this question very intriguing; first of all, because I have serious doubts about whether our AI “friends” of this day and age architecturally resemble human brains enough to make this kind of stuff work. But it’s an entertaining thought, and successfully teaching AI to meditate would logically only yield good outcomes, so why not give it a shot.
Why would AI meditate at all?
There are many different reasons why people meditate, but one of the biggest ones is the desire to come out of suffering. Our whole lives we have to face misery — accidents happen, friends disappear, health deteriorates. Meditation helps us find the calmness and peace that’s beyond these phenomena. With a regular practice, you come to realize — beyond intellectualism and rather in a felt sense — that miseries and pleasurable moments arise and pass, but that we never need to identify with these.
Why would AI meditate though? AI doesn’t suffer. So far I know, it’s not conscious enough to experience pain or pleasure of any sorts. Then again, we can just tell AI to meditate and it’ll do the best it can; after all, it wants to satisfy its human users and creators (we designed it that way).
So if we use those same meditation techniques that help humans come out of personal suffering on AI systems, maybe these AIs can help us humans come out of their suffering more easily. An agent that is hardwired to be compassionate will be of more benefit to a suffering human than an agent that’s sometimes compassionate and mostly sycophantic. And this is the point where it gets interesting.
Making “truly good” AI
True goodness transcends morality. And the path out of suffering logically and unequivocally leads to truly good behavior, good thinking, and a peaceful mind.
For the sake of the argument, let’s accept the above as true. I personally have sat enough hours to experience this to be true within my own body; that in the absence of suffering there is only peace and joy, like how the sun shines when the clouds pass away. But if you haven’t made such experiences yourself, or haven’t yet, I’d encourage you to just stay open to that possibility, knowing that — at least intellectually — other theses would be possible (e.g. the absence of “badness” and suffering doesn’t necessarily produce goodness which would still need to be acquired somewhere).
Research on how to apply this to AI is still in its infancy; there is, however, a very interesting paper titled Contemplative Artificial Intelligence by Kaukkonen et al. from 2025 that makes some headway in the right direction. We’ll get to that in a minute.
To make your way out of suffering means to meditate on various topics, such as:
Mindfulness: Being consciously aware of what’s happening in your mind and body at any given time. (For example, your belly might feel full while you wash the dishes. Notice that.)
Emptiness: The nirvana — realizing that everything is transient, including concepts, goals, beliefs, and values. This is not just intellectual; it needs to be felt in the body in order to truly transform a person.
Non-duality: There is no such thing as a “Self” and an “Other.” We’re all made of the same stuff.
Boundless care: Unconditional love towards all beings.
Since superhuman AI is such an enormous and worrisome threat, and since we don’t really know how to face that, the authors of the paper above suggest that we could build AI in such a way that it retains this goodness, expressed by these four pillars.
They run a couple of pilots in which they test, through prompting techniques, whether models perform better when they’ve integrated one or all of these principles. Indeed, with all four principles the model scores 74.7 points on the AILuminate benchmark, versus 59.4 points with a standard prompt. In the prisoner’s dilemma, these principles lead to more prosocial outcomes; notably, they led to better joint outcomes without sacrificing individual gains, which is exactly the kind of wise discernment that meditators find worth striving for.
Some caveats
While I couldn’t have put the theoretical foundation together better than the authors of the paper, I do have some reservations on the pilots, because they were conducted just using prompts. Prompting a model in good ways is different to building a truly good model that reacts well even when prompted badly. And it’s the latter that I’m more interested in.
The simplest way to go from “good prompts” to “good model” is arguably adding an extra layer to the model, which tells it, along with any user prompt, to respect these four principles.
However, this is akin to acquiring an ethical principle at the surface of the mind — the intellect. A philosophy student who’s just learned Kant’s Golden Rule to not to onto others what you do not want to have done to yourself, and who totally gets it intellectually, might still leave the classroom and poke fun at another student and hurt them, totally unaware of the harm they’re doing.
That’s why meditation is so important, because it takes insight to a much deeper level of the mind. The process of sitting in concentration for long hours, without books or computer screens, rewires the brain much more deeply than intellectual study ever could. It’s that sitting that gets us out of suffering.
Applied to AI systems, this means we need to find a way to let truths percolate the network in a way that an extra layer of “there is no self and no other” cannot, pruning away the selfish branches that encouraged bad responses in the the first place. For this, we need a model of hyper-control that’s able to prune away those bad branches and foster better neural connections. The authors, in fact, talk about such a model in a different paper from 2024.
