← Assembly Required with Stacey Abrams
Assembly Required with Stacey Abrams
How Anxious Should You Be About AI? (w/ Katie Drummond and Timnit Gebru)
01:09:21
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- [00:00]
Stacey Abrams
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- [01:27]
Crooked Media Host
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- [02:23]
Stacey Abrams
With Vrbal's last minute deals, you can save over $50 on your spring getaway. So whether it's a mountain escape with friends, a family week at the beach, or sightseeing in a new city, there's still time to get great discounts. Book your next day now. Average savings $72.00 select homes only. Welcome to Assembly Required with Stacey Abrams from Crooked Media. I'm your host Stacey Abrams. During the 2024 elections, warnings about attacks on democracy competed with worries about the economy. But now we know affordability and democracy aren't two separate conversations. More and more, they're about the same thing. The price of gas or groceries and how much decent housing or health care now cost. A smart politician can't claim to want to protect democracy without understanding how how it affects the cost of living. I personally believe that AI is another dimension that we now need to add to the discussion. In my novel Coded Justice, I explore how AI is already such a massive part of our lives and how much more it can change about how we live free lives. Coded justice uses AI's infiltration of our healthcare decisions and how much AI surveillance is already in our cars. Spoiler alert. It's more than you might imagine. But I'm not in the AI is bad camp yet. Instead, I'm in the we need to be curious and cautious camp. From AI sponsored data centers driving up utility bills, to gross invasions of privacy by AI companies, to the threat of jobs lost over ever expanding AI agents, we can't fight for a real democracy unless we understand the challenges and the potential of artificial intelligence. Right now it's generating boos at college graduations and propping up stock markets from here to South Korea. Look, AI is not going anywhere and neither are we. So let's dig into the complexities, let's make sure we understand the questions, and let's start figuring out how to how we get this right. This week, to help us in our quest to unpack AI are two fantastic guests. Katie Drummond is the Global Editorial Director at Wired, and Timnit Gabru is the founder and Executive Director at the Distributed AI Research Institute. Katie Drummond and Timnit Gabriel welcome to Assembly Required.
- [05:18]
Timnit Gebru
Thank you for having us.
- [05:19]
Katie Drummond
Happy to be here.
- [05:20]
Stacey Abrams
So the reason I wanted to do an episode about AI is that I am not just fascinated by it, but I'm really committed to unpacking how important it is. I wrote a novel a few years ago called Coded justice mainly because my niece knew more about AI than I did. And that's just an untenable situation. When a 16 year old has more knowledge, that's just bad. And so I started doing a lot of research and ended up writing a novel that really tried to grapple with how AI could be a lived experience, but also what it's capable of and what what I finished and published in 24 has now been far outstripped by the reality of things like Mythos and just the lived experience people are having. Because this technology is being developed at such a breakneck pace, we have so few rules around it, and people still don't quite get it. And so I don't want to make assumptions about our audience's familiarity. I presume they haven't read my book, although they're going to. So, Katie, I'm going to start with you and ask you to just talk about how you explain AI to the novice and why it's important for them to understand it.
- [06:36]
Katie Drummond
Oh, wow. I mean, that is a very, very big question. And I think if we are starting at the most basic and practical place and maybe a place where people will feel a little bit less intimidated by the technology, I think that the Last sort of three years have been, ever since ChatGPT was released, I think there has been a really high bar for intimidation around artificial intelligence, particularly generative artificial intelligence. And so I think one thing it can be really helpful to tell people is that artificial intelligence as a technology has been around for many, many decades. People experience AI in all sorts of facets of their lives, and they have since well before ChatGPT became the sort of widespread, widely adopted consumer application that it is today. But I think that one of the most effective ways of describing AI to the average person is just talking to them about machine learning, about the idea of automation, about the idea of a machine doing something at the behest of a human being. And I think importantly for me, when I talk about it, it's always centering automation and AI in humanity and people rather than sort of anthropomorphizing it, right? Making it feel like it is a being unto itself. It's not. This is just a piece of technology, it's a tool. And so really making it clear that this is automation technology. And it can come in myriad forms, it's a general purpose technology, it can be used in radiology as much as it can be used to transcribe your interview notes. It's very broadly applicable. But it's automation technology that can be used by people as a tool, ideally to be more efficient and more effective. Whether that is actually the case in terms of how the technology is being deployed and commercialized is a separate conversation that I'm sure we'll have in the next 45 minutes. But I think those are some of the things that I try to bring up with people. And I think most important to me is really grounding it in the fact that AI didn't just appear three years ago with ChatGPT. It has actually been around and in development in all sorts of different ways for many, many decades.
- [08:53]
Stacey Abrams
And Timnit, I would love for you to expand on what Katie just said. There are different types of AI in the novel. I talk about AI helping with healthcare, but I also talk about its intersection with dei and. And it's in your refrigerator, when you have a smart refrigerator, that's AI. Can you talk a bit more about the places where AI is showing up, where people don't even realize it, and how you contextualize AI with the work that you do?
