What Artificial General Intelligence Could Mean For Our Future

What happens when AI moves beyond convincing chatbots and custom image generators to something that matches—or outperforms—humans?

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

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• 0:47Ira Flatow?

  Science Friday is supported by Mathworks, creator of MATLAB and Simulink software for technical computing and model-based design. Mathworks, accelerating the pace of discovery in engineering and science. Learn more at mathworks.com.

• 1:07Flora Lichtman?

  This is Science Friday. I'm Flora Lixman, here with Ira Flatow. Today on the podcast, are we ready for super powerful artificial general intelligence? And will we ever get there?

• 1:18Speaker 03

  How do you really test that? And how do you know when we've got there? And it's not clear at all that we'll get there on the current path.

• 1:30Ira Flatow?

  Every week, you know, it feels like there's another AI advance. Some company produces a system that will write proposals better than you can, or makes more lifelike pictures, or videos, or wrangles data in a new way. And most of these systems are still limited to a few specialized tricks in what they can do. But how close are companies to creating something that can virtually think on its own, or outperform humans on any task? What researchers are calling AGI, artificial general intelligence. And that's what we are talking about this hour. All right, let's get into this. Let me introduce.

• 2:10Ira Flatow?

  Our guests, Will Douglas Heaven is a senior editor for AI coverage at MIT Technology Review. He's based in the UK. Welcome back.

• 2:18Speaker 03

  Hi, it's good to be back.

• 2:20Ira Flatow?

  Nice to have you. And Dr. Ruman Shoudri, founder and CEO of Parity Consulting, and the Responsible AI Fellow at the Berkman Klein Center at Harvard. You know where that is, in Cambridge, Massachusetts. She's also a visiting researcher at the NYU Tandon School of Engineering, and she's with us in our New York studios. Welcome back.

• 2:40Speaker 04

  Thank you.

• 2:40Ira Flatow?

  Nice to have you. Okay, everybody's heard of AGI. Will, what do we mean when we say AGI? What does that mean? How is it defined?

• 2:51Speaker 03

  I have no idea. And that's, that's the problem.

• 2:54Ira Flatow?

  Thank you, folks.

• 2:56Speaker 04

  And we're done.

• 2:57Speaker 03

  The end. No, seriously, I think, I mean, that is a fascinating question. Like, my, my whole problem with AGI, the term, is it, it means so many different things to different people, and it's sort of, it's changed its meaning over the last few years. But, you know, for the sake of getting the conversation going, what it seems to mean to people now, you know, the companies putting out their blog posts and their manifestos about what they're building, is an AI system that can do a wide range of tasks, cognitive tasks, as well as a human can. That's about as good a definition as you're gonna find, but, I mean, my problem is that there's so many words in that themselves need defining, like,

• 3:40Speaker 03

  what is a cognitive task? What does it mean to do it as well as a human? How many cognitive tasks do we need to call an AI system an AGI? It's, yeah, we'll get on to this, I'm sure, but that's, that's sort of what we're talking about.

• 3:52Ira Flatow?

  Ruman?

• 3:53Speaker 04

  Yeah, so that's the question of the hour, the day, the year. And it's interesting, because it's on purpose, right? It's to leave the sort of vagueness where we fill in the narrative ourselves and scare ourselves. But actually, if you look at what OpenAI has defined AGI as, it's the automation of tasks of economic value. And this is what happens when corporations get to define what intelligence means. They, they pin it to things that are economically productive, and I think that's That is a very important distinction from simply saying cognitive tasks. And Will's right. Yesterday, DeepMind had a blog post where they pretty much defined it as the automation of most human cognitive tasks. And I agree with Will. Who knows what that means?

• 4:32Ira Flatow?

  Does that mean self-awareness?

• 4:34Speaker 04

  It absolutely does not mean self-awareness. Intelligence and sentience are two totally different things, completely different things.

• 4:41Speaker 03

  If I think AGI is a muddy question, then, you know, sentience, then, you know, we'll be here for ages and not get anywhere.

