Technology, Connected - Machines of Loving Grace - Dario Amodei

Episode Date: July 8, 2025

In Machines of Loving Grace, Dario Amodei imagines a future where artificial intelligence works exactly as intended: curing disease, ending poverty, and giving humanity everything it ever wanted.Mark and Jeremy break down that vision: a “country of geniuses in a data center,” where AI drives biology, neuroscience, economics, and governance to their limits. They examine the optimism, the blind spots, and the moral cost of progress that moves faster than culture.Because even if AI gets it right, the question remains, can we?Please enjoy the show. And share with a curious friend.--Read the essay: https://www.darioamodei.com/essay/machines-of-loving-grace#fn:1--Follow and Support Thinking On Paper🎙️PODCAST: www.thinkingonpaper.xyz📸 INSTAGRAM: https://www.instagram.com/thinkingonpaperpodcast/X: https://x.com/thinkonpaperpod--Chapters(00:00) Machines Of Loving Grace(02:46) Dario Amodei's Definition Of Powerful AI(05:11) Speed Of The Outside World(07:24) Complexity(11:27) List Of Diseases AI Will Cure(13:46) Neuroscience And Mind(15:45) AI For Everyone?(21:33) Peace And Government(25:03) Work And Meaning(31:56) What's Meaningful?(34:27) Taking Stock--Connect the dots of AI, quantum and emerging technology and watch these videos next:

Disruptors and Curious Minds, CEOs, welcome to Thinking on Paper. I'm Mark. This is Jeremy, and this is Pocket Edition, a smaller, more concise, more succinct exploration of one article, essay, news story, controversy. Jeremy, what do Anthropic? Why are they important? Why is what Dario Amudi says important? He's been at OpenAI, VP of Research.

He left to start Anthropic. Anthropic is Claude. In one thing that caught my ear during an interview that I listened to, was that he thinks the number one skill for people moving into the age of AI is open-mindedness. If there wasn't even AI, that would be like the number one thing. But that caught my eye and then kind of there lived the rabbit hole. We found this essay, Machines of Love and Grace. Again, a great title.

We've been exploring the difference between silicon and carbon consciousness and machines. And I was like, man, this could be a really interesting thing to unpack. It's an essay called, as you said, Machines of Living Grace by the CEO of Anthropic. premise of the essay is the upside of AI. It's like what would a world with powerful AI look like? If everything goes right, and that's the key of the essay, so everything goes right. It's based on a poem by Richard Broughtigan, a key figure in the counterculture movement, belongs in the same lineage as the beat mix as Carowack and Burroughs, Ginzburg. And he wrote a poem called All Watched Over by Machines of Loving Grace. I'm going to read it. I like to think, and the sooner the

better of a cybernetic meadow where mammals and computers live together in mutually programming harmony like pure water touching clear sky. I like to think, right now please, of a cybernetic forest filled with pines and electronics where deer stroll peacefully past computers as if they were flowers with spinning blossoms. I like to think, it has to be, of a cybernetic ecology where we are free of our labours and joined back to names. return to our mammal brothers and sisters and all watched over by machines of loving grace. That's where the title from the essay came from. The premise, what will a world of powerful A look like if we can ever think right?

What's the first thing he gets into? He's very distinct about calling it powerful AI and he talks about defining intelligence. He thinks about intelligence is problem solving across domains. Well, let's read the whole, his actual definition of powerful AI from, so we know where we're based in this. So by powerful AI, I have in mind an AI model, likely similar to today's LLMs in form, though it might be based on a different architecture, might involve several interacting models and might be trained differently. But it has the following properties. In terms of pure intelligence, it is smarter than a Nobel Prize winner across most relevant fields,

biology, programming, math, engineering, writing. This means it can prove unsolved mathematical theorems, write extremely good novels, write difficult code bases from scratch, etc. In addition to just being a smart thing you talk to, it has all the interfaces available to a human working virtually, including text, audio, video, mouse and keyboard control and internet access. It can engage in any actions, communications or remote operations enabled by this interface. It does not just passively answer questions. Instead, be given tasks that take hours, days or weeks to complete and then goes off and does those tasks autonomously in the way a smart employee would. It does not have a physical embodiment other than living on a computer screen, but it can control existing physical tools, robots or laboratory

equipment. And the resources used to train the model can be repurposed to run millions of instances of it. Each of these million copies can act independently on unrelated tasks or if needed can all work together in the same way humans would collaborate, perhaps with different subpopulations, find tuned to be especially good at particular tasks. We could summarize this as a country of geniuses in a data center. And he's going to be focusing on the positive applications of AI across five domains, biology and physical health, neuroscience and mental health, economic development and poverty, peace and governments and work and meaning. Scene set. He talks about two extremes of where people think this whole thing is heading.