- [09:21]
Timnit Gebru
Yeah, I completely agree with what Katie said. I would just add that AI has been many different things, so it always changes the meaning of what AI is. Right. So. So I think of it more as a marketing term, and so it encompasses a whole bunch of different techniques. Sometimes it's products, it's a bunch of mix of things. And one of those techniques kind of surprises us by having a certain kind of performance on a benchmark that we didn't think it could do. Then that gets upgraded into AI. So, for example, machine learning was not AI for a long time, and a subset of it called deep learning actually was so stigmatized, the academics, their papers were getting rejected from the AI journals, so they kind of changed their names and they did all this stuff to be accepted. So I think that's one thing to consider. It can be so many different things that it's hard to have concrete conversations when we just talk about AI, because we can. We call breast cancer screening, medical imaging AI. We also call ChatGPT AI. We call face recognition AI. When you're walking down the street on CCTV cameras that are being put for surveillance in many places that ICE is using these days, that can be called AI. There are some algorithmic price fixing that we might talk about now where people can change the different prices for many things. Even airlines have started doing this that can be called AI. So it's a mix of different things. And I try actually to avoid using the term and be more concrete as much as possible, because then we can have, I would say, more concrete conversations about the harms and the benefits. Whereas when we mix everything up into AI, it's kind of difficult because if I talk about breast cancer screening, then people think I'm talking about ChatGPT. Right. Which are very different things.
- [11:36]
Stacey Abrams
So, Tim, and I'm going to stay with you, so give us some examples of what you would call it. So we know that ChatGPT and Claude are chatbots, I guess, is one of the terms of art. Although if you use Claude for certain things, you can build agentic devices with it, so it can automate some of your work. And I think that's what Katie was getting to. If we're going to use this episode to kind of expand the lexicon, what are some of the words that you would use instead of AI to describe the functionality?
- [12:06]
Timnit Gebru
Automated facial analysis tools. The tools that are, you know, trying to infer gender or infer age by looking at a photo or video or recognize faces. Speech recognition or automatic speech transcription. Actually, just see how speech recognition sounds very different from automatic speech transcription. I think that's the anthropomorphizing. It's hard for me to say this word that Katie was mentioning.
- [12:32]
Katie Drummond
It is a very hard word.
- [12:33]
Timnit Gebru
I couldn't say Machine translation, translating from one language to another. Large language models, which underpin a lot of these chatbots that we're talking about right now, even though they don't only consist of large language models. These are some. And then those are models. But then there's techniques, which is machine learning, I don't know, linear regression. We don't have to get into these things, which are now. It's kind of like the big data era. Everything was big data, and now there's a rebranding of the big data into AI as well. These are some words I use. And then, of course, I do agree that sometimes when we say AI, we actually mean automation. So if we're talking about harms, it's also good to just talk about, okay, we're talking about automation. We're not necessarily trying to be specific about the techniques of automation. So I think it depends on what we're trying to get at.
- [13:28]
Stacey Abrams
Katie, as a journalist, I mean, part of your job is to do the sort of deep dive into specifics that Timnit is talking about, but it's also your responsibility to use common terms of art. So people have a point of entry. How do you think about and navigate that in the writing that you not only do, but oversee?
- [13:48]
Katie Drummond
I'll be very, very honest about this answer. I mean, I think that in the last couple years at Wired, it has been a challenge for us. I think that one thing we do really well and have done really well for a very long time is we are able to take highly technical topics and we are able to translate them and make them digestible and understandable for the layperson. Right. That is something that I really take seriously as a priority for us. At the same time, we don't have two or three paragraphs to spend in every story. Whenever we're talking about artificial intelligence to get into sort of it was this model or this training technique, or it comes from sort of this origin. So I think as much as possible, what we try to do is approach the coverage in a very clear eyed, consistent, thoughtful way. A way that avoids as much sort of the marketing that Timnit was referring to, sort of the marketing and the hype, because I think that is such a dangerous place to be. And we just try to be as simple and as clear with our readers as possible about the technology that we're talking about, how it works, how it's being used, and what the implications are. We are very careful never to, for example, take a technology executive working on one of these research projects or working on a given product at face value. I think that's really important when you're talking about the amount of money that is at stake in this industry right now. So we try to just be really careful and really thoughtful, and we try to be really clear. And we always try to position our reporting on AI in as human a way as possible. So bringing people into the conversation as often as we can so that we're not just spending 2,000 words talking about a given technology and how it works. We're explaining how it works, but what we're really focused on is what it means for the people on the receiving end of that technology. So that's a bit of a muddled answer, But I think that sort of simplicity and clarity in the face of so much confusion and complexity is probably the single most important thing any journalist can be doing right now. We might need to understand a lot more about it in the background. Candidly, I don't know that readers need to or even can understand sort of the 60 or 70 years of history behind a lot of this technology. I don't know that that sort of best serves them in this moment because I think there is so much hysteria and anguish and confusion and frustration already. We're really trying to cut through that as much as we can.