• 4:48Ira Flatow?

  Okay, so, so, so far I've mentioned things like chat box, things, questions that get answered, things that make images or video clips. But how do you make the leap from something that's good at doing these sorts of things, Ramon, to something that's good at doing all sorts of things?

• 5:05Speaker 04

  How do you make the technical leap?

• 5:06Ira Flatow?

  Yeah, what is, what is that leap? How is that done?

• 5:09Speaker 04

  Um.

• 5:09Ira Flatow?

  Is it, is it learning, teaching computers to do different things? Is it sucking all the energy up like we hear these computers do?

• 5:18Speaker 04

  Yeah, I mean, if we're going to pin this to defining AGI, I think the goal would be that it's able to do these tasks without us explicitly teaching the model to do so. So what's very, what's captured the imagination with generative, generative artificial intelligence is that it seems as if we're just sort of handing over a pile of random-looking information, and it's putting together patterns, these models. And that is actually an impressive feat. What it is not is, you know, alive or replacing humans, et cetera. I think like what these things are in the real world is very, very different from just capability performance. So one of the interesting things to think about is when these new models come out, and like you said, they seem to come out like three a week, and they say it's performing better than X, Y, and Z.

• 6:02Speaker 04

  The important thing to ask is, what is the measurement by which we're saying it's so impressive?

• 6:08Ira Flatow?

  Right.

• 6:08Speaker 04

  And that's publicly out there.

• 6:10Ira Flatow?

  Right.

• 6:10Flora Lichtman?

  I want to bring AI into this conversation.

• 6:14Speaker 04

  Literally an AI?

• 6:14Flora Lichtman?

  Yeah, literally, literally an AI. I asked Google's AI assistant Gemini what we should ask you to. And we workshopped it a few times. But here's, here's where we got, and let's see what you guys have to say about this.

• 6:27Speaker 05

  If I could only ask one question to AI experts about AGI and humanities preparation, it would be, considering the inherent uncertainties surrounding the development and capabilities of AGI, what is the single most proactive and universally beneficial step humanity should take now to prepare for its potential arrival, regardless of the specific form AGI might take? This question aims to-

• 6:50Flora Lichtman?

  It goes on and on and on. But, okay, what do you think?

• 6:53Speaker 04

  I'm gonna punt that one to Will.

• 6:55Ira Flatow?

  Will?

• 6:56Flora Lichtman?

  What is the most proactive and universally beneficial step humanity should take to prepare for AGI's arrival?

• 7:09Speaker 03

  I mean, this is, I don't think AGI is coming anytime soon. And like, I'm not really sure what, you know, what that would be when it came. So just like, a little side note there, I think at some point, probably soon, because so many companies have said they're building it and it is around the corner, probably someone will just make a, you know, a definition and say, we're calling this thing we've just made AGI. So, you know, if the question that Gemini is asking is what do we need to do to prepare for that, then it kind of depends what that is. But, like, more constructively, I would like us to get off this obsession with AGI and sort of, you know, focus on the specific, you know, technical advances that we are seeing

• 7:54Speaker 03

  that are coming along really fast. And it's, it's so easy to sort of, you know, dismissing AGI, the idea that AGI is around the corner, is not to dismiss like how amazing the advances have been in, in video generation and in chatbots over the last few years. I'm, I'm constantly wowed. I mean, and it's, it's wonderful doing my job, like seeing the latest thing, the latest thing that's come out and you're talking to the people that are making it. I'm constantly awed by, you know, how good this tech has got. And I'd like to just sit with the capabilities that we have and think about what impacts those are gonna have on the world.

• 8:34Speaker 03

  And there's enough to deal with just with the AI we have today without, without sort of spending so many hours and words about, you know, preparing for AGI.

• 8:45Ira Flatow?

  Let me go to Samuel in Rochester, New York, who may have some words like that. Samuel, welcome to Science Friday.

• 8:53Speaker 06

  Hi, can you hear me okay?

