The Musketeers Take Washington + Spotify's Ghost Music + Tool Time

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Speaker 10 Match Group has a new CEO, Kevin. Yeah.
And it is the former CEO of Zillow,

Speaker 10 the sort of real estate company. Yes.
Which I imagine you probably spent some time on Zillow recently as you've been, you know, looking for houses. Yes.

Speaker 10 Well, this raises the question, Kevin, as you're browsing through your Tinder matches, something I know you do a lot,

Speaker 10 do you think that we're soon going to see some sort of a zestimate of that person's worth?

Speaker 11 I think that's a great idea. You know? I think that they should analyze market conditions and say, you know, the market price for, you know, a tall gay man in San Francisco, down 30% from last year.

Speaker 10 That's right. Short kings are having a huge moment.
I just think, to me, I think the Zestimate should say something like, this person probably still has roommates, you know?

Speaker 10 Like, like that sort of information that you want, not that it's bad to have roommates, but you know, it can, it can introduce complexity. And maybe, you know, you want to know that before you swipe.

Speaker 11 I think, you know, how on Zilla, you can see the history of every house or of every property. I think you should be able to like see the entire relationship history.
The entire romantic history.

Speaker 10 The last like three

Speaker 11 romantic partners. Yes.
Two relationships ago, this person got dumped for not being a good communicator.

Speaker 10 I have to say, we've come up with more good product ideas for Tinder in these past five minutes than Tinder has in the past year.

Speaker 11 Call us. Call us.

Speaker 11 I'm Kevin Roos, a tech columnist at the New York Times. I'm Casey Newton from Platformer, and this is Hard Fork.

Speaker 10 This week, the Times Jonathan Swan joins us to discuss Elon Musk's tech takeover of Washington, D.C.

Speaker 10 Then, author Liz Pelley stops by to discuss her new book on Spotify and how its algorithms are reshaping music culture. And finally, it's tool time.

Speaker 10 We'll tell you about the new AI tools we're using and the one that we wish existed.

Speaker 11 Well, Casey, the biggest story in tech this week is actually not happening in the Bay Area where we live. It is happening across this great country in Washington, D.C.

Speaker 10 It sure is, Kevin.

Speaker 11 So Elon Musk and his team at Doge, the Department of Government Efficiency, have been hacking away at the federal government, barging into agencies, demanding data and access to computer systems, basically staging what some people are calling a tech takeover of the federal government.

Speaker 10 Yeah.

Speaker 11 And Musk brought with him to Washington a bunch of people to help him at Doge with this effort, including a number of young men, some of them in their 20s and even reportedly a teenager or two who are helping him with this effort.

Speaker 10 Yeah, including Luke Veritor, who we mentioned on the show in a previous episode, Kevin, because he was part of an effort to decode ancient scrolls using AI.

Speaker 11 Yeah, and together they've been pulling late nights, some of them reportedly literally sleeping in their offices, so that they can work basically around the clock to shrink the federal government.

Speaker 10 Yeah, and they're doing it in some really aggressive and some would say scary ways. They have already gained access to the treasury's payment system.

Speaker 10 They have put on leave nearly the entire workforce of USAID.

Speaker 10 And they have emailed roughly 2 million federal workers, Kevin, offering them the option to resign and allegedly to be paid through the end of September.

Speaker 11 Yes. And the subject line of that email was fork in the road, which is not a hard fork reference

Speaker 11 that we know of.

Speaker 11 But it was the same subject line that was sent to employees at Twitter after Elon Musk took Twitter over, giving them the chance to resign or take severance packages if they didn't want to work there anymore.

Speaker 11 So, Casey, why are we talking about this on Hard Fork this week? We are not a politics show.

Speaker 10 We are not, but Kevin, several listeners emailed us saying we want to know more about what is happening.

Speaker 10 What we're seeing unfold in Washington is unprecedented in the modern history, certainly, of the United States.

Speaker 10 And it involves somebody who has been a main character of this podcast from the beginning in Elon Musk. In 2022, Elon Musk bought and took over Twitter.