- [16:25]
Stacey Abrams
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- [21:07]
Katie Drummond
Oh my gosh, I mean, we're just putting the finishing touches on a big package about AI and work and sort of looking at what it means in all sorts of different contexts. The good, the bad, the uncertain. And I think what stands out to me most is the uncertainty. And we did a data analysis with this project where we looked at all of the different sort of estimates and research studies about job loss and artificial intelligence. And we have fantastic data journalists at Wired. I mean, they are the best in the business. And they came back to us and said there is not a clear picture at this moment. We don't have a crystal ball. The numbers are all over the place, the estimates are all over the place. And so it may not be particularly helpful for me to say we don't have a great clear view, but I think that if I sat here and said to you, well, Wired knows exactly what this means for jobs in the next five to 10 years, I would be lying. I don't think that anyone really truly knows. I think we're seeing sort of signals. I think, for example, the job market for entry level employees is absolutely atrocious. I think you can attribute that to a lot of different things. And I think that's a very complicated story. It's certainly not singularly an AI story. I think you can look at for Example, within specific industries. What's happening in software engineering right now? I think there's a relatively clear story about sort of AI coding, agents and tools being introduced and that changing the nature of work for some people in those professions. And I think that's pretty transformational. But I think big picture, there is a lot of uncertainty and there is a great deal of frustration. And the frustration, to me is troubling. And it's fascinating because I think so much of that sentiment, and I'm interested in what you think of this too, Timnit. It's this loss of agency. I think that's what we're hearing in our reporting over and over from people is, yes, I find the technology confusing. Yes, I'm worried about being left behind. But most of all, I just really resent feeling like this is being foisted on me and I don't really have a say in what it means for my career, what it means for my personal life, what it means for me in 10 years, what it means for my financial health, for my community, for all of these different things. And so you have that sort of uncertainty in a professional context combined with this feeling like this is just being shoved down my throat, including by the CEO of my own company. And I don't like that. And I think that combination in the workplace right now explains a lot of what we're seeing, but what we don't have an explanation for is, okay, exactly what does this look like in five years?
- [23:45]
Stacey Abrams
Well, Temnet, your organization, dare, focuses on building thoughtful, inclusive and supportive technologies that can benefit our communities.
- [23:54]
Katie Drummond
And.
- [23:54]
Stacey Abrams
And you have actually articulated a disagreement with this notion of treating AI as an inevitability. Can you respond to what Katie just raised and talk more about the work that you're doing and specific examples of how you're trying to navigate this?
- [24:09]
Timnit Gebru
So I completely resonate with what Katie's saying about loss of agency. In addition to your book, Stacey, I think your listeners should read Empire of AI by Karen Howe, that talks about the empire building project of OpenAI and similar companies. And she talks about the loss of agency that people are feeling across so many different, basically across so many different parts of the pipeline in the AI production process, whether it is exploited data workers who label the data and sift through the content that is used to train these systems, or the worker whose CEO thinks they can be replaced by AI. There's so many different aspects of this. So for us, the first thing we want to do is we want to explain to people that there is no predefined it's not like gravity that it exists and somebody's going to discover it. There was a way in which historically we got to where we are right now and if we had, had we made different choices, had we platformed different people or given money to a different set of people, we would have arrived at a different set of technology. So there is no predefined path that we have to take place. I'm actually writing a book. I just finished writing a book. I don't know how you write so many books. I have to say
- [25:37]
Katie Drummond
I'm not writing any books. So I don't know how either of you do this to be trusted.
- [25:41]
Timnit Gebru
Well, I did one and it really has wiped me out so far. But one of the examples I give is actually an example I read in Paris. Marks book called the Road to Nowhere is about self driving cars. And it was an example from a researcher at Princeton who suggested that to make it easier for cars to detect self driving cars, to detect people, that each person, each pedestrian wear some kind of sensor that would cost like $2,000. So for me I'm like, okay, we have the most famous universities in the US focused on how to make self driving cars a reality by any means necessary and how to make the lives of the self driving cars easier. It's not starting from how to make the persons, each of our lives easier. That's one thing we want to do at Deere is to make sure that people understand that this technology is not inevitable. The second question then is how do we build technologies that actually support our communities? And for me, the one thing I'm fundamentally opposed to is this one model for everything approach. It's kind of like its history is rooted in trying to build a machine God. Basically all of these companies, OpenAI, DeepMind, Anthropic, they all claim to be building AGI. And I actually wrote an op ed way back for Wired, which actually was published the same day that ChatGPT was released. I wasn't really talking about ChatGPT only, but this idea of trying to build a machine God. Now when you think about all the data that we're guzzling all of the environment that we're plundering, it totally makes sense. When you're thinking about trying to build a machine God. Well of course we have to take all the resources that we can take on Earth and then go to Mars and take those resources too. Because it's worth it to build a machine God that will solve all of our problems, whether it's climate change, I have no idea what the logic there is, how we're going to solve climate change by building all these data centers or it's like health care or anything like that. This is how they talk about their systems, every single one of them. Even when they warn about job losses or other kinds of so called also existential risks that they talk about. Well, I'm fundamentally opposed to this idea and we show in our work that for example, when you have small models with curated data that is not guzzling everything from the Internet, but intentionally thinking what do I want this model to solve? And then what kind of data do I need for this specific model? Then a your models are safer because fundamentally from an engineering point of view it's if you have an unscoped system, it's not going to be safe. So I'm just basically fundamentally against this whole one model for everything machine God idea. And I advocate for small models, community rooted curated data, task specific. First ask what problem am I trying to solve? And then build a model that works for that problem.
