How AGI Will Impact The Economy

0:00Today on the AI Daily Brief, a discussion on AGI's likely impacts on the economy. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. To join the conversation, follow the Discord link in our show notes.

0:17Welcome back to the AI Daily Brief. As you can probably hear, my voice is absolutely destroyed. We had a good run this fall into the beginning of winter, but the flu has finally hit our house, taking me and my voice with it. Now, rather than either absolutely shred my vocal cords, extending the delays and getting back to normal, or just skipping entirely, I thought we'd do a little bit of an experiment. Towards the end of last year, we of course got a very interesting and high-powered podcast creation tool in the form of Notebook LM's audio overviews. And so of course I thought maybe a fun way to do today's show would be to turn over some topic to Notebook LM.

0:53But what to have them talk about and where to source that information. Another new tool that many of us are just starting to try is OpenAI's deep research. Deep research takes a prompt and then spends anywhere from 5 to 15 minutes looking across the web and writing up the research, complete with citations. My first thought was to look at enterprise AI agent adoption trends to try to find some case studies. Unfortunately, what I found was that the language of AI and agents gets very blurry and that all of these case studies were basically 2019-era chatbots. The second idea I had was to research the likely economic impact of AGI and superintelligence.

1:29Now, of course, this is a realm of speculation, so I wanted the research to specifically organize different theories and what people thought was likely to happen. I also asked it to get into some of the history of these definitions and how they've changed, and what follows is the results. I fed that paper, which I will include a link to the raw version of in the show notes, into Notebook LM, and this is what came out. Now, you'll notice that when it comes to a topic that's changing as fast as this one, Even deep research has some problems. Particularly note the point in the presentation where they say some people think it could happen this decade, but other people think it's decades away.

2:01I think at this point, the debate is really more in terms of months or a small handful of years. But in any case, I now turn it over to Notebook LM to talk about the economic impact of AGI and superintelligence. Hopefully, I will be back tomorrow with a normal episode. Until then, enjoy my robot substitutes. Hey, everyone, and welcome back to the Deep Dive. Today, we are going to be looking at a really fascinating topic. It's the potential impact of AGI on the economy. Big one. Yeah. So we've got excerpts from this analysis. It's an academic analysis called Economic Impact of AGI and Superintelligence.

2:37And I got to say, even just skimming through it, I was like, whoa. Yeah. It's a lot to unpack. There's a lot to unpack. It is. Yeah. And it's not just robots taking our jobs. This analysis goes way deeper. You know, we're talking like how the definitions of AGI and superintelligence have evolved and really what it means to be human in a world where machines can potentially outthink us. OK, so let's get into it. Let's do it. The analysis takes us way back to like the beginning of AI, you know, with the Turing test. Oh, yeah. Alan Turing, 1950. Classic. This idea that a machine could convince a human that it's intelligent.

3:11Right. And he predicted that machines could pass this test by the year 2000. Which is interesting because that didn't quite pan out the way he thought it would. No, it didn't. But it is really interesting how those early ideas kind of set the stage for where we are today. Totally. Yeah. And the field has come a long way since then. Just a few years later, in 1956, you have the Dartmouth Workshop. Right. Where they officially coined the term artificial intelligence. Huge moment. And there was this almost like utopian belief back then. Yeah. That, you know, machines could eventually simulate any aspect of human intelligence.

3:45Yeah, it was a very ambitious vision. It was super ambitious. Yeah. But as AI progressed, we start to see these terms AGI and superintelligence emerge. I think it's important to kind of distinguish those. For sure. From the more narrow AI that we see today. Yeah, definitely. Like my phone can beat me at chess. Right. But it can't write a screenplay yet. At least not a good one. Not a good one. Maybe not yet. Yeah. So that's kind of the distinction we're talking about, right? Exactly. Narrow AI is really good at specific tasks, but it doesn't have that like broad, adaptable intelligence that we think of when we think about human intelligence.