As with many things, it's not this or that. There's various stages of in-between. It talks about the one extreme being the singularity. The machines are smarter. They're doing everything, and we're doing our best to kind of hang on. And then the other piece of it is, hey, tech's not going to progress that quickly. There's significant limitation. Between that, he suggests some new frameworks, I think, that are really interesting.

Let's go through them one by one. And then we can hit on all of these five areas that he thinks will be impactful. So speed of the outside world. These are things that any applied intelligence needs to rely on to act and do their thing. You have slower systems, like human systems that are involved that will slow down what AI can do super speedy because we're the bottleneck. Think about current systems. Think about hardware. Think about gaining consensus, how hard it is to gain consensus in a, in a job.

giant group of people. Social systems are a bottleneck. No matter how fast we get, when we apply AI to solutions to social issues and social, like societal issues, we're still going to be the bottleneck. And the same thing applies when you're using this, the AI to solve biological problems. For example, you want to find a cure for cancer. AI is going to help us find a cure for cancer. I can't change the laws of physics. The tests still have to be run. The experiments still have to be run. The results still have to be found. They're still, and what equals like an irreducible time for certain things. As you said, on the cultural front, you have us people. We're like oil tankers, you can't move us on mass. It takes time. And when you're doing, using AI to solve

medical issues, there are certain time limits that it cannot supersede. And I think it's very important in the conversation when everyone goes, AI is going to save the world and AI is going to save climate change. And AI is going to do this and do that. It has to work within the limits of what can happen. And as we've spoken about a lot on this show, Jeremy, you can't change time. The invented construct. Yeah. Right? Need for data. Yeah. What's the, what's the fuel for all of these models? It's, it's data. And not all data is

created equal. And parsing through that to, to make it a good input for the model is pretty challenging. So is there going to be a limit to data? Yeah. The example he uses, he uses for physicists, particle physicists, and particle accelerator data. is limited. There's only so many times you can bash atoms around a particle accelerator and get the results from that. So data is limited and that connects nicely to the speed of the outside world. Intrinsic complexity. I know that this is your favorite specialized subject, Jeremy, complexity. Well, is this complexity as defined by Julio Otino, complicated versus complex. I think it aligns with what he thinks about that. What I wrote here is AI is marginally better at working on chaos.

systems like the three body problem. So this goes back to return on intelligence. If we point AI at problems that it's currently not better than we are at solving, that's, you're not getting the best return on the use of that AI. Humans in the loop again, pointing AI to the right problems that it can be successful at solving quickly, efficiently. Is that where you landed on this? It's funny. I was thinking of Nexus as well with Julio. And I remember one of the book club episodes. We spoke about complex systems and there was this idea of, it was a shoal of fish in a very small area of seawater off the coast of Canada and the interactions between these fish and the food chain

and how quickly it just exploded exponentially into mind-bending numbers. It was literally a few square metres of water. AI just simply cannot process this equals that equals that to a ridiculous amount that needed. Although I do bring into that this, the intrinsic. complexity returns to intelligence, which he mentions as a hamperer to what could possibly be achieved with AI. I have two words for him, quantum computers. There's a little repetitive nature between human constraints and physical laws and speed of the outside world. I think that the need for data

and intrinsic complexity kind of stand on their own a little bit. Let's dive into the first of these five areas. Biology and Health, we've always heard about the idea of this. Making new drugs is a very brute force process. You know, it's, it's test this thing, push it through, see what happens. Test this thing, push it through, see what happens. And then there's also the bureaucracy on the other side of it. We get, we get, we get, we get, AI's going to cure cancer. It's going to make us all live longer. I think perhaps he's been drinking the Brian Johnson Kool-Aid and he, that's the Silicon Valley obsession with longevity. Maybe it gets more importance here than it perhaps would elsewhere. Maybe not. What I found really interesting is how it explains why the AI will be so net positive and very quickly.