- [29:01]
Stacey Abrams
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- [34:23]
Timnit Gebru
I'm just going to interject really quickly because I'll let Katie answer this really difficult question first.
- [34:28]
Katie Drummond
Oh, good, good, good, good.
- [34:30]
Timnit Gebru
I'm so, I'm, I'm so nice, aren't I, that we have. I was smiling when you said Luddites because we're starting something called the Luddite Lab at DARE and we're launching it on Wednesday. So that's one thing I wanted to say. But Katie. Yeah, all of them ask the questions.
- [34:44]
Katie Drummond
Well, I cannot solve this ethical quandary for you. I think everybody needs to solve their own ethical dilemmas vis a vis AI in their own way. But what I would say and what I really believe and what Wired believes always, is technology in service of a better human experience. Technology to help us be better, to be more informed, to be more empathetic, to live better lives, to be better to each other, to build community. That is the ideal manifestation and deployment of technology. And so I think I can't absolve you of any sort of guilty 3am moments that you're having. But if there is any use for technology, period, is it not to serve communities that are currently not being served the way they ought to be? You know what I mean? I mean, I wish that we were spending more time and doing more to funnel technological progress in those directions. I think the sad reality of the fact is that by and large we're not. And by and large, the makers and commercializers of the chatgpts of the world don't seem particularly interested in those use cases for technology. They seem much more interested in scale and growth and revenue and global domination at all costs. And that doesn't sound like what you're talking about. I understand the points. I understand the consternation that you're facing. And I think anyone, any organization sort of using AI for anything right now is probably feeling that same pressure. Certainly in journalism, there's a lot of conversation about how newsrooms are and are not using some of this new technology and some of these new tools. And so it's shades of the same conversation depending on what you do and what field of work you're in. I don't think there's an easy answer, but I think that technology for good ought to be what we're all striving for.
- [36:46]
Timnit Gebru
I would ask just a couple of questions, I would ask like, why did, did you, when you were thinking of a chatbot, is it because other chatbots are on the market? Or you thought, I wonder if these other chatbots weren't around? If you would think that a chatbot is the best medium to convey this information? I would also think, you know, not all. You can have a chatbot that has, that does information retrieval in a more deterministic way, like it retrieves information based on preset questions or something like that. It doesn't have to be the same kind of chatbot built the same way that these other chatbots are built, which is why they're guzzling so much energy, which is why you might get pushback, because it's kind of like that. There was this study that showed that writing 100 word email with chatgpt or something requires one bottle of water. Just doing that kind of resource consumption. Perhaps there is a need for that chatbot type interface, but maybe there's a different way to do it in a way that consumes less resources. But I agree wholeheartedly with your tension, because the tension is maybe you're. Even if you're supporting your community, which we all want to support our communities, if the tech we're building is actually creating, building more data centers in their own neighborhoods and then giving them asthma, then we're like, okay, like what am I? You know, am I doing the right thing or am I not? And these are questions we should all be asking, but at the same time I don't. I also resent that each of us have to. I also resent that it's on us, because I feel like before anything is on the market, like from the big tech companies, because they're the ones who are doing most of the polluting. Ideally we would have had some kind of body asking this question, should these systems even be out there? Instead of each individual person having to be the one to really grapple through so many of These questions all the time.
- [39:03]
Stacey Abrams
No, I appreciate that, and I. I'm not going to dive too much into my own therapy here. I will say that one of the reasons we built the chatbot was. And to your question about deterministic answers versus something that was more responsive was that DEI covers such a wide range of topics, whether you're talking about the disabled or talking about communities of color, talking about labor. And because of the complexity of the topic, if you used existing technology, you were going to get hallucinations or just slop answers. And so the goal was to aggregate into one place something that could filter through, you know, what is basically 250 years of law and give people direction. Not legal guidance, but legal direction, which is why the technology is so fascinating to me. As someone who writes a lot and believes I should write my own words, I'm deeply privileged to also understand the importance of research and know that I am better at it than some and worse at it than others.
- [40:03]
Katie Drummond
And.
- [40:03]
Stacey Abrams
And where this technology comes in and fascinates me is its capacity to help give access to people for whom this kind of knowledge seeking has never been. And so, Katie, we lost him. It may have been a data center reaction to our conversation.
- [40:22]
Katie Drummond
She was just horrified. She had to get out of here.
- [40:24]
Stacey Abrams
Well, to put you in data center jeopardy, I would love for you to talk about what are data centers. We know that according to a new Gallup poll, 7 in 10Americans oppose the construction of these centers in their local areas. 50% are strongly opposed, and only 7% are strongly in favor. So can you explain what they are for, and why do you think this is becoming an issue that is breaking through across the political spectrum?