4:21Whereas AGI is really about replicating that general capability, the ability to learn and solve problems across a whole bunch of different domains, just like humans can. And then you've got superintelligence, which is where things get really trippy. Yeah, that's the next level. Nick Bostrom, in his book, Superintelligence, argues that the first superintelligence could be the last invention humanity ever needs. It's a pretty bold statement. It's a very bold statement, an intelligence that surpasses human capabilities in every way. Right. In every way imaginable. It's exciting and terrifying at the same time.

4:55Yeah, it's both. I mean, the implications are just massive. Yeah. So this brings us to, I think, one of the central debates in the field. For sure. How close are we really to achieving AGI? Right. Let alone superintelligence. Yeah. Some experts like Ray Kurzweil believe we're on the verge of this singularity, this point where AI surpasses human intelligence and leads to this like exponential technological advancement. He predicts it could happen as early as 2045. 2045. Wow. But then you have other experts like Melanie Mitchell. Yeah. An AI researcher who are much more skeptical. Right. And they argue that we're still nowhere near creating machines that can really outthink us.

5:35In a general sense. In a general sense. Yeah, exactly. So there's a real spectrum of opinion here. Definitely. And I think part of it is fueled by how we even define intelligence. Yeah. How do you measure that? Right. Shane Legg, who's the co-founder of DeepMind, defines intelligence as the ability to achieve goals in a wide range of environments, which implies this very general capability. Right. And DeepMind's whole mission is to create AGI using this definition. So where does this analysis land on that debate? Good question. Yeah. Are we like on the verge of this AI revolution? Aren't we there yet?

6:10Or is it still science fiction? Yeah. The analysis acknowledges that the expert consensus has kind of shifted in recent years. True AGI used to be considered this distant possibility. Yeah. But now a lot of people think it's plausible within the foreseeable future, although there's still a lot of uncertainty about the timeline. Right. Some people say it could happen within a decade or two. Yeah. Others think it's still many decades or even centuries away. And even the definition of AGI is being challenged now. Like some researchers even suggest that today's large language models, like the ones that power chatbots and content generation tools, exhibit rudimentary forms of general intelligence.

6:49Which is a pretty controversial claim. It is. But it raises even more questions about what the future holds. Yeah. But regardless of the exact timeline, one thing's for sure. What's that? AGI has the potential to be immensely disruptive. Especially when it comes to the economy. Exactly. Especially in terms of its economic impact. So let's talk about that. Let's get into it. What does the analysis say about the impact on jobs and the workforce? Okay. Well, one of the most immediate concerns, and I think we hear this a lot, is job displacement. Yeah. If AI can potentially perform any job a human can, what happens to all the workers?

7:26Where are those headlines? Robots are coming for our jobs. Exactly. And this analysis goes beyond the hype and actually dives into the numbers, which are pretty stark. One study estimated that 47 percent of U.S. occupations are at risk of automation. Wow. And Goldman Sachs predicts that 300 million jobs globally could be impacted by AI automation in the coming decades. Those are big numbers. Huge numbers. I mean, they paint a picture of really significant disruption. Right. But it's important to remember that technology has always disrupted labor markets. Like the Industrial Revolution, for example, caused huge upheaval, but ultimately led to the creation of new jobs and new industries.

8:09That's true. But what makes AGI different? Well, AGI could potentially automate not just manual labor, but also those complex cognitive tasks. Like writing, analyzing data, even making strategic decisions. decisions. Jobs that we once thought were immune to automation are now potentially on the chopping block. Yeah. And so the analysis really pushes us to think critically about this. Like, yes, yes, there will be job losses, but will there be enough new jobs created to compensate? Right. And what kind of jobs will they be? Yeah. Big questions. Big questions. Right. The World Economic Forum predicts a net gain of 12 million jobs by 2025.