We probably should have mentioned this earlier, but in Machines of Loving Grace, he's painting a very short window of like five to ten years of what, if this goes right, AI will produce. He says that historically it's a very small number of discoveries which have created the biggest impact. You have one small discovery and it's a tidal wave of impact everywhere. else that these discoveries major discoveries each year drive i think he said 50% of the progress in biology examples of these could be crisper which which has been out there i didn't know that the idea of crisper was known since the 1980s but it took 25 years to apply it it's like this this idea kind of has to sit and have its aha moment but you know what maybe it doesn't with AI that's the thing maybe there's lots of discoveries like that which are sitting under our noses right we just don't

have the, we haven't clicked yet, we haven't found the little missing ingredient. AI will help find that missing ingredient. He talks about speeding up the discovery of the big discoveries. AI can, you know, speed up 10x that and get those aha moments, those eureka moments, more, you know, easily. Engineered serendipity is a really interesting, interesting thought. Quote, it's my guess that powerful AI could at least 10x the rate of these discoveries, giving us the next 50 to 100 years of biological progress in 5 to 10 years, and then why not 100x?

The idea of the compressed 21st century is what he refers to in here, and it's what you're saying. Instead of something happening in 50 to 100 years, we're creating a scale where that could possibly happen in 5 to 10 years. Just quickly before we move on to neuroscience and mind, for anybody wondering exactly what he thinks, we got in the next 5 to 10 years, if all goes well, reliable prevention and treatment of nearly all natural infectious disease. elimination of most cancers, very effective prevention and effective cures for genetic disease, prevention of Alzheimer's, that's a big one, improved treatment of most other ailments, biological freedom, doubling of the human lifespan. So yeah, good news. Biological freedom was a little face melting maybe a little bit. It's just the, you know, the idea of like, man, are we all going to become, like, be able to become Marvel superheroes

down the road? Like, that's where my head immediately went with that. But I thought that was the one that was like, oh, that's kind of... I know he gets into the culture later, but it's about augmenting humans. Like, doesn't he say you can choose what you want to be? So I want to be bigger, faster, run, Marta, you know, okay, upgrade. It's a bit matrixy. Yeah, a little bit, a little bit. And it's funny because he talks about the idea of we need to, and we'll get to this later,

he talks about the idea of needing to steer away from these science fiction narratives. That sounds like very science fiction narrativey a little bit. But we talk about the doubling of human lifespan. And it's actually interesting. He casts out that like this doubling has happened. It's happened in the past. It's, we've already doubled our lifespan from 1900 to 2021.

So why does it have to stop there? Who's saying that we've hit the limit of that? We need an expert on that. We've doubled the lifespan because I think like we've doubled the lifespan in the last 100 years is dishonest to what actually has happened. And it's not they live longer. They just don't die as early on average. So obviously the what's the difference between that?

Live longer versus dying early. Well, it's statistics, isn't it? You can make a statistic tell you what you want. And the statistics says like the average lifespan has increased twofold because people don't, children don't die in childbirth at the numbers they used to. Disease doesn't kill people like it used to. People don't die on average as early as they once did, which makes the average lifespan appear much longer on average than it was.

If you were born 100 years ago and you didn't die in childbirth, obviously, and you didn't catch any diseases and you didn't injure yourself, is your life expectancy. Isn't that what he's saying, though? Isn't that like solving the things that are making our lives shorter now? Like the things that are in the way of us living longer, it's the same thing in my book. Yeah, probably right. Let's move from all of biology to neuroscience and the mind.

So basically the same framework he talks about in biology, the expediency, the 10xing of progress applied to neuroscience. It's like the 80-20 principle on steroids that. 20% that creates 80% of results is just amplified where AI can just notch that up and 10x that. So what does it look like to win with with AI in this realm? So he talks about being able to work with the fine-grained, he calls it neural measurement, like the things that happen in the brain and the intervention, being able to interact with that information at scale. Talk about complexity.

Talk about intrinsic complexity. You know, mood disorders, psychosis, like what happens in the brain when that goes on? Like we still don't really understand that as humans. And I think the mental health aspects and benefits here are going to be tremendous if AI can help solve that complexity. But is our mood disorders as complex as the three body problem? And is AI going to be good for that? Well, I'm not going to answer that. I have no idea.