- [40:52]
Katie Drummond
Absolutely. I mean, I think the only thing anyone needs to know about a data center is just imagine, like, the biggest, most boring building that is just full of racks and racks and racks of servers. I mean, that is what a data center is. And we need more of them. The tech industry needs more of them, simply because we need all of that processing power to fuel the training and development of AI models. And then more than that, the actual use of artificial intelligence by anyone sort of making a query on a daily basis. I mean, there is an almost unfathomable need for that horsepower, not only in the United States, but around the world. And that is propelling big tech and propelling the US Government to funnel enormous amounts of money into building data centers, essentially, like, wherever they can, as quickly as they can. They're talking about building them in space. They're talking about building them under the ocean. I mean, there are some really, really, truly crazy proposals emerging for sort of where we're going to find enough square footage to build the data centers that the tech industry is alleging they will need to service all of this demand. So as far as individual communities are concerned, I think it comes back again to that agency question and the feeling of loss of agency. It's not only do I feel this technology encroaching on me at work, encroaching on me in my personal life, I'm worried I'm going to lose my job. And now you're telling me that they're building a data center that's how big, where, like right outside of my town, people are worried about their energy costs going up. They're worried about what it might mean for their local water supply. There are all kinds of really valid concerns. But I think you can take all of those sort of specific concerns about data centers and distill them into that bigger picture narrative, which is, I feel like this thing is happening and I can't control it, and I resent the industry that is pushing all of this onto me and onto my community.
- [42:58]
Stacey Abrams
Well, there's the reaction that we're seeing, and then there's the politics behind it. But there's also, to your point, this lack of agency that is not only coming from the individuals, we also have seen it play out in the tech side. You've got this very public break between the Trump administration and Anthropic because Anthropic wanted guarantees that their tech wouldn't be used for mass surveillance or lethal autonomous weapons. We saw today that, and we're recording this on a Monday, Humans first led by Steve Bannon, issued a letter saying to the Trump administration, their God. Maybe you need to do a little bit more to deal with what's happening with AI.
- [43:43]
Katie Drummond
I mean, it's. It's not funny. But, you know, things have really derailed when Steve Bannon is leading the charge on AI regulation. Just saying.
- [43:50]
Stacey Abrams
So, Katie, part of what I want to understand as we face this rise of authoritarianism, this backsliding of democracy, but also this weird bedfellows coming together when I am in, you know, abundant agreement with Steve Bannon about the need for regulatory changes or for some regulation. Talk a bit about why it is so important in this moment for small P politics to take a backseat to what technology, how technology should be understood and how government should be intervening.
- [44:28]
Katie Drummond
Boy, I mean, this is an issue that could not have come, I would argue, at a worse time with regards to who is actually running the United States. I wish so deeply and so often that Donald Trump was not the President of the United States. When we were having these really timely conversations about AI regulation, the ultimate reality is this is not a US Conversation exclusively. This is a global conversation. And so this is ultimately what I think it ought to be, is a moment and an opportunity where entire countries come together on an international level and agree to a set of rules and principles around how AI will be regulated. How will models be assessed for safety, what will stop or permit them from being commercialized and deployed? How are we actually going to make sure that with something like Mythos, we, which was really a shock to the system for the cybersecurity industry, how do we make sure that models like that are managed appropriately, that the appropriate safeguards are put in place? Right. That this thing is not sort of encroaching on any individual's personal privacy, on their cybersecurity, on data security, all of these big global questions that we need to be asking and answering, those are the conversations that. That I think ought to be happening. Instead, what we have is, you know, the federal government essentially, you know, batting down states across the country that are trying to implement their own AI regulations, Steve Bannon and a coalition of sort of MAGA renegades, you know, pushing the President of the United States to think a little bit more deeply about this technology. And then you have a Trump administration that is benefiting to the tune of much, much personal enrichment for many of them by effectively colluding with the leaders of the technology industry to say, hands off the steering wheel, foot on the gas, we're going full steam ahead, full speed ahead on this thing. Essentially no regulation whatsoever, which is, of course, much to the benefit of the Sam Altman's of the world, much to the benefit of the Donald Trumps of the world, and potentially much to the great dismay and the great loss of many Americans and potentially many people around the world. So to me, this is a global moment. It's a moment that demands international cooperation and collaboration. And instead, we have the President palling around with tech executives on Air Force One and Steve Bannon publishing, desperate, desperate pleas for regulation. I mean, it's unbelievable.
- [47:19]
Stacey Abrams
So one of the most important things about the work that you're doing Temnet, is helping people understand how they can navigate AI. One with language, another with understanding the technologies. But the third is that you're actually helping produce useful technologies that shape how people live. Because I want people to know that you used to work at Google. You're not opposed to. To technology. But you understand that we have to navigate what's happening. And about 10% of Americans are more excited than concerned about the large idea of AI. And the United States is ranked as one of the countries most concerned about it. But we also happen to be its foremost developer. How do you understand this catch 22? And what is your advice to people who are feeling this anxiety? How should they process it?