Speaker 10 And what is happening at the federal government, while it is infinitely more important than Twitter, is unfolding in a very similar fashion.

Speaker 11 Yeah, I mean, that to me is what brings this into our lane. I feel like the Twitter takeover was sort of the warm-up act for what is happening with Doge and the federal government.

Speaker 11 Many of the same tactics and playbooks that were used to take over Twitter, to purge the disloyal, woke employees of that company as Elon Musk saw them are now being used at a much bigger scale on the federal workforce.

Speaker 11 So we brought in someone who is an expert in politics and Trump and all things Washington.

Speaker 11 Jonathan Swan, my colleague at the New York Times, he was one of the authors of a piece that came out in the Times earlier this week that was basically a broad and sweeping look at all of the ways in which Elon Musk and his allies have been making what they called an aggressive incursion into the federal government.

Speaker 11 Really great story. People should check it out.

Speaker 11 But Jonathan has been covering Trump for years, and he's he's just really got a feel for the pulse of Washington and how people are reacting to Elon Musk's big invasion. Let's bring him in.

Speaker 11 Jonathan Swan, welcome to Hard Fork. Thanks for having me.
So, Jonathan, give us the view from Washington.

Speaker 11 What is the vibe on the ground as Elon Musk and his band of Silicon Valley programmers move around trying to call call the federal government?

Speaker 11 Well,

Speaker 12 it really depends who you talk to. For the career civil servants, it's terror.
I mean, these people don't know if they're going to have jobs.

Speaker 12 They don't, in some cases, don't know if their agency is going to exist in the morning. You know, the website goes dark at USAID.
They get an email after midnight. Don't come into work.

Speaker 12 He's calling their agency evil. They're sort of following him on X.
A lot of it's very opaque. He's got these young guys who work for him at Tesla and some of the other companies.

Speaker 12 Some of them are in their 20s. one of them was like 19,

Speaker 12 and they're roaming around the agencies.

Speaker 12 And they'll do these interviews with folks, but they won't sometimes tell them what their name is because they're worried about being docked. So it's like you imagine you're a civil servant.

Speaker 12 This guy shows up from Doge,

Speaker 12 you know, and he's wearing a t-shirt and a blazer, and he starts basically interrogating you with the questions all being based on the assumption of you are a lazy, worthless, idiotic federal worker.

Speaker 12 Justify your existence to me, please.

Speaker 11 And they're so, well, who are you? Well, I'm not telling you my surname or whatever.

Speaker 10 So this operation is now unfolding. Do we know where it's going?

Speaker 10 Is there a roadmap that anyone can see, or do we just have to rely on reporting that folks like yourself are doing to even understand what is happening and what the plan is?

Speaker 12 We know, broadly speaking, what he wants to do, right? I mean, he has said he wants to cut $2 trillion

Speaker 12 out of the federal budget. The federal budget's around $7 trillion.

Speaker 12 It's almost impossible to imagine how he would actually do that.

Speaker 12 He's since even Elon Musk, who's famous for setting unrealistic expectations and deadlines and what have you at Tesla and SpaceX, he's downscaled that and said, well, maybe we'll get to a trillion.

Speaker 12 Even that would be astonishing. And

Speaker 12 people don't really think that that's plausible. But he wants to cut.
We know that there's an ideological agenda. Agencies that are

Speaker 12 doing things that are seen as not aligned with the Trump movement are going to face more hostility.

Speaker 12 USAID is sort of the platonic ideal of, in their minds, the evil leftist deep state because what is the Trump movement? It's quote unquote America first.

Speaker 12 Well, what is USAID? It's an agency that spends money overseas in foreign aid, humanitarian assistance. They have found themselves in the crosshairs, but so have a bunch of other agencies.

Speaker 12 Their general contempt for the federal workforce was really evident if you just read that email.

Speaker 11 Right, the fork in the road email.

Speaker 12 Yeah. I mean, you guys know this because this is your field, Lady Detect, but, you know, it's basically this email.

Speaker 12 went to almost all federal workers, you know, around 2 million federal workers.