• 8:54Ira Flatow?

  Yes, go right ahead.

• 8:56Speaker 06

  Hi, um, I wanted to just say that I, I agree with what's been said where, you know, we, we have a lot of very good image generators and chatbots, but those are pretty far away from something that can cognit-, you know, can reason cognitively and generate new ideas, right? It's always kind of a, we're, we're making amalgamations of things that are already on the internet and the jump from that to, you know, or kind of summarizing to generating something new, right? Something that hasn't been done or said before. Um, that's a leap that, you know, I, I think hasn't been made yet. And the trend I see is that there, you know,

• 9:38Speaker 06

  tech companies can slap AI powered on anything now and it makes investors happy. But the results, the profitability of it, the advancements, it's hard to know what the scale actually will be of that, the impact of that.

• 9:51Ira Flatow?

  Good, good point, Rumman.

• 9:52Speaker 04

  Yeah, there was a report last year, I believe, or two years ago, that pretty much dug into all the companies claiming that their products were AI powered. It was in the UK and I found about 60% of them had no AI under the hood. There is no, you know, first of all, we have a very slippery slope definition of AI itself. And then now it's translated into, into AGI. Um, and again, to Will's point, the analogy I give is how we have gone down the same slippery slope of self-driving cars. Remember the earliest self-driving cars? And what we imagined is like, we'd get into this pod and like, take a nap and it whisked us off to where we're going.

• 10:25Ira Flatow?

  Jetsons.

• 10:26Speaker 04

  Right, but now we have, according to Elon Musk, we have self-driving cars, which we still have to sit there in traffic with our hands on 10 and 2 and our foot on the brake. And this car is quote unquote, "driving," but if it got into an accident, we are liable. So you're still effectively absorbing all the stress of driving with none of the self-driving.

• 10:44Ira Flatow?

  Well, but let's also go right to the, the main point that I see is that the reason that all AI exists and AGI is being developed, it's about the money, isn't it?

• 10:53Speaker 04

  A hundred percent, it is. Well, and actually, um, OpenAI and Microsoft have defined what AGI is with a monetary value. They have said it is when they have earned $200 billion of revenue. Then they will slap on a sticker and say, "We have AGI."

• 11:07Ira Flatow?

  So, uh, do, do you, do you agree, Will? It's about the money here?

• 11:11Speaker 03

  Yeah, I do. And I, yeah, it was like, I, I'm happy that that we were reminded of that definition. I think that's probably the best definition of AGI we have. At least it's, it's precise and clear. But yeah, absolutely. It's, it's so hard to talk about your AI advances and really get into the details of, you know, what these systems can and can't do because the, the, the tech is being developed by, by companies and it's, you know, they're doing it for, for, for profit. And it's, it's, you know, obviously they're going to make as big a claim for their new tech as, as they can. Again, genuinely, when you get a lot of these demos in your hands, they are truly impressive, but, you

• 11:56Speaker 03

  know, they're never going to be as impressive as the, the companies selling them want them to be.

• 12:00Speaker 04

  Well, and the story within the story is that for many years, companies have poached the brightest scientists and minds from academic institutions. In fact, they poached them straight out of their PhD programs. If you go visit the University of Cambridge, Oxford, MIT, Stanford, there is a very close tie to every single major model developer. And that's on purpose. So there is something also to be said here about the lack of independent researchers who are able to do this work without getting funding or just explicitly being hired by these companies.

• 12:36Flora Lichtman?

  After the break, your hopes and fears for AI.

• 12:39Speaker 03

  We don't have to make it so that it has any power over us at all.

• 12:44Flora Lichtman?

  Stay with us.

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• 14:50Ira Flatow?

  And let's go to the phones to Chris in Scottsdale, Arizona. Hi, Chris.

• 14:55Speaker 06

  Hey, Ira, can you hear me?

• 14:57Ira Flatow?

  I sure can. Go ahead.