But he says, quote, it's my guess that these four routes to progress working together would, as with physical disease, be on track to lead to the cure or prevention of most mental illness in the next one. hundred years, even if AI was not involved, and thus might reasonably completed in five to ten AI accelerated years. I'm not qualified to speak about it, but it's a very ambitious, very, very ambitious claim. I mean, we've been speaking about quantum consciousness. If consciousness is quantum, there ain't no way that you're solving mental illness in five to ten years. I don't care what he says about AI. I think we've got to be careful with that one. Biology, neuroscience, the, this, the ability to scale things, make things happen quicker. Human baseline improves is the idea.

Like the general human baseline neurologically, biologically, can improve because these aha moments are happening quicker. Happy days, Jeremy. So surely this will be available to everybody. Well, there goes the next piece of the puzzle. Access to everything. Will everyone have access to the technologies that let us do this, right? Can I hazard a guess?

Yes, they will. Man, I think that would be tremendous and great, but those wielding and controlling the powers of a new resource, a new asset, we've seen it over the years, control it and can limit access to it to certain areas, to certain economies. I mean, he sets, he sets this stuff out there that back to the human problems, back to the human problems. And he says we've got to put the work in to fix the human problems that will let AI do what it does and have the returns on intelligence that we're hoping. hoping to have and take us to a spot where we can thrive. He uses the GDP example. And this is always a great refresher, just to understand and know, but like the GDP per capita in the U.S. 75,000 bucks, you know, sub-Sahara Africa, is it still at $2,000? Can AI help close the gap? Well, well, theoretically it can, but humans get in the way still, right? Have you ever read a book

called The Economic Hitman? No, sounds good. Man, it was a really, really interesting book at how These developing countries and nations are controlled by larger nations, by those larger nations, inserting leaders and dictators that are corrupt and can be manipulated. AI can't slow down the flywheel of corruption, can it? I mean, he says it himself, if AI further increases economic growth and quality of life in the developed world while doing little to help the developing world, we should view that as a terrible moral failure and a blemish on the genuine humanitarian victories of the previous two. You don't really hear Sam Altman saying things like that, do you?

We should point people to Nexus, and I think we speak about peace and government's next, and we did a 10-part chapter-by-chapter breakdown of Nexus by Yuval Noah Harari. In short, too long didn't read. This idea that the benefits of this technology will be available to all is a pipe dream based on a narrative that is not going to come to fruition, because history has never, ever, ever shown us that that is possible. And when the powers that be, when it's in their interest not to share the seeds of progress with other nations, when it's in their political, financial, economic and cultural interest not to do it, they won't do it.

And it's all good and well saying, oh, AI, is this path to freedom for everybody. But if the powers that be are putting that path up in space, and you need a spaceship to go and get on the path to start walking it, you're just not having it. And I think that this is for all of the positivity and optimism of this essay, like everything, is actually down to the human temperament at the end. Well, he references, like, there's hard work to be done. I haven't done a deep dive into Sam Altman's position and maybe some other people developing AI technologies position on this, but his seems to be, at least with the awareness of the hard problems that have.

The hard problems are not, you know, how to make GPUs connect faster. The hard problems aren't how to, you know, clean up the data to make the training the best. The hard problems are us. We're the bottom, we're the hard problem and the issue. And we're going to be here no matter what happens. Here's the thing. Here's my hot take for you today. So we, we get with the family of Alan Watts and we basically create a model that helps us remind us of our humanity, focusing on empathy, focusing on open-mindedness, focusing on gratitude and having models like that that can nudge us in that right direction or have pieces of these larger models. What if there was a requirement

for a piece of that in a larger model, right? Because anyone can build a model based on anything. Someone can build a model to be an asshole, right? Have this AI be an asshole. It's just like a kid. You train the model. You train it to be an asshole. It's going to be an asshole.

But if you instill the right stuff, not just how quickly you can calculate logarithmic math or whatever the heck it is. It's how much empathy and how much open-mindedness can you instill in these models. And I think that's a bigger thing, but a harder thing. It's messy. That's messy. I think it'd actually be easier to have our AIs, have all of those facets, to be compassionate, to be empathetic, to be culturally aware, to have patience and empathy. On a level that actually is really, really hard to put into the powers that be power corrupts and ultimate power corrupts completely.