Speaker 12 But the email was, I thought it was really revealing, you know, when you talk about what's his plan, what's his thinking, I thought it was such a revealing document because

Speaker 12 the text of the email basically was, we'd love you to resign. Whoever you are, you are in a lower productivity job and you should resign and take a higher productivity private sector job.

Speaker 12 I don't distinguish between your expertise. I don't distinguish between your experience.
You're all basically worth nothing.

Speaker 11 Yeah. Jonathan, let's talk a little bit about the cast cast and characters here.
So obviously our audience is very familiar with Elon Musk,

Speaker 11 but tell us about the people around him,

Speaker 11 these young men from Silicon Valley that he's brought in with Doge, who everyone's been talking about this week.

Speaker 11 You mentioned some of them are in their early 20s, maybe even one who's a teenager still. Who are they? How many of them are there? Do they have any private or public sector experience?

Speaker 11 Or are they just sort of interns from his companies who he thinks would do a good job helping with this?

Speaker 11 Well, this is a little opaque to me.

Speaker 12 And I have to give credit to my wonderful colleagues, Ryan Mack, Kay Konger, and Teddy Schlieffer. So from what I can understand,

Speaker 12 some of these are like very bright and experienced allies of Elon Musk

Speaker 12 that he's worked with for a long time. You know, Tom Krause, who is, I think, the one that was given access to the treasury payment system.

Speaker 12 And I think he's the the CEO of like a software, cloud software or something.

Speaker 11 One of them deciphered some ancient scrolls. Yeah.
That was his claim to fame. Luke Farator.

Speaker 12 Yeah, you run the gamut from like that guy, the scroll decipherer, to you know, more seasoned people who've worked with Elon Musk for a long time.

Speaker 12 But I will say, it's not actually that clear to me how many of them are there.

Speaker 12 I've heard that there were around 40 at inauguration, and they show up and, you know, they're very confident and they ask a lot of questions and want access to the systems.

Speaker 12 They want to get their hands on the pipes of government and not sort of take the word of career officials telling them what they're doing.

Speaker 11 Man, it just makes me think of every time over the last decade that I've heard some, you know, person in Washington saying, We've got to get more young people interested in government.

Speaker 11 And I just pictured like the monkey's paw curls.

Speaker 11 It's like, you might not have wanted it to go down this way.

Speaker 10 Careful what you you wish for. So, Jonathan, one of Musk's first moves was, as you mentioned, to seize the federal government's payment systems.
Why did he start there?

Speaker 12 So, Musk

Speaker 12 has told people in the administration that in his view, the way to control government is to control the computers.

Speaker 12 He's got a real history of taking interest in the detect, like the really getting down to the nitty-gritty and roaming the floors of the factory. And why do we have this part in this machine?

Speaker 12 Why can't we get rid of it and make it more efficient and cheaper and whatever? So that's the mindset, as far as I can tell from talking to folks in the White House and the government.

Speaker 12 And his view is, I don't want my guys at Doge to sit down with deep state, quote unquote, official ex who's going to tell them everything's great and blah, blah, blah.

Speaker 12 No, I want my guys to have the source code to go in and see for themselves all this nasty fraud. And he's sort of doing a version of what he did with Twitter.

Speaker 12 Like he's trying to publicize things that he he thinks are ridiculous, that money is being spent on. It's the same playbook that we're seeing publicly.

Speaker 11 But with Treasury, I mean, it's really important.

Speaker 12 I mean, this is like, this is really an important part of America's critical infrastructure. I've talked to former senior Treasury officials.

Speaker 11 They were really alarmed.

Speaker 12 This is the outgoing Biden people in December when they got these requests from these Doge

Speaker 12 people saying we need the source code because this payment system, it's literally the payment system that distributes more than $5 trillion a year.

Speaker 12 It's like 88% of federal spending goes through this system. People's social security payments, you know, people depend on this system.
And

Speaker 12 it's historically been managed by a small group of really trusted, really experienced career civil servants.

Speaker 12 As far as I know from talking to former officials, they've never heard of a situation where a political appointee has requested access to this,

Speaker 12 let alone be granted access to it. Now, they are insisting to us that it is quote-unquote read-only access, meaning they can't alter payments.
But even that is considered extraordinary.

