Lately, AI data centers are public enemy No. 1. The concerns are legion: how much water and electricity they consume, the noise they generate, the sprawling buildings they bring to communities, and the technology they’re powering that may or may not take all of our jobs and usher in the robot apocalypse.

Earlier this year, Gallup found that 71 percent of Americans oppose building data centers that support AI in their communities. And the backlash is bipartisan: Majorities of Democrats, Republicans, and independents opposed local construction.

Even in Texas, where data center development has been booming, Republican Gov. Greg Abbott has hit the brakes. In September, he directed state regulators to halt permits for data centers pending audits examining their effects on the power grid and water resources.

But while many data center projects have run aground, others are still getting built — and the companies behind them are employing experts like Nicole Thomas to smooth the way.

Thomas is the senior vice president of media and community engagement at JSA, a marketing and public relations firm that represents data center companies. She spoke with Today, Explained co-host Sean Rameswaram about how the industry is responding to public opposition — and why she argues that these facilities can still be good neighbors.

Below is an excerpt of their conversation, edited for length and clarity. There’s much more in the full podcast, so listen to Today, Explained wherever you get podcasts, including Apple Podcasts, Pandora, and Spotify.

You’ve been at this for 21 years. Obviously, 21 years ago, data centers were not the hot-button issue they are today. When did you notice the shift?

I’d say about two years ago. I came into this industry myself about four and a half years ago. I come from a state transportation background where community engagement is just paramount. When you’re putting a new traffic intersection up, they expect you to interact with the public.

When I got to this industry, I said, “Oh, what’s your community engagement like?” And they said, “We don’t even have any community engagements in this industry.” And they weren’t wrong. Because 21 years ago, [data centers] were just like infrastructure. It was like building a warehouse for your computers. And so it was very similar to the way that you would build a Costco.

You would just go in, request a zoning permit, the zoning board would say, “Yeah, that works. Stamp, boom.” And you build your data center. And as a matter of fact, it was very secretive before, because data, and having that data in the wrong hands, has a lot of [cybersecurity] implications. About two years ago is when we started noticing the mainstream journalists coming around asking questions about data centers. And that’s, to me, when it started.

It still feels secretive, I think, to a lot of people, and that’s why people are mad. If you read about this data center that was proposed in Utah by Mr. Wonderful, Kevin O’Leary, it caught a lot of people off guard. Seventy percent of Americans, at the moment, do not want them in their backyards. How do you go about trying to change that 70 percent’s minds?

First and foremost, I think education is really important. And so one of the things that we did notice very early on because of the previously secretive nature of data centers, there wasn’t a lot of education out there about what they even are. And so that’s something we need to change. We need to make the connection between [phones] and data centers so that people understand what a data center means to their life on a daily basis.

Every app on your cellphone requires a data center to save your information in there. When you put your password into anything, you are interacting with a data center, which will verify your password and then let you into that app. Not to mention all of the information about you that you store in that app is then stored in a data center so that it can be recalled at any time.

We could not be having this call without digital infrastructure. It doesn’t work that way. We can’t have email without digital infrastructure. And that stat about 70 percent of people not wanting the data center in their backyard — I’d be interested in seeing the stat of how many people actually live near a data center and don’t realize it.

Because there are nondescript data centers doing work quietly in your neighborhood that have been there for decades and you don’t even know it. And so in some ways I feel, and I think the industry does as a whole, but I won’t speak for them, that the pushback on data centers is somewhat related to the pushback on AI, because people can’t control AI.

You even have Sam Altman telling us that AI will destroy society. So you have this concern about AI and you don’t know how to control it, but you can push back on data centers. And so it becomes the physical manifestation of AI are these data centers that people are trying to get overturned or get to not be in their neighborhoods.

It’s understandable. I’m a citizen too. You’re a citizen, and if things come into my neighborhood, I want to know about them. I have questions. There’s a big data center that just came to my community not long ago and their community engagement was horrible, absolutely horrible.

I’m in Indiana and I won’t say which hyperscaler it is, but a hyperscaler came into — I would say, not my neighborhood, into my city. They’re definitely not in my backyard, but they’re in my city. And so we took them to task because their community engagement was basically non-existent.

Wait, you work in data center PR, but you took a data center in your community to task for not being transparent enough?

I’m on the side of responsible development.

We’ve all kind of accepted that we need a cloud for X, Y, and Z. And that it’s worth it so I can take lots of photos. I think everyone’s cool with that.

But the issue here is that people aren’t necessarily cool with AI, but we’re barreling forward anyway. How do you separate this essential need we have from AI, which people don’t necessarily feel is essential to their lives?

I think it goes back to education. Educating consumers on the difference between data centers: a small data center, a medium data center, a large data center. Educating them on why data centers exist and how they interact with data centers on a daily basis multiple times.