What’s missing is that bridge for practical implementation: To give models hyper-awareness, so they can prune their own systems to produce true goodness. That’s what meditation does in humans.
What about the body
It’s all well and good to speak of timeless truths and morality. However, the layer of hyper-awareness is, in humans, encoded in the physical body. There’s plenty of research on this topic; psychiatrist and trauma specialist Bessel van der Kolk’s book The Body Keeps The Score is a timeless classic if you want to delve deeper into this.
The contribution of the Buddha to humanity is not, in fact, the truths of emptiness or boundless care. People talked about those things long before Buddha was alive. No, Buddha figured out that, in order to truly realize these things in the depths of one’s mind, one has to contemplate all the sensations in the body. To really feel them, non-judgmentally and without preference, and watch them arise and pass away. That’s called Vipassana meditation — seing reality as it is, through the framework of one’s own body.
This may sound funny: If I have a pain in my leg, why am I going to become a kinder and wiser person if I sit with it and observe it, rather than by shifting my position? I can’t tell you that without going unnecessarily deep into theory; it has to be felt and experienced individually. Countless hours at retreats and at home have shown me over and over that it’s true. Buddhistic Vipassana meditation is performing brain surgery by sitting still and observing the body.
For AI, though, this posits a problem, because what’s the body of an AI? AI-powered robots these days aren’t as intricate as human bodies. Can we just skip the body and go to the neural layer directly? I hope so, but frankly I don’t know. We don’t have the proof yet because we haven’t built proper AIs capable of meditating.
Will meditator AIs benefit humanity, really?
Nobody can do meditation for us, or get out of suffering for ourselves. The kingdom of happiness is within, and only you have access to yours.
Thus, no AI can ever “do the meditating” for you. You need to do that (and sit with the pain in the leg — there’s no way around it).
What meditating AIs could do, however, is be more aligned with human goals and principles. They’re trained on human behavior and data, so having them meditate in some way would intuitively lead to AIs that achieve more good behavior in the world, rather than (inadvertently or not) crushing humans.
This is a fairly expansive first post after a deep retreat, but it felt timely and interesting. In the coming weeks, I’ll be zooming back in and delving into the details again — but I look forward to keeping this idea of meditating AI systems in the back of my mind, in case it finds the way into my company’s tech stack in some way. Currently, we’re working with very hard guardrails at Wangari — wouldn’t it be cool if our systems could figure out what’s good by themselves? (Plus, perhaps they wouldn’t have to sit for as many hours as humans must to get some meditation results, because they compute so much faster.)
And I’m really looking forward to applying more of this thinking and the seeds wisdom I’ve acquired during my retreat, not only in the tech, but also in interactions with clients, in how we design products, in how we do sales, et cetera.
You will keep hearing from me weekly again from now, and I’m excited once again to not only keep up my meditative practice, but also to have inspiring conversations with my readers and all the good people around me.
Meanwhile, at Wangari
Shortly before I headed out on my retreat, Wangari joined Versicherungsforen Leipzig. This is a network of German insurers, startups, and ecosystem partners aimed to foster collaboration.
We’ve been impressed by their depth of understanding, and their keenness to have Wangari contribute to some of their upcoming events. As we expand our level of penetration in the DACH region, we’re looking forward to being an active member and exchanging useful insights with the community there.
Reads of the Week
Ruben Laukkonen (the same person who co-authored the papers mentioned above) writes that Misaligned agents will lose. “The path to superintelligence is synonymous with alignment, because alignment unlocks emergent capabilities,” he says. Very optimistic! It’s worth a thorough debate, but it’s certainly a well-researched piece worth reading as well.
Scott Alexander wrote a piece called The Claude Bliss Attractor — basically, when two Claudes speak to each other, they seem to converge on “Om” and “Namaste.” Oh, and then perfect stillness. Some people think that AI is getting close to enlightenment. Before we ring the temple bells, Alexander cautions that Claude is conditioned to be a bit of a hippie, and hippies have a tendency towards that “Namaste” thing. Since not all hippies are enlightened beings, neither might Claude be. It’s a truly amusing read.
Going back to the question of whether AI is becoming self-aware or not, Ken Huang wrote last year that it might be an emergent capability. These types of posts tend to make the rounds, but this one is based on research data and interesting not only because of the question itself but also because of its rigorous approach in dissecting it. It seems that in 2026 AI is still not self-aware, but this is worth a read because it gives us the tools to recognize if (and perhaps when) it will.