We ask this a lot on thinking on paper, like can AIs really be empathetic or is that just a mirage? Is that just they're mimicking us? if they're mimicking those behaviors, but those behaviors are actually acted on. Maybe that's better. Well, maybe so all these models, every interaction is captured by the model. Everyone that interacts with that model affects the future output of the model. So we all have people in our lives that affected us in good ways and affected us in bad ways and sometimes great ways. Sometimes you have someone that comes into your life for a week that really changes your mind,

really opens you up to something even more powerful. So maybe the hope is at least some of those interactions are influencing the model. Unless for some reason the way the model is trained, someone can block those things from having consideration on the overall model, which again is like super scary. But this is all optimum. So I think you're right. And we spoke about the flywheel of corporate greed and how crazy people running asylum.

But you also have the flywheel of economic growth. And it's been proven that economic growth increases all. levels of empathy and compassion. It should fuel that flywheel too. Totally. So as we move into peace and governance, which is the next section, what did you get out of this section? This is the glue that sticks, that keeps all the others together. In machines of loving grace, we get in five, ten shrunken years, we get to this place where AI has. Everything goes right and everyone lives longer. There is no disease. There is economic freedom for everybody. There is biological freedom, whatever that means for everybody. And that all hinges on the governance. He says so himself.

He also says that he is not as optimistic about this one. He says, I see no strong reason to believe AI will preferentially or structurally advanced democracy in peace in the same way that I think it will structurally advance human health and alleviate poverty. Then he speaks about his attente strategy in which a coalition of democracies seeks to gain a clear advantage. even just a temporary one and powerful AI by securing its supply chain, scaling quickly, and blocking or delaying adversaries? What if our enemies are more advanced than us? What if the non-democratic world is more advanced than we are?

How do you, then what happens? Yeah, I enjoyed the callback to Adams for Peace and Eisenhower when like the idea of atomic weapons first came up and it was like, oh shit, like things are going to, things are different. And we got to really think about this stuff. This is very similar to that in a lot of ways and even more impactful, right? So I immediately thought, like, now there's like a nuclear coalition or commission that checks on what's going on from a nuclear capacity or capability across the world. Are we going to have like a central monitoring agency for that? And who is it and who leads it into what benefit?

Well, I'll turn that question back on you then. Who does lead it? That's an easy. That's an easy volley mark. It's difficult, right? It's difficult. Let's talk about democracies. You referenced democracies in this entente strategy as like, hey, all the democracies get together.

We try to control the access and scaling of these systems through availability of chipsets and hardware. But then you yourself are using AI for militaristic stuff. And then it becomes this carrot stick thing that he talked about. So the stick is all of these Democratic nations. together are using it to develop the stick to wield whatever kind of militaristic advantage AI gives us. And then there's the carrot. Hey, we figured out how to how to get our arms around this technology and scale it, but now we're going to give you access to it only if you jump on board with how we do our thing. It all sounds fine and good, but like who is, who are the people

doing that? And did they need oversight? And a lot of people, especially in the States, Whenever you say oversight, people freak out. And they're like, no, free market, it's all of this stuff. But dude, some things as big as this, some things as powerful as this is more powerful, I think, than nuclear weapons were back in the 30s, 40s, 50s, when that was all coming up. And we've determined that those need global oversight and control. Let's assume for the sake of this essay that we overcome that hurdle, government, governance and peace. least AI solves that little riddle that's plagued us since we first stepped foot out of the lake and evolved into some kind of humanoid thing.

It raises a question that in this world where AI has solved all of our problems, cured all of our diseases, what the hell do we do? Yeah. So the way I thought about that is like AI is like solve. AI is helping us take the elevator up. Maslow's hierarchy of needs. So we're figuring out food, shelter, keeping us safe, healthy. When you have those basic needs figured out, then you start thinking about meaning and purpose.

But guess what? Meaning and purpose. There's no easy button to meaning and purpose, right? So that's like, that's the interesting work. That's the hard work we can do as individuals, as humans. But that would be really cool if all the other things were generally solved and we're able to point towards meaning and purpose. Yeah, the economic piece is much.

more difficult than the meaning piece. People like doing stuff. People don't care if there's people who are better than them at something. You don't stop doing something just because you're not the best in the world. Whatever your hobbies or interests are, you do them because they bring you some kind of meaning. They bring you some kind of pleasure. It would be a very strange world if there was only the best to do anything.

UBI's been floated around depending on who you read. It's a cure all or it will be a complete failure. How do you fix the economic side of? Meaning because how do I pay for it to do all my hobbies all the time? Really interesting. I read it. I read a book a long time ago. I think it was called On the Conquest of Bread.