I hear you. But again, I feel like the issue here is not the data centers my cellphone needs, but instead is the data centers these AI companies need and these AI companies who the public doesn’t necessarily trust because they keep telling us that they’re going to kill us, and who the public is wary of because they don’t want their jobs being replaced by AI.

There’s all sorts of reasons that people are skeptical of new technology. So how do you specifically respond to that fear and to those people?

I think it’s, again, understanding the actual data center that’s being built in your community. Is it a 5-megawatt data center? That’s never going to house AI. That’s not enough power to house AI. Is it a one-gigawatt data center like Mr. Wonderful in Utah? That’s different.

But I think that AI is probably going to be something that is a lightning rod in the American public for a very long time. There are going to be people who are going to be anti-AI and pro-AI, and there’s going to be some people in the middle. I think it’s just, again, for us, it’s education, educating the community.

Have you ever been part of a project that a community rejected and you guys just packed up and said, “Okay, we’ll go find another community?”

Yeah. We have some clients who have had pushback from residents and they have said, “Let’s do a one-on-one community meeting where people can come in and ask us questions.”

And after the questions were answered, the community leaves and says, “Okay, this isn’t as bad as I thought it was.” Or we have a community that says, “No, we now have a moratorium and we’re pushing all data centers away.“

Sometimes they’ll wait for their client — my client is a developer and they’ve got clients that they’re developing for. If that client will wait, then maybe it is something that we’ll try to work out with the community. But oftentimes, they’ll just say, there’s communities who are literally raising their hand saying, “We’ll take a data center. We’ll take one. We’ll take two. Bring it here.”

So there are communities who recognize the benefits of data centers. And there are going to be other communities who say, “No, we don’t want this.” And then in five, six, eight years, they’re going to be like, “Wow, that county has a lot of tax dollars. They have a lot of really cool stuff. Why don’t we have that?” And the answer will be data centers.

I don’t think this ends anytime soon though, right? I counsel my clients that we could still be here in three to five years, really trying to help the American public understand the benefit of data centers. But it’s going to take a lot of education across the industry, and once we get those seeds planted, I’m a firm believer that they grow into educated community members who make educated decisions to bring community-minded data centers to their community.

If there’s one thing a busy person doesn’t need, it’s more information. More emails, more notifications, more infinite feeds — the steady drip of data spells doom for the overstimulated American. And if you’re a busy parent, like me, sometimes it feels like a flood: school emails, doctor’s appointments, so many little things to buy.

Even things that used to be simple are harder. I recently listed an item on Facebook Marketplace, which quickly meant I was replying to offers and getting ghosted for the better part of a weekend before finding someone who, after a detailed back-and-forth about the most likely place to find a parking spot in my neighborhood, finally took my old baby swing away.

If only I’d had Muse. You’ve probably seen the ads on Instagram promising “AI that gets it done for you.” The new personal AI agent app from Meta can not only automate your Facebook Marketplace tasks, but also sort your emails, manage your calendar, and buy your groceries. And it’s free — unless you’re using it most of the day or you want access to Meta’s most powerful models, at which point it costs $20 or $100 a month. It all sounds, in a word, magical.

Muse is probably the personal AI agent you’ve heard of — and it’s currently the market leader with more than 8 million downloads in its first month, according to one estimate — but there’s now a small army of these bots: OpenAI recently announced Dots, X has Grok Bot, and there’s Instinct, which is currently invite-only and operates entirely in iMessage or WhatsApp. They all offer the same promise: to remove friction from your busy life.

For the last two weeks, I’ve been handing over more and more of my life to AI agents in pursuit of making my life a little simpler. What I found is that AI is unpredictable, and so are AI agents. When I first began using Muse, it started doing things I didn’t ask it to do. It offered to help with random email threads and created dossiers on people in my work meetings. It generated a detailed report on nearby apple-picking destinations based on a calendar invite from my wife. To me, an AI agent doing these things without prompting isn’t helpful. It’s unnerving.

But ultimately, I came away believing that AI agents can make your life easier.

That might mean giving an AI agent more access than you’re comfortable with — handing over lots of login credentials and possibly even your credit card. The more you rely on an AI agent, the more you risk outsourcing your decision-making. This raises real questions about how much agency we want to hold onto in our lives — even the tedious parts.

Let’s get one thing out of the way first: To make an agent work for you, you’ll have to sacrifice a tremendous amount of privacy and grant it permission to access a lot of personal information.

Muse and its competitors can do the classic generative AI tricks, like draft emails or make you a fitness plan. If you’d like the agent to send one of those emails, however, you’ll have to grant it permission to access pretty much everything in your Gmail account. If you want it to schedule workouts, it will need access to your calendar. If you want the agent to buy anything on your behalf, it will need your credit card. If you want it to book your doctor’s appointments, it will need the credentials to log into your healthcare portal. The more permission you grant it, the more the agent can do for you, but that also opens up more opportunities for the agent to misunderstand you or your instructions (more on this in a moment).