• 14:59Speaker 06

  Excellent. Well, I was just gonna mention that I use AI quite a bit for nutrition analysis, so it helps me come up with plans of what I'm gonna eat during the day, and I love it. One question about that that I would have, and it helps me with recipes too, but is, do they think the memory on these things is gonna get better, or will have personalized AI that can, you know, remember like what we ate a month ago? Because what I find is I have ChatGPT and I've tried Grok, and both of

• 15:31Speaker 03

  Um, sort of forget, you know, if you go back to it after a week, now you're having a brand new conversation. So one thing would be about the memory. And I had a just second question about uh what will happen with AI. Do you think it's or do your experts think it's more likely that we'll have a situation where that will place the jobs lost from AI with universal basic income, something like that? Or do you think it would be something like uh an assisted situation where all of our jobs are assisted? You know, we tell AI what to do and it does the job for us.

• 16:02Ira Flatow?

  Okay, two, two.

• 16:03Speaker 03

  That's my two questions.

• 16:04Ira Flatow?

  Two meaty questions, Chris. Thanks for calling. Uh, I'm gonna divide it up. Will, you wanna take the first half of that?

• 16:11Speaker 03

  Sure, yeah, the memory is a feature that um, you know, a bunch of these companies making these chatbots have either already added or talking about adding to the chatbot. I think it's something, an option that you can turn off or on in in Chat GPT and and probably in in the others like like Gemini and and Grox. I don't know if the Chris, wasn't it, the the caller has has is using that feature. I mean, it's possibly, I'm I'm not an expert on the actual different tiers. Like there are different paid tiers and free, free uh versions of these chatbots. But it's certainly something which exists in some of them. And if it doesn't already, then I know that's what people are aiming to improve.

• 16:52Speaker 03

  But this idea that, yeah, this this this will be like your your personal little buddy that knows more about you than than anyone else and can can recommend stuff is is a vision.

• 17:02Ira Flatow?

  And Ramon, what about jobs? Is it taking our jobs?

• 17:05Speaker 04

  Yeah, I also can chime in on the first one. Um, I use perplexity to help me do research. They actually have something called threads, and then a thread can be a particular topic and you can kind of go back to that. So um, not to like promote any particular AI, it just happens to be the one that I use for that reason. Um, future of work, I have many thoughts on future of work. Well, first of all, I wanna start by saying there is no finite amount of work we do as humans. I think one of the fallacies of this, like, there will be no jobs conversation is it, there's a core assumption that is wrong, that there is a finite amount of work that we do. Any sort of technological advancement has actually not given us less work, but more work, right? How much more available are we now that we can be found on these little devices, our phones, 24/7? We used to like leave work at 5:00.

• 17:48Speaker 04

  Very few of us remember that time anymore. So, you know, email, internet did not give us less work, it actually gave us more things to do. And there's some empirical evidence to kind of back this. So there's three studies I like to talk about. The very first one came out last year, it's by this labor economist, Dr. Darren Essamoglu, out of MIT, like brilliant labor economist. And he did a macroeconomic measure of the impact of AI over the next 10 years and found that total factor productivity, so like all of the stuff we produce in the world, sub 1% will be automated by AI. But that's not nothing. I mean, sub 1% of what the entire world produces is still something. And what he talks about that's kind of interesting, I think this is what captures the imagination. Most automation tends to get rid of like blue collar jobs or rote tasks.

• 18:31Speaker 04

  So email, automated sending mail, right? But what is interesting in capturing our minds about AI is that it automates knowledge tasks, which we've never had before. So he talks about how the distribution between blue and white collar jobs is actually fairly even slash maybe even leaning a bit more towards lower tier knowledge jobs. The second paper I like to talk to is called, talk about is called GPTs or GPTs. It came out in 2023. It was actually by some researchers at OpenAI, as well as some economists, talking about how like different sectors, what may be automated, what threat is faced by different sectors. So it's, you know, going from like big picture to like industry level. And like the rough takeaway would be about, would be roughly that 80% of jobs, we'll