8:46OK. Due to automation. But they also say that these new jobs will likely require different skills. Yeah, which means retraining and education are going to be super important. So let's kind of break this down a little bit. Okay, let's do it. One area the analysis focuses on is wages. Right. And the overall structure of employment, like imagine if AI can do everything a human can do. Yeah. But faster, better, cheaper. Right. What happens to the value of human labor then? Right. That's the million dollar question. Yeah. Some Some people say that AI will mainly augment human workers, making us more productive, leading to higher wages.

9:21But then others worry that it could lead to this devaluation of human labor, downward pressure on wages and even mass technological unemployment. Right. So it's like this push and pull between optimistic and pessimistic scenarios. Totally. On one hand, you've got this potential for increased productivity and efficiency, which could lead to economic growth. Right. But then on the other hand, you've got this risk of widespread job displacement, declining wages. Yeah. Which could exacerbate inequality and lead to social unrest. Absolutely. That tension is really at the heart of this debate. So how do we even begin to navigate all this uncertainty?

9:56That's tough. How do we prepare for a future where the very nature of work might be transformed? Those are the questions we're going to explore as we continue this deep dive. OK. We're going to be looking at potential policy solutions. the impact on wealth distribution and what this all means for economic growth and innovation. Sounds like we've got a lot more to cover. We do. All right, we're going to take a quick break and then we'll be right back to dive deeper into all of this. Sounds good. Today's episode is brought to you by Vanta. Trust isn't just earned, it's demanded. Whether you're a startup founder navigating your first audit or a seasoned security professional scaling your GRC program, proving your commitment to security has never been more critical or more complex.

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12:25Hello, AI Daily Brief listeners. Taking a quick break to share some very interesting findings from KPMG's latest AI quarterly pulse survey. Did you know that 67 % of business leaders expect AI to fundamentally transform their businesses within the next two years? And yet it's not all smooth sailing. The biggest challenges that they face include things like data quality, risk management, and employee adoption. KPMG is at the forefront of helping organizations navigate these hurdles. They're not just talking about AI, they're leading the charge with practical solutions and real world applications.

12:57For instance, over half of the organizations surveyed are exploring AI agents to handle tasks like administrative duties and call center operations. So if you're looking to stay ahead in the AI game, keep an eye on KPMG. They're not just a part of the conversation, they're helping shape it. Learn more about how KPMG is driving AI innovation at kpmg.com slash US. So, you know, we were talking about the potential impact on jobs and wages. Like a huge question mark. A huge question mark. But the analysis actually goes even deeper. It really digs into how AGI could impact wealth distribution. Oh, wow.

13:31Okay. So like, will the benefits be spread out, you know, leading to a more prosperous society for everyone? Or will it just concentrate wealth in the hands of a few and make inequality even worse? That's the big question, isn't it? Yeah. And it's something we've already seen with technology, right? You get these winner-take-all dynamics. Yeah. Where just a handful of companies end up dominating entire industries. Right, exactly. So could AGI just like supercharge that trend? It's definitely a possibility. Think about it. AGI basically becomes this form of hyper-efficient capital. And the people who own or control it, which is likely to be, you know, large tech companies or even governments, they stand to gain enormously.

14:13Yeah. But what about the rest of us? Right. The people who depend on their labor for income. Exactly like if our skills become obsolete, how do we even participate in that kind of economy? It's almost like AGI could create this whole new class divide. Could. Where you've got the AI owners on one side and then everyone else struggling to keep up on the other. Yeah, that's a pretty bleak picture. It's a very bleak picture. And the analysis doesn't shy away from those concerns. It talks about these potential winner-take-all effects. Right. Right. Where you have a few AI powered companies that just dominate everything, leaving everyone else in the dust.

14:51And how would we even prevent something like that? Well, there are a few policy options. Some of them are a little radical. Like what? Well, one idea is progressive taxation. OK. But specifically targeted at the gains from AI. So like capital gains and high incomes that are generated by AI. So taxing the winners of the AI revolution. Essentially, yes. To help the people who are left behind. Exactly. Yeah. It kind of challenges how we traditionally think about taxation, right? Yeah. It's not just about taxing income from labor anymore. It's acknowledging that AI itself could become a major source of wealth.