- [48:15]
Timnit Gebru
The first thing is, yes, I completely agree with what you said. I am a technologist and I resent every single minute that I have to read the terrible things that Sam Altman writes or Dario Amodei writes. And then I talk about it, because that's not my job. Right. But it's difficult to make space for imagination, alternative tech futures, when I don't know how you do it. I mean, I think you're amazing because you write all these fiction books and fight all these fights, but I think for a lot of us, it's not very easy to do that. So the first thing, I think we hold these kind of workshops called Alternative Possible Futures. And these are meant to encourage all of us to make space, to imagine alternative ways of making technology and building technology. So that's one of the things I encourage people to do. Secondly, I don't blame the public because I think that the people who are supposed to inform them are not doing that. Academics are supposed to be independent, but a lot of them are paid by Google and Facebook or OpenAI. So there's really no difference, for example, between Stanford and Silicon Valley. So whatever comes out of Stanford is basically whatever Silicon Valley wants you to believe as well. So there aren't independent sources of information. Hollywood is misinforming the public because their conception of AI is like the Terminator. And then you have the government, who you expect to regulate these companies, but we know that a lot of legislators are, for lack of a better word, bought by some of these people. And then sometimes what the press does is press release as a service, I call it like, you know, it sounds like news, but it really is press release. Like, I was on 60 Minutes one time, and the amount of time they gave me, basically their introduction of me, was longer than the amount of time I was able to speak. But then Microsoft CEO was there for the whole segment, talking about all the different capabilities of their systems, and. And I didn't have any space to counter what he was saying, all the things they didn't test, all the ways in which he was misinforming the public. So the American public is kind of acting based on what they're hearing. They're also hearing things I want to say, actually, just because someone says that we need to regulate AI, don't believe them. I remember I heard you say talk about Steve Bannon for a little bit. And I know there is this supposed coalition that's getting built, but it's actually being built by the same people who invested in these companies. And so when sometimes we have to ask the source of the messaging. Just because someone sounds like they're on the same side doesn't mean that we should believe them. So when a tech CEO says, I'm so worried that my models are going to be replacing all of these jobs, we should be really worried. You should think that they are doing marketing for themselves because investors want to hear that these models are going to be replacing all these jobs. That's why they want to invest in them. And right now OpenAI and Anthropic are about to they're in competition with each other and they're about, they're both about to ipo. So when I see Bernie Sanders repeating things that Dario Amodei, the CEO of Anthropic is saying, I'm very disappointed because some of our politicians who are focused on labor should know not to repeat the propaganda of CEOs. So it's very difficult to sift through what is going on because we're being misinformed and there are a lot of they have so much money that they can spend all this money on propaganda
- [52:08]
Stacey Abrams
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- [54:04]
Crooked Media Host
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- [55:02]
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- [56:02]
Stacey Abrams
so I recently had Tim Wu on the show and he talked about how we could use antitrust as a mechanism for reigning in tech companies. Katie, when you are thinking about and reading pieces, what other interesting legal or Ethical conversations have come up about how we can regulate what AI is or what AI might become.
- [56:23]
Katie Drummond
Oh, my gosh. I mean, there's so many. And I'm just sort of thinking through, in real time, the storylines that we're following. I mean, I think one of the maybe most interesting or consequential to me, that we have not reconciled and that in many ways it feels like the narrative and the conversation has moved on from is exactly what to make of all of the data and all of the copywritten work that these models were trained on. And I think we've reached a point in that conversation. And almost as these legal cases sort of wind their way through the system where we're not actually really talking about that anymore, it's sort of like everybody tacitly accepted that that had happened. There are cases winding their ways through the legal system, but we've all just moved on and we're all, like, using ChatGPT to figure out what to make for dinner tonight. And I actually think that there is still the potential for those legal cases to serve as something of a morality check, an ethics check on these companies and on big tech, and on sort of what they did in many cases, knowingly taking data that they had no right to use to train models that are now enriching their companies and their executives to the tune of many, many millions, if not billions of dollars. So I think that that remains a really interesting piece. I think the other piece I come back to, because we're spending so much time at Wired right now focused on AI and work, is how exactly to think about and how to regulate against the possibility for widespread job loss. I think we still don't know exactly what employment looks like, as I said earlier, in five years, in 10 years. But there is no question that this technology is already highly disruptive in some industries. Software engineering, again, is of the perfect and most salient example, and we have a good sense that it will be highly disruptive in others. What should lawmakers be doing and sort of how should they be insisting that these technology companies participate not only in that conversation, but in the financial reality, in the practical brass tax reality of what it means for potentially millions of people to need to make a career pivot or to find themselves out of work? How should tech companies actually be compensating the American people for that disruption? And there have been some really interesting proposals that have been raised around that. I mean, the idea of AI companies essentially paying into some sort of fund that would then allow for retraining, upskilling, employment services and all these things. I'm very interested in seeing where those conversations go because I do think we are at a fairly urgent inflection point around so many pieces of this conversation with AI. But the employment piece is one. When I think about the stories we try to tell at Wired, that is so deeply human. I mean, it affects every single person in this country one way or another, whether they are working full time or not, if they're in college, if they're retired, if they have kids, grandkids, whatever it is that affects you. And so seeing some resolution or sort of practical way forward there, I think is really, really important.
- [59:32]
Stacey Abrams
Look, as someone who had to fill out the anthropic claims form because eight of my novels or eight of my eight of my books were used to train their models, I know that they're the only ones who've admitted it. I mean, I've written several books and part of it for me is as a writer, what does it mean that there's a technology that can steal my information and feed it back to me at a cost. But I also wonder about the new versions of what's coming. The AI startups. And we hear about hyperscalers, we hear about frontier AI systems, we hear about the idea of beating China to victories so that when Deep Sea came out, the paroxysms of worry were just voluble. But what else are we not hearing about? What are the crumbs of information that we should be getting a lot more of about what's happening in AI and what's happening in tech?