• 19:13Speaker 04

  see about 20% of automated away, 20% of jobs, we'll see about 80% automated away. And they were talking about jobs like paralegal, et cetera. So, you know, research type jobs, so knowledge jobs, it's interesting. The third one just came out last week, really interesting, and this is getting super nitty gritty about future of work. Harvard Business School, some other folks worked with Procter and Gamble, and they did this study across over 900 employees. They did a kind of like a competition where it was humans, it was individual humans, individual humans plus AI, individual, like teams, teams plus AI. And they looked at things like quality of work, time to completion. How well it augmented people already with a skill set? And how well it augmented people without a skill set in a particular topic?

• 19:57Speaker 04

  You know, it's lots of details, but pretty much the takeaway is that human plus AI is better than human alone is better than AI alone. So it's one of those things where it is a productivity booster. And what that means is probably what it has always meant for us when we've gotten new productivity technology, which is that we will just kind of have more stuff to do.

• 20:17Ira Flatow?

  Right.

• 20:18Flora Lichtman?

  You know, when we think about AI, we talk about it as a reflection of us, right? That it learns from us, it learns from our data. Can we teach AI to be better than us?

• 20:29Speaker 04

  Oh, it's a good question.

• 20:32Speaker 04

  I think AI is capable of evaluating data at a scale that is hard for humans to do. That's why the output of these models can be so impressive. So the short answer is yes. The longer, more complicated answer is what do you mean by better?

• 20:46Flora Lichtman?

  I mean, and I mean it specifically like doesn't cheat, is more ethical. You know, when we, when people think about these sort of doomsday scenarios with AI, they're like, oh, they're gonna, AI is gonna scheme and take down humanity. Can you teach AI ethics?

• 21:03Speaker 04

  The short answer is yes. And actually, a lot of these scenarios where AI quote unquote cheats, it has no normative judgment, doesn't understand good and bad. So, you know, even predating Gen AI, I remember some of the earliest models coming out of DeepMind and something, you know, some of the research bodies, they would have like play video games and it would do things like race a car backwards or it would shoot everybody else in the game and then pick up all the goodies. But that is not the AI beating, being evil. We have decided that is evil because we made rules. And we implicitly know if I'm playing a game with other people, what I should not do is like get rid of everybody else so I can slowly pick up all the goodies. The AI is simply optimizing for what you have told it to do.

• 21:44Speaker 04

  Like in this very blunt way, like if you are of a particular age and I'm of a particular age and you read like Amelia Bedelia as a kid, like think of it as Amelia Bedelia, like you literally are like, you know, I don't know. Make me a cake and it will just quite

• 21:59Flora Lichtman?

  Very literal, yeah.

• 22:00Speaker 04

  Yes, and a lot of these issues of AI gone awry is actually can be boiled down to a misspecified objective function. You are telling it to do something. You actually have to think through all the ways in which you are making assumptions because you have been socialized to do things a certain way. And like, how would Amelia Bedelia understand this?

• 22:22Flora Lichtman?

  That's the new way that I interact with GPT.

• 22:25Ira Flatow?

  All right, let's go to the phones to Anton in Phoenix. Hi Anton, welcome to Science Friday.

• 22:31Speaker 06

  Hey there, thank you. Can you hear me okay?

• 22:32Ira Flatow?

  Sure.

• 22:34Speaker 06

  Okay, yeah, so I just wanted to address the earlier question that you guys asked Gemini, which is like, if there's one thing that you would, you know, want to focus on, focus humanity on, what would it be? And I'm kind of thinking about like, somebody said doomsday scenario, right? And oftentimes when we talk about doomsday scenarios, we're thinking about the technology getting smarter than us and then deciding that we're expendable and all that. But I think that's kind of misguided. It makes for a good science fiction novel, but I think the problem, if that was the problem, then it would be a technology problem. That would be easy. The problem I see is a people problem, you know, like, so the NRA says, you know, guns don't kill people, people kill people. And I think, you know, we really need to

• 23:19Speaker 06

  focus on maybe two things. One is, who's controlling the AI? Both in terms of training it, as well as using it to inference, to actually do things. And then, but I think the bigger thing is really, if you think about artificial general intelligence, or artificial superintelligence, where it has like, whatever godlike intelligence, and AI is not going to necessarily see humans as a threat unless humans are competing for the same resources with the AI, right? So that could be jobs, it could be electricity, it could be any number of things. And I think it's, the question that I think about is, how do we?