Speaker 10 But I mean, here's why I think so many people are concerned about this. The Constitution gives the power to spend money to Congress,

Speaker 10 not to the president. The president cannot unilaterally decide what to spend money on or not spend money on.
So give us a sense of the conversation around the law here.

Speaker 10 And is anyone even trying to make the case that what Musk and his

Speaker 10 colleagues are doing is legal?

Speaker 12 So, firstly, you're absolutely right. Congress has the power of the purse.
There's no question about that. The White House has cast this as a temporary freeze to

Speaker 12 examine the spending to make sure it doesn't conflict with Trump's policy priorities.

Speaker 12 But as Charlie Savage, my colleague, has written, it also appears to plant the seeds of a potential Supreme Court fight over how much power a president has to refuse to spend money that Congress has appropriated.

Speaker 12 So there actually is a legal question here that could be litigated all the way up to the Supreme Court. And Trump's aides, they have long wanted to seize back some of this power to withhold spending.

Speaker 11 Right.

Speaker 11 There's this theory floating around that I want to get your take on that some of this is just a diversion or a tactic that basically they're the Doge folks, they know that not all the things they're doing are legal.

Speaker 11 They know that not all of it will end up passing muster with Trump or with Congress, but they're sort of asking for a foot and expecting, you know, six inches, that they're essentially overreaching on purpose so that even if half of what they're doing gets overturned or overruled or can't actually make it through all of the checks and balances, they will still have gotten a fair bit of what they wanted.

Speaker 11 Do you buy that? Or do you think they legitimately expect all of the things they're doing to stand up?

Speaker 12 Oh, no, no, no, no, no. And, you know, we've written about this.
This is actually a really important part of how they think and their strategy.

Speaker 12 They learned in their first term, it took them a while, but they learned that the most effective way to get really aggressive policies through is to flood the zone, is to do so many things at once that are aggressive that your opposition, and when they think about their opposition, their mental map is the media, Democrats in Congress, and these outside nonprofit groups like the ACLU who are likely to sue them.

Speaker 12 They know that those three

Speaker 12 institutions have a limited amount of resources, right? There's just only so much mental bandwidth to fight them. And so people need to pick their targets.

Speaker 12 Meanwhile, you're shooting bullets through one after the other on all these different issues. And

Speaker 12 that's been absolutely their approach in this onslaught of executive action that we've seen in the last two weeks.

Speaker 11 Yeah, I mean, I'm sure everyone in Washington is very shocked and surprised.

Speaker 11 I imagine there's one group of people who are not all that shocked and surprised, which is Twitter employees or former Twitter employees.

Speaker 11 Casey, this is a question more for you, but like you covered the Musk takeover of Twitter and everything that followed that, including layoffs and budget cuts and general madness.

Speaker 11 As you're watching what's unfolding in Washington, is anything surprising you? Or do you kind of feel like we're just seeing a story we've seen play out before just on a much bigger stage?

Speaker 10 I mean, the playbook is not surprising. We know that this is how Musk operates.
He does have tremendous disdain for anybody who who he did not hire himself, right? And

Speaker 10 so we're seeing so much of the way he treated Twitter employees reflected in the way that he's now treating the workforce of the federal government.

Speaker 10 What I think is so surprising, though, Kevin, is that Twitter was a company that he bought, right? He had the legal right to do most of what he did.

Speaker 10 There were some lawsuits related to some agreements that he maybe broke, but for the most part, he bought the company and it was his right to decide who he wanted to work there and what he wanted to do with them.

Speaker 10 The shocking thing about the case of the federal government was that, as Jonathan just said, this is the richest man in the world. He was not elected.

Speaker 10 He's not presented, you know, Congress with a plan for what he wants to. He's not gotten, you know, consent from the legislative branch.
And so that, to me, is just the real shock.

Speaker 11 Yeah. I mean, to me, these don't feel like perfect comparisons because as you said, one of these is a company and one of these is a, is a government.

Speaker 11 But I am starting to see some parallels in some of the tactics that Elon Musk is using. One of them being this idea of zero-based budgeting.