15:27Right. And that we might need new ways to make sure that wealth is shared more fairly. So like changing the rules of the game. Exactly. The rules of the game might need to change as AI reshapes the economy. OK. So what else besides progressive taxation? Well, another idea that's gaining some traction is a robot tax. A robot tax. Okay, I've heard of that. Yeah, it would basically require companies to pay a tax for using AI or robots that replace human workers. So if a company automates and benefits, they have to contribute to a safety net. Exactly. It's a way of acknowledging that, you know, AI can create economic value.

16:03Yeah. But it can also displace workers. Right. And that we need to find ways to soften that blow. Okay, so what would we do with the money from a robot tax? Well, it could be used to fund things like retraining programs to support those displaced workers or even to implement a universal basic income. UBI. UBI, yeah. Which is something that we're hearing more and more about. Definitely. Especially as a potential solution to mass technological unemployment. Right. Can you explain UBI a little bit more? Sure. Basically, UBI is a system where everyone receives a regular payment from the government.

16:37Oh, great. Whether they're working or not. So it's like a safety net. Yeah, exactly. It's about providing a basic level of income security for everyone. Which makes sense in a world where jobs might be harder to come by. Exactly. It could be especially crucial if automation really takes off. But wouldn't that be super expensive to implement? It would require a huge investment for sure. Yeah. But people who support UBI argue that the cost would be outweighed by the benefits. OK, like what? Well, for one, it could significantly reduce poverty. OK. It could boost the economy by putting more money in people's pockets so they can spend more.

17:13And it could even give people the freedom to pursue, you know, more creative or entrepreneurial things. That's interesting. It is a really thought-provoking idea. Yeah. Definitely seems more relevant as AI keeps developing. Yeah. But there must be some downsides too, right? Oh, of course. Critics of UBI worry that it could discourage people from working. Okay. Create dependency on the government. Yeah. And be really hard to fund sustainably. Right. Right. It's a complex issue with no easy answers, but it's a conversation we need to be having. For sure. As we think about this future of work and the potential impact of AI.

17:47OK, so beyond UBI and the robot tax, what else does the analysis suggest? Well, it also talks about the importance of democratizing AI. OK, what does that mean? Basically making sure that the benefits of AI are shared widely. Right. And not just controlled by a few powerful entities. OK, so how do we do that? Well, one way is through open source initiatives where AI research and development is freely available to everyone. So it's like making the technology more accessible. Exactly. So that everyone can benefit. Right. It helps level the playing field and prevents a scenario where you have a few companies hoarding all the AI tech.

18:25Interesting. So it's about promoting collaboration and openness instead of this cutthroat race where only a few come out on top. Right. A more cooperative approach. Exactly. And there are other models being explored, too. Like public sector involvement in AI development. Okay. Or even schemes where citizens have a stake in the profits from AI. Interesting. Similar to how some countries manage their natural resources. Wow. So it's really like rethinking the whole social contract in the age of AI. It is. If work as we know it is going to be transformed. Right. How do we make sure everyone has a chance at a good life?

19:01Yeah. How do we define purpose and value in a world where machines can potentially do everything better than us? Those are the big questions. They're huge questions. Yeah. And the analysis doesn't claim to have all the answers. Sure. But it really emphasizes the need for foresight, creativity, and a real commitment to making sure that the benefits of AI are shared equitably. Okay. So let's shift gears a little bit. Okay. The analysis also talks about AGI's impact on economic growth and innovation. Right. And it kind of paints this picture that's both exciting and unsettling. It does. Like on the one hand, the potential for AGI to unlock these unprecedented levels of economic growth is pretty amazing.