• 24:03Speaker 06

  How do we arrive at a place where AI isn't being manipulated by humans for human ends, right?

• 24:12Ira Flatow?

  Yeah.

• 24:13Speaker 06

  And this one example, okay, good.

• 24:16Ira Flatow?

  All right. Yeah, that's a good question. Let me get an answer to it because I mean, if the point of AI is to make money, I mean, it's going to be manipulated to make money, right?

• 24:25Speaker 04

  I mean, it already is, right? If we think about where money is being spent to build AI capabilities, companies have conveniently found the alignment of things people are willing to spend money on cross things that are also important to us. Like, it's not surprising that healthcare has been one of the primary applications. There's so much money being made in healthcare, but also we want to lead better lives. The other one people talk about quite a bit is education, right? So like, but no one, no one is talking about things that are maybe less profitable, but also good for humanity. And I appreciate the statement about like, let's think about the access or the people behind the wheel. A lot of these doomsday scenarios are very fantastical. You know, what if AI sets off nuclear weapons?

• 25:10Speaker 04

  Why the hell did you give AI access to be able to set off? You just can just not do that, you know?

• 25:17Ira Flatow?

  But those are people who worry about the singularity, right? I mean, when AI, when AI is smarter than us and takes, we become the AI, we become subservient.

• 25:28Speaker 04

  I mean, I, I think most AI is smarter than me from like a ability to answer jeopardy questions perspective, right? Like, I probably couldn't beat the average AI system.

• 25:37Speaker 03

  Well, can I jump in on that?

• 25:39Speaker 04

  Yes, please.

• 25:40Speaker 03

  This, this, what gets me about all these doomsday scenarios is this weird sense of inevitability that this technology is just going to appear and, you know, and squash us, you know, humans. Like, let's, we don't have to make this. We don't have to make it, have the nuclear codes, as you said, we don't have to make it so that it has any power over us at all.

• 26:02Ira Flatow?

  But we also, but you already have some advances in medicine and, you know, where doctors doing things doctors couldn't do. Aren't there already positive results, Will, of using AI?

• 26:12Speaker 03

  Oh, yeah, many, many. And, yeah, medicine is a, is a, you know, a great example. I mean, just the everyday conveniences that we're already seeing from, from chatbots, I, I think are great.

• 26:27Speaker 03

  Yeah, so I tend, in these conversations, could we go straight to AGI? I come across as a, you know, a sort of a naysaying crank, which is, you know, not, not a good professional look for someone who is very much, and has been for, you know, more than a decade, a champion of this technology, which I think is amazing. It's just, it gets derailed, I think. A lot of the interesting, brilliant things that we could talk about get derailed when we talk about, you know, doom, doom, doom.

• 26:53Flora Lichtman?

  Well, what are they? What are the interesting things that we should be talking about?

• 26:57Speaker 04

  I can chime in on some of that. I mean, the, we are likely to cure many cancers in our lifetime because of the advanced protein folding, AI-driven technologies that have been created. Like, this is like a fact. You know, we have advances in genomics and medicine because of the models that have been made. There are, we have better weather prediction models, and, you know, I live part-time in Texas, and hurricanes are a very big deal. We have better weather prediction models that can tell us weeks in advance that a hurricane may be coming because of AI. So, and the thing is, this just won't capture the imagination the way a quote-unquote "talking humanoid" bot idea will. But all of that is AI.