Speaker 11 So Jonathan, tell us about zero-based budgeting and how it's showing up in Washington.

Speaker 12 Well, it's the idea that you bring a budget to zero and then justify every dollar that you add in spending. So instead of saying, what should we cut?

Speaker 12 It's actually, no, let's start from zero and say, what should we add? And it's just a way of forcing people to justify every single dollar that they spend.

Speaker 12 Elon Musk has told people that the success of this Doge effort, his metric for it will be how many dollars they save per day.

Speaker 12 And to do that, they're looking at the treasury payments, the USAID. He's looking at the federal government's real estate portfolio, property portfolio to see what they can offload.

Speaker 11 So the range is so wide.

Speaker 11 Yeah, I would say, like, to me, what happened at Twitter, to the extent that that can be used as sort of a preview of what might happen in Washington, is that there was sort of two phases of that takeover of what he considered a hostile institution.

Speaker 11 One of them was sort of the operational phase where you try to figure out, you know, who's paying what to whom and what are we, what are we spending money on that we don't need to, and where are the inefficiencies.

Speaker 11 And then there's the ideological purge, which happened when he would go around to Twitter employees and ask them to commit to being extremely hardcore and try to figure out who was on his side and who wasn't and then purge the people who weren't.

Speaker 11 Do you see any signs, Jonathan, in Washington that that kind of thing is happening? Are these Doge people going around

Speaker 11 asking people to pledge their loyalty to the Trump administration, or is that sort of still to come?

Speaker 11 Well,

Speaker 12 I'd have to go back and look at the text of that email that was sent out, but I think loyalty was one of the criteria on that email.

Speaker 12 Certainly, the Trump team has made loyalty absolutely central to the way that they hire people.

Speaker 10 There's been some reporting in the Times, Jonathan, that Elon and his crew want to bring AI into government. Do we know anything about how or what they mean by that?

Speaker 12 I credit my colleagues for this, Kate Conger and Ryan Mack, but this was in our big story on Musk.

Speaker 10 Yes.

Speaker 12 So as we understand it, Musk's allies aim to inject artificial intelligence tools into government systems.

Speaker 11 And the point

Speaker 12 supposedly is to use them to assess contracts and recommend cuts.

Speaker 12 So what they were told, Kate and Ryan, was that on Monday, Thomas Shedd, who's a former Tesla engineer, he's been tapped to lead a technology team at the General Services Administration.

Speaker 12 He told some staff members they hope to put all federal contracts into a centralized system so they could be analyzed by artificial intelligence.

Speaker 12 And I know from my own reporting that Elon Musk, privately for months now has been talking about this idea of using artificial intelligence to identify waste within the federal government.

Speaker 12 And, you know, it doesn't seem like a crazy idea to me conceptually. I mean, use whatever tools you can to figure out where the wasteful spending is.

Speaker 12 Problem is, I don't have visibility into what these tools are. It's all very, very opaque.

Speaker 11 Right. And I think we should say, like, this is not, this part does not feel unprecedented to me.

Speaker 11 Like, you know, the various administrations democratic and republican have tried to bring in the brightest minds in the tech sector to update and modernize some of the creaky outdated systems that many government agencies use we have the u.s digital service there are groups like 18f these groups of technologists who are sort of brought in to try to bring things up to date but that is a process that is established and requires doing things like you know going through a procurement process if you want to use some new ai tool because maybe it's not secure, maybe there are privacy concerns.

Speaker 11 You want to make sure that that is fully vetted before you roll it out into these very important systems.

Speaker 11 It seems very different to have a group of engineers, programmers, product people coming in and just saying, we're going to use these tools whether you like it or not.

Speaker 12 Yeah, I mean, one thing that a source

Speaker 12 mentioned to me the other day, who's been a very senior person in the government, is

Speaker 12 the counterintelligence risks here.

Speaker 12 When you have a bunch of people who are young, who are from Silicon Valley or different private companies moving very fast, very aggressively and getting really sensitive access to the federal government opens up all sorts of espionage opportunities.