19:45It is. Like imagine an AI that can solve scientific problems. Right. Design new technologies. Yeah. Optimize production processes. At a speed we can't even fail. Right. Way faster than humans could ever do. Exactly. We're talking about potential breakthroughs in energy, medicine, materials, science. All kinds of fields. Yeah, like hitting fast forward on human progress. Totally. But the advances could be even more profound than anything we've seen before. Right. It's not just faster. It's potentially more transformative. Yeah. The analysis even suggests that AGI could bring about a new era of abundance.

20:18Yeah. Where goods and services are produced so efficiently. Right. That costs go down. Yeah. And everyone has greater access. It's a vision that's been around for a long time. Right. Like in science fiction. Exactly. But with AGI, it might actually become a reality. OK, so that's the optimistic few. Yeah. But are there any potential downsides to all this growth and change? Of course. I mean, societies might not be able to adapt to such rapid change. Right. And there's always the risk of making existing inequalities even worse. Creating a world where only a select few really benefit. Yeah. So it's not just about how fast the economy grows.

20:57Right. It's about how those gains are distributed. Exactly. And whether everyone has the chance to participate. That's the key. So it seems like we're at a really critical point. Will AGI lead to a future where everyone benefits? Yeah. Or will it just create even more inequality and division? That's the challenge. And the analysis really stresses that it's not just up to technologists and policymakers to figure this out. Right. This is a conversation that needs to involve everyone. We all need to be thinking about what kind of future we want, what values we want to prioritize, and how we can make sure that AI serves humanity.

21:30And not the other way around. Exactly. So it's not just an economic issue. No. It's much bigger than that. It's social and ethical, too. It is. We need to be thinking about the broader implications of AI for our lives, our communities, our planet. Yeah. Okay, so the analysis digs into these deeper questions. It does. About what it means to be human in an age of AI. It goes beyond just the economic stuff. Yeah, like what makes us unique? Right. What gives our lives meaning and purpose? Exactly. Those are questions that philosophers have been thinking about forever. Right. But AGI makes them even more urgent.

22:08Because it's not just theoretical. Because it's not just a thought experiment. We're actually building these things. Right. And that forces us to confront these questions head on. Okay, so how do we even begin to answer them? Well, the analysis doesn't give us all the answers. but it suggests that we need to be really proactive about shaping the values and principles that guide how we develop and use AGI. Okay. We have to ask ourselves, what kind of society do we want to live in? What kind of future do we want for ourselves and our kids? Right. It's like we need a new social contract for the age of AI.

22:42A new social contract. One that considers both the amazing potential and the potential for massive disruption. Right. And we need to make sure everyone benefits, not just a select few. That's the goal. OK, so that brings us back to policy and governance. Right. The decisions we make today will shape what happens tomorrow. Yeah. We need to be thinking about things like how to regulate AGI, how to distribute the benefits fairly. Right. And how to prevent the potential risks. And the analysis gives us a bunch of different policy options, right? It does. From investing in education and retraining to things like universal basic income.

23:18Right. It's like a toolbox for policymakers. OK. But as you said earlier, there's no one size fits all approach. There isn't. Each country has to figure out what works best for them. Right. Based on their own unique circumstances. Yeah. But the key is that we can't just sit back and watch this happen. We need to be proactive and make sure the transition is just an equitable. It's almost like we're sailing into uncharted waters. Yeah. We're going to have to adjust course along the way. Absolutely. Adapt to new information. All right. And make sure everyone is on board. It's a journey we're all on together.

23:55And that's where international cooperation becomes so important. It's essential. AGI isn't just a national issue. It's a global one. It affects all of us. Exactly. We need to be working together. Yeah. Sharing knowledge. Right. Coordinating policies. Yeah, to make sure AGI benefits everyone. Exactly. Because if one country messes up. Yeah. Or if AGI is developed in a way that only benefits a few. Right. The consequences could be really bad for all of us. Yeah, we need to be thinking globally. We do. And working together. To create a future where AGI serves the common good. Okay, so what you're saying is.