• 27:38Speaker 04

  And, and, and, you know, it, it does, as Will is saying, it's a disservice to have such a focus driven by, you know, multiple narratives, companies included, to push us to look at AGI when we actually can celebrate a lot of the great stuff that AI is being used for today.

• 27:56Ira Flatow?

  Let's go to the phones tomorrow. Elena in Washington State. Hi there, welcome to Science Friday.

• 28:00Speaker 06

  Hi, can you hear me?

• 28:02Ira Flatow?

  Yes, I can.

• 28:03Speaker 06

  Okay, my question is, what is AI going to do to stop sucking up all the electricity in our environment? I live in a small rural town, and a small rural town really close to ours has made a deal, and they've built a big data center, and we all know this is how AI generates all its juice, and it made a deal with this town way

• 28:33Speaker 05

  Giving the employment flag. And now, uh, these residents in this small town are experiencing rolling blackouts. I call this predatory behavior. And I would like to know what AI, what these billionaire owners of AI are going to do to be protective of people and save more of the energy in our environment. I mean, come on, this is global warming.

• 29:04Ira Flatow?

  Yeah. Sounds like Marlene is mad as hell. I'm not gonna take it anymore, Will. What, what do you say to that? Good point?

• 29:13Speaker 03

  Yeah, I, I think, yeah, I think that's a really good point, uh, especially, you know, if you have this uh, affecting your, your neighborhood, I think we are gonna see that, you know, these massive data centers get set up and they suck the power out of the local grid. So there's lots of things that could be done. Um, and let's like, let that could hang in the air a minute. Like, there's a lot of, you know, work being done to reduce the size of, um, models. Uh, and, you know, a smaller model can do many of the things that a larger model can do, uh, for, you know, for less power.

• 29:45Speaker 03

  There are things that could be done around the way that these models are trained, train them more efficiently, rather than just throw every single bit of data you can scrape up at them, maybe curate that data and show them sort of, uh, data that's actually gonna be more useful. So the training, the training steps could be fewer, again, using a less electricity. That's all on the side of actually building the models. Uh, the data centers, of course, are used then to run the models, you know. We're all, we're all invoking ChatGPT for our recipes and, and everything else. And every time we do that, it's, it's sucking up a lot of, a lot of power. So, I mean, there are, we could be making more efficient chips, uh, we could be, uh,

• 30:30Speaker 03

  you know, running on renewable sources of energy and finding ways to store that energy in the data centers with, with batteries, et cetera. So all of which is just to say there are solutions available.

• 30:40Ira Flatow?

  Yeah.

• 30:41Speaker 03

  Will they happen is a completely different question, because right now, this is a race to. The bottom, you know, all these companies really, really having invested everything they have into this race, need to come out on top, you know, with the punchiest, most powerful AI model.

• 31:00Ira Flatow?

  All right.

• 31:00Speaker 03

  And I think the, the, the sort of sustainability needs are they going to be an afterthought.

• 31:04Ira Flatow?

  Thirty seconds to go, Ruman.

• 31:06Speaker 04

  Um, well, Microsoft is rebooting Three Mile Island for those who are local, who know what that is.

• 31:13Ira Flatow?

  I remember it well.

• 31:14Speaker 04

  Yes. Um, and, you know, when pressed on this, Sam Altman was sort of hand waving over, we should have a fission technology in our lifetimes and everything will be fine. Um, so it seems like they too are kind of banking on scientific advancements to do the work for them.

• 31:30Ira Flatow?

  All right, we've run out of time. I'd like to thank my guests, Will Douglas Heaven, Senior Editor for AI Coverage at MIT Technology Review, and Dr. Ruman Choudhury, Founder and CEO of Parity Consulting, and the Responsible AI Fellow at the Berkman Klein Center at Harvard. Thank you both for taking time to be with us today.

• 31:52Flora Lichtman?

  And that is about all we have time for. Lots of folks helped make the show happen, including Shoshana Buxbaum. Kathleen Davis. Diana Plasker. Beth Ramey. I'm Flora Lichtman. Thanks for listening.