This process of sharing your digital life with an AI agent means you’re giving an untold amount of personal information to tech companies, who don’t always behave ethically, and who sell user data for profit. For now, Meta says that it does not share Muse data or conversations with its ad systems, although privacy experts warn that doesn’t really matter since those systems monitor what Muse does on your behalf. Nevertheless, Muse’s early days were filled with security and privacy blunders.

But without all of this info and access, the AI agents aren’t very useful. So if you’re not comfortable letting a bot into all of your accounts, an AI agent is probably never going to be the solution to your digital administrative exhaustion. But even if you are willing to hand that over, there are still other barriers to an agent’s efficiency and effectiveness.

AI agents, like a lot of new software tools (including chatbots), suffer from the blank slate problem. The blank slate problem essentially means that people don’t know how to get started. This might be because you don’t know about the tool’s capabilities, or because you simply don’t know what would be helpful. There might be some trust issues, too.

As with AI in general, we don’t exactly know how AI agents work. That means we don’t know exactly what they can do or how they’ll do it, according to Pattie Maes, a professor of media technology at MIT — so it’s necessary to do a lot of babysitting. “I feel like I’m not gaining a lot of time because I can’t completely trust the system,” Maes told me about her experience with Muse, “and I can’t predict how it will behave and what it will do.”

Some advice I heard from early adopters of these tools, however, is to start small. “In the beginning, it’s very hard to trust that it’s going to just magically do a really big thing,” Julie Zhuo, founder of the AI company Sundial and an early Facebook employee, told me about her experience using personal agents. “So you give it smaller tasks, and once you see it succeed, then I feel like you develop more trust that it can tackle bigger things.”

This is surely why Meta decided that Muse needed an Ideas tab full of small tasks the AI agent can do. Muse will also send you a lot of push notifications to prompt you to do stuff, like reply to specific emails or prepare for a meeting. That detailed report on apple-picking destinations? That was a notification about something I didn’t ask Muse to do. Muse also sent me a notification about a show hosted by a podcast I don’t listen to and another one with details about a Halloween party I wasn’t invited to, as well as several evening digests that included lists of things it had already bugged me about that day. Notifications are either helpful nudges or time-consuming attention thieves, depending on your worldview. However, if you fall into the latter category and turn off the notifications from your always-on personal agent, you’re inevitably forfeiting some friction reduction opportunities.

These agents worked much better when I drove the conversation. While wondering what to do with my new agents, literally staring at the blank slate, cost me some time, I found myself thrilled at how easy basic productivity tasks became. Adding events to my calendar, making to-do lists and then being held accountable for stuff not getting done, being reminded to reply to an email — it was these kinds of simple, administrative chores where I saw personal AI agents really start to save me time.

Other tech journalists seemed to have similar experiences. Eli Tan at the New York Times raved about Muse handling a call to his insurance company. Nicole Nguyen saved time by enlisting Dots for help canceling unwanted subscriptions. Allison Johnson at The Verge had Muse do a whole list of “pebble-in-your-shoe annoyances” she’d been putting off, and among other things, the agent succeeded in helping her buy an entire camping kitchen. Still, she wrote something that stuck with me: “the dirty secret of productivity hacks is that doing more stuff often doesn’t feel like things are being removed from your plate; somehow it just invites more tasks.”

This gets to the heart of one of the big questions I have about AI agents: How helpful are they, really, if it’s this difficult to know what to do with them? There’s a learning curve, sure, where succeeding at one thing gives you an idea to try something else and have some certainty about how well the AI agent will handle the task. But as the notifications roll in, and you spend more and more time texting with a piece of software, how much time are you really freeing up by using these tools? At a point, enlisting an agent with its own computer to do your chores still amounts to using one app to save yourself from using a different app.

The ironies of automation

Even when they have access to a lot of your information, and you’ve come up with some things for them to do, AI agents can be unpredictable. Because despite reading every email in your inbox or scanning every purchase on your latest bank statement, AI agents still can’t read your mind, and you can’t necessarily guess how they’ll interpret your commands. They can misunderstand you and, armed with the keys to your digital life, do some real damage.

Some people are already learning about the unpredictability of AI agents the hard way. One early adopter, Matt Robb, gave Muse the keys to his Facebook Marketplace account and was surprised when buyers started showing up at his front door ready to pick up their purchase. Muse, without asking Robb, had told them where to go. It turns out, without realizing it, Robb had given the agent permission to do so, and the agent had simply decided that the most efficient way to get buyers to Robb’s door was to give them his home address.

