Navigating the artificial intelligence boom

So AI can help write an email, plan a trip, or even do parts of your job, but how much should we trust it? That's the big question. As Washington races to expand the technology, are safeguards keeping up with the speed that it's actually changing? The Trump administration is moving to expand AI across governments and national security while directing agencies to strengthen its security and keep humans accountable for high-stakes decisions. But concerns remain over privacy, misinformation, jobs, and the massive infrastructure needed to power it. Joining us now to talk all about it is AI Now Institute Senior Fellow Aya Ibrahim. Aya, thank you for being here this morning. Thank you so much for having me. So Trump administration is moving pretty quickly on this. What's been done so far and really what still concerns you? Well, there have been a number of announcements over the last few weeks and months, a number of importantly voluntary agreements that the administration has struck with industry. So there's been a lot of asks of industry as it relates to utility prices and what that means for people, the additional demand on our electric grid. But also questions of national security and being able to look at models before they are released out into the wild. But again, all of this is voluntary. So there has been a lot of asking of companies and not quite as much requiring them to do certain things. Demanding, yeah. So are government safeguards developing fast enough though to keep pace with the companies that are already releasing some of this stuff? Well, I think it is a little bit of chicken and egg. So the companies will argue that government fundamentally doesn't have the capacity to do so. As a former policymaker in government, I would disagree. I think that there is a lot of effort that goes towards furthering this belief that government is incapable. And so then you're constantly reacting to developments from the industry as opposed to helping shape the trajectory and the development of the technology in a way that is beneficial to all Americans and in a way that limits the potential harms. So there's been a lot of commentary from people saying AI is going to take over our jobs. This is only the beginning of it. And it's really hard to tell if that's actually the case or where that's going. A, because it's so early in all this and it's happening so rapidly. But also the Labor Department doesn't really have those kinds of facts and figures where they categorize things like that, right? Well, the Labor Department does have a very robust sort of data and analytical apparatus. So they are tracking a number of these things. But what I would say is that a lot of this is yet for us to decide. So again, the posture that we're simply waiting for the technology to develop and then we'll figure out how to deal with the effects as opposed to saying, well, how do we want this technology to show up in people's lives? What do we want it to mean for jobs? Do we want to make sure that if someone's required to use AI in their current job and it makes them more productive and they're creating more for their employer, that they're also compensated in a way that reflects that additional productivity. So all of these are choices and decisions as opposed to risks that we simply have to wait to see how they play out and then respond to accordingly. So I really just want to stress the role that workers themselves and their electives have in deciding what this means for work, what this means for labor, what this means for Americans. Yeah, like how do you use it? Because many people, you start to rely on it, you start to take it for what it is. People treat it kind of like whatever the AI answer is, it's a fact. And we've seen sometimes mistakes are made, right? So what are some big mistakes these systems can make and how do you kind of maneuver around that? Well, the mistakes can make any, or excuse me, the models, the technology can make any mistakes that the humans that design and develop them can. And so one thing is to be very clear that this technology is a tool and to be clear about both its capabilities, what it's able to do, but also what it isn't able to do. And so for folks who are experts on a particular issue, when they're interacting with technology, they're a lot more aware of the limitations. I think very clear, useful practices, I mean, always fact check. So whatever it may pop up as an answer, just do your due diligence. I think be very intentional about how you want to use it. So it's one thing to have it draft an email for you, it's another to have it write a paper. And to own your own knowledge and your own ability, this technology, these machines are not substitutes for people and what makes us uniquely human, including the knowledge that we accumulate over our lifetime. And again, do not treat it like it is infallible, fact check it as you would any other source. And be very clear about the tasks that you are leveraging this technology to accomplish. And one more thing because we're running out of time. As AI grows, there's gonna be this huge data centers that are built all around the country and nearly three and four Californians oppose an AI data center in their area. What would you say is driving that resistance? I think it's a few things. One, people obviously were in this affordability crisis, and they're very sensitive to increased costs and we see where data centers go up. There tends to be additional pressure on utilities and on electricity prices. So I think that's one of them. I think the strain on water and what that means for not just like clean water, but also clean air. There's a pollution piece to it too. But I think there's also just a fundamentally democratic question. We don't want these things in our neighborhood. And despite the fact that folks are organizing and pushing back on these data centers being located in their neighborhoods, it feels like they're being ignored. And so I think it's part of a larger sense of frustration where voters are saying, well, this is what we want things to look like, or this is what we're asking for. And it feels like neither their leaders nor leaders of this industry are listening. Ibrahim, thank you. You can learn more about her work at ainowinstitute.org. Thank you. Thank you so much.