Speaker 12 I mean, foreign governments are constantly targeting the American government workforce, looking for vulnerabilities.

Speaker 12 There are all kinds of potential side effects of this that perhaps are not being considered as they move really quickly and aggressively.

Speaker 10 Well, help us think through the next steps here. We know that there are already some lawsuits percolating designed to maybe stop some of this.

Speaker 10 We've also seen Democrats wake up and start protesting.

Speaker 10 But can you give us a read, Jonathan? Like, what do you think is likely to happen over the next week or so?

Speaker 10 Do you imagine that anything is going to put the brakes on Doge or are they just going to sort of have their way with the federal government here?

Speaker 12 Obviously, there are lawsuits.

Speaker 12 One of the challenges with lawsuits in general is that the speed at which Musk is moving and Trump is moving far exceeds, I think, the capacity of the legal system to catch up.

Speaker 12 They're doing so many things at once so quickly that the facts on the ground are changing. In the meantime, a whole bunch of things are happening, you know,

Speaker 12 relief projects in Sudan of, you know, all around the world where U.S.

Speaker 12 foreign aid is helping people have stopped already. So, yes, there's going to be legal challenges.
Some of this won't fly ultimately, but some of it will.

Speaker 12 And we're not seeing much appetite from Congress to assert themselves and assert their authorities. Obviously, the House and Senate are in Republican hands.

Speaker 12 We're not exactly seeing like a very aggressive legislative branch. And

Speaker 12 in terms of Musk himself, the limit on him is the extent to which Trump tolerates him. That's the only kind of limiting principle.

Speaker 12 You know, there's been a lot of people predicting that this relationship would blow up. It's kind of interesting.
He's sort of willing to tolerate a lot more from Elon Musk.

Speaker 12 And it might just be as simple as.

Speaker 12 It's pretty flattering having the richest guy in the world, you know, and pretty convenient having a guy who spent $300 million helping you,

Speaker 12 working for you as Trump sees it. Trump's the president.
Elon Musk can never be president. He was born in South Africa.
You know, from Trump's point of view, great.

Speaker 12 And Elon is the one that's been most aggressive at turning his platform into a vehicle to support Donald Trump.

Speaker 11 Yeah. Jonathan, out here in Silicon Valley, we've spent a lot of time over the past year talking about various types of management changes.

Speaker 11 One of them is founder mode, which is this sort of school of thought that a lot of tech companies have borrowed from Elon Musk, where basically you stop listening to your workers, you take control, you sort of dictate more from the top, and you try to make things as lean and efficient as possible.

Speaker 11 I see what Elon Musk is doing in Washington as an extension of founder mode, which is a kind of corporate authoritarianism.

Speaker 11 But I'm wondering if you think there is a parallel to be drawn here between the way that a company is managed in an industry like tech and the government.

Speaker 11 Or do you think that those are just fundamentally two different things?

Speaker 11 Of course, of course.

Speaker 12 And, you know, you're talking about a federal bureaucracy at a really dangerous time in the world, a complex world, a federal government that

Speaker 12 has to do so many things.

Speaker 12 Make sure our water is clean, make sure our food is safe, take care of our critical infrastructure, manage national security, including cybersecurity, air travel, the break it to fix it mindset.

Speaker 12 Like the break it part of it's pretty important because what gets broken, the stakes are just so much higher when you're talking about the entire country and the federal government.

Speaker 10 Well, I mean, we saw what happened at Twitter, right? Twitter doesn't exist anymore. That was how the Elon Musk approach worked for Twitter.
There's something else now. It's called X.
Not as good.

Speaker 10 Doesn't make as much money. Doesn't have as many people using it.
He tries to sue people just to advertise on it to keep it running. So that's how that's going.

Speaker 10 So I have no confidence that what they're doing is going to lead to some sort of magically more efficient federal government because nothing they have done so far suggests that they have a plan that is centered around taking care of people and making sure that people still get the services that they depend on, which is one of the key reasons the federal government exists.

Speaker 11 John, the quick last question, and then we know you have to go.