This dilemma is an example of a decades-old set of concepts known as the “ironies of automation.” Identified by psychologist Lisanne Bainbridge in a paper published in 1983, the ironies of automation help explain why things go wrong when humans give a machine too much control. As Vera Liao, an electrical engineering and computer science professor at the University of Michigan who studies human–AI interaction, explained to me: More advanced automation leads to more consequential errors, and the more humans rely on automation, the worse we get at catching those errors. “Even in simple tasks like judging whether AI output is wrong, people consistently accept wrong AI outputs even if they could have gotten it right on their own,” Liao said.

In some cases, like the time Muse read a journalist’s private messages, things go wrong as a result of poorly designed software, but more often than not, it’s the fault of the user who gives instructions that are too vague, giving the agent space to get creative, which isn’t always a good thing.

I had my own misunderstanding with Instinct. In a text message, the agent reminded me about a couple of emails I’d received and prompted me to follow up. When I replied to the text, I asked Instinct to show me possible replies to these emails. The AI agent instead just sent the responses it wrote. I audibly gasped.

Looking back at our chat history, I could see why Instinct interpreted my instructions that way. I effectively gave the machine too much control and then failed to manage the automation properly.

Leaning on AI to do your thinking is an example of what psychologists call cognitive offloading, where you employ an external tool to reduce your effort to complete a task. It makes completing the task easier, sure, but you also open yourself to mistakes. In this case, an AI agent took my instructions too literally, and I failed to catch the error. I can only imagine how a small oversight could turn into a cascade of catastrophes that need cleaning up. All it takes is one poorly worded email sent to the wrong person, and you might have hours of explaining to do — all because you were trying to save yourself 30 seconds of writing.

While I was testing all these agents, I talked to a mix of experts and early adopters. Their opinions were decidedly split about whether these tools were useful out of the box, without a ton of oversight and training by the user. The experts, who had all studied AI in academic settings, all brought up the ironies of the automation problem, where AI makes errors that humans can’t catch. And Maes, the MIT professor, pointed at another consequence: By outsourcing so many tasks to agents, we’re actually creating more work for everyone, including the human service workers who have to interact with this technology instead of us.

“There’s just more and more slop,” Maes told me. “We risk, in a world where agents do all the tasks for us, becoming so dependent on them that the world also isn’t created for us to interact with anymore, but it’s only created for our agents to interact with others, with services.” (We’re already seeing versions of how dominant tech platforms can fundamentally reshape real-world spaces: Think of how Starbucks no longer looks like a coffee shop where you can hang out all day, and is instead built and staffed around mobile order pick-up.)

The early adopters were decidedly more optimistic. Matt Van Horn, an entrepreneur who co-founded the ridesharing service that became Lyft, has been tinkering with agents since the craze started late last year. He’s currently telling his friends and family to use Instinct, which he described to me as “the most ambitious and aggressive” AI agent.

“I’ve been pushy with my mom and my wife,” Van Horn told me, “and saying, ‘Hey, you should sign up for this. It’s magical.’”

“My wife does not care about living in the future, but we have four kids,” Van Horn continued. She recently took a picture of a parking ticket and sent it to Instinct, no description, no instructions. Instinct, which had her credit card, just paid the ticket.

At the same time, outsourcing certain chores to AI agents causes real-world problems. Some of these AI agents can make phone calls, for instance, which can lead to some confusion when a human is on the other end of the line. Van Horn told me about the unfortunate time he enlisted an AI agent to reserve a room at a karaoke bar. “The karaoke place said, ‘Are you an AI?’” Van Horn said. “‘I don’t want to talk to an AI. Please connect me to Matt, the person.’ And so Muse had failed to book that for me.” Van Horn, undeterred, found something called Fo, an AI agent that will bring in human help to complete a task. Fo succeeded at making the reservation, although the entire ordeal surely took longer than if Van Horn had picked up the phone himself and talked to the karaoke bar himself.

At best, the times these tools worked and actually saved me time were rather mundane. I made a doctor’s appointment online using Instinct. Zhuo, the early Facebook employee, planned a party for her college reunion — everything from tracking down everyone’s emails to sending out invitations via Paperless Post. But she’s also said these kinds of applications of agentic AI “read more like vitamins than painkillers.” In the startup world, “vitamins” refers to a product that offers a vague benefit, and “painkillers” solve a big, immediate problem. If you’re a startup, you want to sell painkillers.

If you’re ready to give an agent a go, be prepared for the bot to make mistakes, and assume you won’t catch all of them. As Liao, the University of Michigan professor, put it, “Choose to use agents for tasks that you can tolerate the consequences of errors.”

In an effort not to create more emails or alerts or feeds to sift through, I’ve stopped using Muse. Like any new tool, it will get better and more useful as more people use it, so maybe I’ll revisit it in the future. I still have a text thread going with Instinct, however. It messages me from time to time, flagging an email or offering to help with an upcoming event. When there’s a clear payoff to giving the agent the go-ahead, I reply. Otherwise, I leave it on read.