- [60:28]
Katie Drummond
I mean, I think that the conversation we're still not having deeply enough. I think it's twofold. And I think that these two pieces come together. I think one is the conversation around agentic AI, which if you're already confused about AI and generative AI and ChatGPT, you're not going to be happy with me that I brought this up. But this really is sort of the next evolution of the technology in terms of personal application, which is not just sort of using ChatGPT for a query, but actually having agents do work at your behest. I mean, this is what has been so transformational in software engineering. But there are startups and plenty of companies that are now deploying agents with an eye towards your everyday tasks. What you do as sort of a regular civilian who is not a software engineer. Agents, in theory, are coming from, for all of that. And so I think that that's an interesting conversation to have, of course, around employment, of course around how individuals use them. But I think it actually ties into this conversation around Mythos, from Anthropic, around cybersecurity. Right? So the idea of autonomous agents having access to all of your data, using it, leveraging it at their will, storing it potentially in places that you may not be fully aware of, entrusting companies that you may not entirely trust with all of the information on your computer or your phone or what have you, that is a massive security risk for the everyday person that I don't think we are anywhere close to being able to grapple with. I think, again, most Americans are still just kind of trying to wrap their heads around AI, period. They're not thinking about agents and sort of what data and what information those agents may be able to access. And then we have the bigger sort of cybersecurity conversation where I'm not sure that every American totally understands. And we have a fantastic team of security reporters at Wired who looked at that initial Anthropic announcement about Mythos. They basically said, we have this model that is actually too powerful and too effective. We're not going to release it, but we are going to share it with a handful of partners to allow them to basically find bugs and flaws in their systems. And because this tech is so good that it can find stuff that's been hiding in plain sight for 20 years, that every single human being working at this company was unable to locate and rectify, I don't know that we have sort of grappled with how significant that is and with the fact that Anthropic, by and large, is a good player here. I mean, it's all relative. But Anthropic, by and large, is a good player here. They're doing the right thing in this instance. They are not China. They are not OpenAI. They are not meta. There are so many other companies and countries and geopolitical players in this conversation. And the fact that Anthropic was able to develop such a powerful model vis a vis cybersecurity stands to reason that other companies and other countries will be able to do the same thing. And so I think this conversation around data security, privacy, the sort of integrity of existing safeguards that we have in place as regular civilians, but more importantly, honestly, the government agencies, massive corporations that hold all of our data, the security mechanisms that they have in place, are all of a sudden significantly more vulnerable. And I think that's something that we will be spending a lot more time on in the coming year. I think that's going to be a really salient subject, but I think it's something worth everyone doing a little bit of digging and becoming a little bit savvier on right now, because it is genuinely disconcerting.
- [64:06]
Stacey Abrams
That was a perfect answer for my last question, and so I'm going to let you hone it a little bit. We like to give folks homework at the end of every episode of Assembly Required. And you told folks to do a little bit more digging in addition to getting their new subscription to Wired and looking for tennis book as soon as it comes out. What is a piece of homework you will give our audience? And it can be around how they can handle misinformation, disinformation. You said they should be doing more digging. What's one thing that folks can do so that when they leave this they feel a little bit more agency in the AI world?
- [64:41]
Katie Drummond
I would say we have the midterms coming up. I've been thinking a lot about it. I've been interviewing a lot of candidates in sort of key races across the country. And I think one thing that stands out where even I feel behind is this patchwork work of state efforts to regulate artificial intelligence and then how the federal government is approaching each of those. I would say my homework for everyone is whatever state you live in, go look up who's running in your midterms, go look up who's in office now, and educate yourself on what their policies and what their platforms are around AI regulation. Just have that information, understand it before you go vote in November, because again, this very likely will not and cannot be solved at a state level. But the reality of the matter is we have a federal government intent on doing basically as little as possible. And so I think as much as we can be seeking out and electing candidates who understand the technology, who have creative, enterprising ideas about how we might regulate it and how we might sort of think about it within our communities, the better. So I would say that is my homework. It's something I am actually going to do. I'm based in New York and I need to do a little bit more reading about it. So I will give myself the same
- [65:58]
Stacey Abrams
homework and TIM NIT. About 10% of Americans are more excited than concerned about the large idea of AI. And the United States is ranked as one of the countries most concerned about it. But we also happen to be its foremost developer. How do you understand this of catch 22? And what is your advice to people who are feeling this anxiety? How should they process it?