And actually I might have people knock on my door right now just because I read that book and tell me I'm in trouble. But, you know, it's the idea of like collective farming where the efficiency of that system pulled together actually creates, if it's done the right way, actually creates time for leisure, time to invest in things that you wouldn't normally have time to do because your basic stuff is taken care of, but the way collective farming works, you still have to work. You still got to put your energy in and the farm, but then you have more time outside of that because collectively everything is pulled together.

Again, collective farming didn't work in Russia, did it? Nexus Chapter 7, check it out. Theory when applied through people, I don't know. It's funky, man. I liked his solution for the economic, or one potential solution for the economic side of this. It could be a capitalist economy of AI systems, which they're. give out resources, huge amounts of them, since the overall economic pie will be gigantic. They'll give this out to humans based on some secondary economy of what the AI systems think

makes sense to reward in humans based on some judgment ultimately derived from human values. I think you should have a question mark after that. Is this when we go into like the whiffle points or the wiffy points? Well, yeah, reputation points on an internet-based society is a load of rubbish for me. Social scoring and all that crazy stuff. Yeah, that was a book he referenced, I think, like a sci-fi book about Disneyland or something. It was interesting. But we talked to Rom about post-labor economics. That's where this is going, which would require an entire reinvention of how society is laid out. And when you think about it, like, how the hell is that

going to happen? But then, look, dude, over the years, we've gone from hunter-gatherers to farmers. We've gone from, as he lists out, farmers to like a feudalistic economy, and then from feudalism to industrialism as he outlays, you know, what's next? So we have evolved in the past. Yeah, but how many centuries did that take? Massage. How many millennia did that shift to farming take? How many centuries did it take?

And so on the one hand he's saying, yes, we can do that. But, oh, on the other hand, we're talking five to ten years. It doesn't compute. Well, he talks about scaling. Things happening 10x faster, not happening. in 100 years, but happening in 10 years. Yeah, but he's talking about the outward, not the inward. He's not talking about, like, the, like you mentioned it earlier, didn't you?

Like the societal change, the cultural change, the changes that are needed within us. And maybe this is the slack in the system, the problem with all this is that with AIs, we create this world and we're simply not ready for it. And so you have however much time it takes for us to be ready. Like, how short can we make it? 10 years, 50 years, 100 years? Can we do it in 100 years? So if what he promises takes 20 years, can we as a society prepare ourselves in 100 years?

What's the ratio here? Collateral damage. What's the collateral AI damage of all of this? Yeah, I think what I'm learning through all of this is tech's moving. The technology for this is moving way quicker than our ability to understand the effects of it and how it's going to change the world. It's going to. I want to talk to the people that are thinking about those things as in. depth as the people that are building the technology.

And if you are one of those people, we would love to talk to you, or you know one of those people that's been working on that stuff. We'd love to kind of chat with you about it. But as we quick... How long did it take us to assimilate the car? There's a technology that changed everything. How long did it take us to assimilate that? 40 years?

I don't know. That's a good question. I mean, we've assimilated the internet, I guess. So that took, what, 20, 25? Yep. So when you talk about assimilate, is more the adoption of it and the widespread use? To live with it as a part of like this new paradigm of humans plus cars, humans plus internet, humans plus the systems AI create. How long does that take?

We're about to find out, man. Hang tight. Buckle your seatbelts, friends and neighbors. Let's finish this last little bit on peace and governance. And I really think if you're interested in learning his perspective on that, I would listen to our Nexus Book Club. It's pretty much aligned with what he says in here. with repressive governments thrive on lack of information and what can AI do to counter that, but what could also AI do to help the dictators help the repressive governments stay repressive.

So one quick quote that I pulled out of this, he said, AI is the first technology to make broad, fuzzy judgments in a repeatable and mechanical way. And why I thought that was interesting is as it applies to laws and judgments upon laws, because laws were created by people, laws are interpreted by people, which has ton of subjectivity, which helps, right? Because, you know, people acting under the laws, it's not always a yes or no. Maybe there's an in-between state, but sometimes it is. And he talks about the idea of, like, AI can potentially alert to biases in decision-making, which could be interesting, how you formulate the ability to, now we're getting into, like,

freaking like minority report pre-cog. Exizing bias? That would be ironic, wouldn't it? If AI helped us excise bias. Yeah. What's meaningful, Mark? Well, horses for courses, it depends. Personally, I could spend the rest of my life quite easily in pursuit of personal and family

experiences. But we've already spoken about this. Who pays for it? It's the economics versus the meaning. How do you find meaning? How do you find meaning when your work is taken away from you? I think that's a big, that's the big question here. How do you find meaning when your work has been taken away from you?

The human science of it says that your real meaning when you're on your deathbed and you're looking back. It's your connections. It's the human contact. It's your friends. It's your family. It's how you spent your time, who you spent your time with rather than what you spent your time doing to a certain degree. You talked about meaning. You talked about work and the things beyond work that are meaningful, right?

which are your relationships, your connection, maybe a sense of accomplishment. But I think the older generation, I noticed this with my dad particularly because he worked for one company for 38 years, did a hell of a job doing that, put a lot of time and energy into that to give us what we had growing up. But you think about how much of his identity was tied to that. That when he retired, that's probably a good example of it. It's like when you retired and so much of you was identified with this work, you, where is the rest and where is the purpose and the meaning and that sort of thing? And it becomes tricky, I think, for the generation before us because there was more of that, I think, than there is now.

We can't measure happiness, but would he have been happier than a 25-year-old who has, and will never know what it's like to work for one company for all your life? Because his links were so deep, because his relationships were so deep. deep because the people he knew he'd known for 40 years because they shared moments. They shared the good times. They shared the bad times. And it doesn't be it transcends the workplace. I'm sure that when your dad looked looks back on that. It's not really the job that he'll remember fondly, is it? It's the networks. It's the relationships. It's the thing, the interactions, the things that he was able to accomplish. So it's maybe it's the same thing. But when you retire that piece, sometimes it's taken from you. We don't have to retire anymore. We don't have a, we won't

a job to retire from but if we do are fortunate enough to have a job to retire from in 40 years we won't need to retire because we'll be living to 120 like marathon runners so um yeah retirement we'll retire that word how many things do you do each day with zero economic value i've always thought about this because there's value in things that value in these interactions that aren't necessarily tied to monetary return. But they have impact. Like this show. Like this show, right? Like this show. You have, you have an impact on, you know, someone's understanding of technology. Someone's going three, four, five levels deep in meaning and discussion and application. The quantification of non-economic value is really interesting and what could that look like

in a post-powerful AI world. And what things won't be economically rewarded. What things do we do now that we get rewarded economically from that we won't be able to in the future? Work. In general. All, all work. All of it. All of it. I think that Machines of Loving Grace, as many of the conversations we have of late,

this is where the tech companies want to go on the whole. This picture that he paints with machines of loving grace is where we want to go. And if they want to go there, if they're going to build their own future and this is where they want to go and essays like this will help. it just always comes back to the human in the loop is the weakest link. And yet the human in the loop at some point has to make a decision philosophically for where this goes. And I don't know how we solve that. That is a funky cycle.

I wrote this question down like what happens when, quote, most humans can contribute meaningfully in a sufficiently advanced AI society, unquote. Then we all sail off into the future happy, content, secure, knowledge, the complete augmented human as we move up the high level of abstraction so so much for the pocket edition mark this is the giant sack of books edition but a quote to to wrap us up here in this just from a closing thought perspective as he landed the plane of the essay quote the experience of watching a long held set of ideals materialize in front of us all at once it's pretty pretty mind-blowing right there.

Like we're, we're, get the popcorn out. Like, we're, we're going to watch and see a lot of things that have been a long part of our life and world and society shift in very new ways. And I think a lot of people don't realize how big the shift is going to be, but it could be the biggest that humans have ever seen. Yeah, agreed. He starts the essay with saying that most people underestimate the potential upside of AI and the same people will probably underestimate.

the potential risk of AI, but whichever side the coin lands, you ain't seen nothing yet. And Dario Amade, I absolutely agree with you that we have to work harder, fiercely at the human side of this thing to make sure the tech side has the effects that we want it to have. Because if we don't spend time on the human side, if we don't figure out the implications of this stuff, we are going to be in a bad way. So kudos to you for putting these things out into the world, come on the show and unpack them in real time. That's all I have on this one. This has been a review pocket edition of Machines of Loving Grace by Dario Amadeh. Mark, closing thoughts on your side. I'll leave you with the verse from the original Orb watched over by Machines of Loving Grace.

I like to think in the sooner the better of a cybernetic meadow where mammals and computers live together in mutually programming harmony. Let's hope we get there. Sounds like the future that we want to build not the opposite off we go be curious stay disruptive keep thinking on paper