- [66:25]
Timnit Gebru
What I think people should focus on is the basics. Do we Want all of these data centers being built? Do I want to pay higher electricity costs? Do I want my water being polluted? Most Americans are saying no. Do I want my job to be replaced? I don't. The other question is, are these systems so powerful that they might render us extinct? Absolutely not. I can't even have stable Internet, so I don't understand how these robots are going to render me extinct. I can just unplug it. And we should ask, why are we getting this kind of propaganda? Well, even whether it is Utopia or dystopia, what these companies are telling us when they warn us about their powerful systems is that they have systems that can replace you. This is propaganda for the investors, right? Whether it is, they either tell us we're going to have utopia or dystopia, and both of them are two sides of the same coin. So instead of thinking about this high in the sky kind of abstract conversations, we should say, who is actually benefiting? Who's getting money to build the systems? Why are we subsidizing these data centers being built with our tax dollars? Why am I paying for a higher electricity bill for Sam Altman to get richer? Because he is. Because they're about to get to ipo. A few years ago, all of these journalists were talking about how he's the Oppenheimer of his day. He doesn't even get paid. I was driving me. I was really getting so upset hearing these things. So we should just really. It's not that complicated, right? We should just stay on Earth and say, bring it back down to Earth and say, why do I want. Why am I. Why is my private data being used to train these systems? What am I getting out of it? Why are my doctors using these scribes without asking me for consent first that can make so many mistakes, that can have the wrong prescriptions, the wrong health plan, et cetera. Who is telling them to do this? I don't want this. I want my kids to have a job. Why should I be pro technology that replaces my kids? Then what are we all supposed to do? I believe creativity is a truly human. I want artists to have money. I want artists to have a livelihood. I don't want to be consuming AI generated thing read by another AI generated thing. I honestly don't understand what the point is at some point. So I think that we should not be distracted by these kind of super abstract conversations that sound kind of magical. Like a magical. In fact, actually, Sam Altman said magic intelligence in the sky is what they're building. So we should not believe anyone speaking in these magical terms and bring the conversation down to earth.
- [69:28]
Stacey Abrams
Katie Drummond and Tim Nitt, Gabe Ruth, thank you both for joining us here today on Assembly Required.
- [69:35]
Katie Drummond
Thank you for having me.
- [69:36]
Timnit Gebru
Thank you so much for having me.
- [69:44]
Stacey Abrams
As always, at Assembly Required, we give you actionable tools to help make a difference whether AI likes it or not. So first, let's be curious. Please subscribe to Wired to gain access to their excellent reporting on technology, politics, science and culture and then let's solve some problems. Visit Timnit's organization, the DARE Institute at dair-institute.org to support their work to imagine an alternative technological future and build a better world. And always let's do some good building off of the Read Them Home DILLY Activation this coming Wednesday, May 20th, I will be joining with the other members of the National Coalition to End Family and Child Detention to host a day of action in D.C. centered around ending all family and child detention. Americans need to know that this isn't just about dilly, but all detention. We will highlight how many families and children have been detained since the start of the current administration, including kids separated from their parents. We need to highlight that everyone must be released and that zero expansion of detention systems should occur. So please visit readthemhome.org to learn more and support our activations in D.C. and around the country and and what you can do on your own social media. And thank you to those of you who shared your questions and comments about the recent Supreme Court decision on voting rights via my substack Assembly Notes, Cricket Media's discord and on other platforms. Keep the questions and comments coming, tell others about us and add us to your feed. Let me know which episodes resonate and what you'd like to learn more about. That wraps up up today's episode of Assembly Required with Stacy Abrams. Do good out there and I'll meet you here next week. Assembly required is a cricket media production. Our show is produced by l. Minkowski and farah safari with katie long and adrian hill. Our team includes matt de groat, ben hethcote, kiril palaviv, jordan cantor, charlotte landis, and jay banks. Our staff is proudly unionized with the writers guild of a. America eats.
- [72:11]
Katie Drummond
Artificial Intelligence is moving very, very fast and it's raising new questions just about every day about what it is, what it isn't. When all is said and done, what is the end game? I'm Chris Hayes and as part of my podcast why Is this Happening? I'm speaking with leading experts each week to help ground that conversation.
- [72:27]
Timnit Gebru
We're right now in a situation where it's very difficult to understand what is real and what's not real.
- [72:32]
Katie Drummond
Why is this happening? The AI Endgame, a special miniseries from Ms. Now. Start listening today wherever you get your podcasts.
- [72:42]
Crooked Media Host
Hey Crooked listeners, if you haven't become a friend of the POD yet, you are missing out on exclusive bonus content that drops every single week. If you do join, you're helping us, you know, grow Crooked Media, which is one of the few independent, proudly pro democracy media companies left in Trump's America. If you join, you also get ad free episodes of all your favorite pods. Ad free episodes of Pod Save America. Love it or leave it offline. Pod Save the World. You also get bonus content like our new extra episode of Pod Save America called Pod Save America. Only Friends Dan Pfeiffer. You also get access to all of our excellent substack newsletters like Pod Save America, Open tabs and tons more great content. So stop what you're doing right now and go ahead and subscribe@crooked.com friends. Check it out.
- [73:38]
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- [74:34]
Katie Drummond
N Developers are shipping AI apps at machine speed. Human speed. Security can't keep up. For every model you ship, there are nearly three hidden components attackers can exploit
- [74:44]
Stacey Abrams
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- [74:46]
Katie Drummond
Enter EVO by sneak, the world's first agentic security system. It maps your entire AI stack, enforces
- [74:52]
Stacey Abrams
live guardrails, and secures your agents in real time. Evo build fearlessly in the AI era,
- [74:59]
Katie Drummond
with security as agentic as your apps. Visit Snyk IO. Meetevo to learn more.