Speaker 11 So far, Elon Musk and his Doge, Cadre, have gone after Treasury. They have gone after USAID.
They're reportedly now setting their sites on the Department of Education.

Speaker 11 What are the three next agencies that you think are in their crosshairs?

Speaker 12 Look,

Speaker 12 this is every agency in the government. Although I will say, as far as I can tell, he hasn't really been that involved at the Defense Department.

Speaker 12 But I do expect that that will come because if you're really thinking about how to cut government spending, you can't ignore the Pentagon. It's such a huge...

Speaker 12 And listen, Trump has really tied their hands to a large extent because he said you can't touch Social Security or Medicare, huge entitlement programs. He's promised not to cut money out of them.

Speaker 12 So if you're Elon Musk and you're looking for savings, eventually he's going to have to turn his eye properly to the Pentagon. And I'll be very interested to see what they propose there.

Speaker 12 Again, huge conflict of interest. Elon Musk, SpaceX,

Speaker 12 huge federal contracts. But I'm going to be keeping a close eye on DOD.

Speaker 11 Jonathan Swan, thank you so much for joining us. Thanks, Jonathan.

Speaker 12 Thanks for having me.

Speaker 11 When we come back, writer Liz Pelly tells us why Spotify is increasingly full of ghost musicians. Spooky.

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Speaker 10 Kevin, if you were a streaming music service playlist, what would you be called?

Speaker 11 Probably lo-fi beats to podcast to.

Speaker 10 Hmm, I think of you more as a 2000s hot girl girly pop Wednesday afternoon. But regardless, Kevin, next on our playlist today, we're going to talk about Spotify.
Yes.

Speaker 11 So Spotify is a company that we really haven't spent much time talking about on the show, but I think they are very important within the world of tech companies.

Speaker 10 In part because when we say wherever you get your podcasts, well, Spotify is a place where you can get your podcasts.

Speaker 11 Many of our listeners are probably using Spotify right now. And Spotify has had a big week.
They just reported their first profitable year ever.

Speaker 11 Daniel Eck, the CEO, was quoted as saying, it only took 18 years for us to get here, but we're here. The company now has 675 million users and around 263 million.
premium paying subscribers.

Speaker 11 Their ad-supported revenue is also up. But that's not what we're really here to talk about today.

Speaker 10 No, Kevin, because as popular as Spotify is, a new book argues that the company's rise hasn't necessarily benefited artists or listeners.

Speaker 10 Liz Pelly is a writer based in New York who has a new book out called Mood Machine: The Rise of Spotify and the Costs of the Perfect Playlist.

Speaker 10 And I have to tell you, I was captivated by an excerpt of this book that came out in Harper's Magazine recently. And the excerpt focused on what are sometimes called ghost artists.

Speaker 10 These are musicians who Spotify uses as a way to fill out popular playlists with lower cost music made exclusively for the company instead of songs from major record labels.

Speaker 10 And according to Liz, it is proliferating quite quickly.

Speaker 11 Yeah, so this is the kind of story that doesn't get told about Spotify that often, which is how it is essentially become an invisible force in the music world, shaping the tastes of its hundreds of millions of subscribers in ways that maybe some people, even hardcore Spotify users, don't fully appreciate.

Speaker 10 Yeah, and you know, we've talked about so many many other invisible algorithms on this show that are reshaping culture in one way or another.

Speaker 10 This is our chance to learn how that is unfolding inside Spotify. So let's bring in Liz Pelly.

Speaker 10 Liz Pelly, welcome to Hard Fork.

Speaker 13 Thanks for having me.

Speaker 10 So let's talk about Spotify's evolution as a music service over the years.

Speaker 10 When I first started using it, I really felt like the person in charge of my music listening, I would search for the artist or album I wanted to listen to, I'd play it, and then I'd go look for more.

Speaker 10 And today, though, it feels like it is Spotify that is more in charge, that it is pushing algorithmic and paid recommendations at me every chance it gets. So how did that evolution start?

Speaker 13 When Spotify launched, these things were more like search bars. You would have to know what you were looking for.
You would have to know the artist or the album that you wanted to listen to.

Speaker 13 Because in certain ways, when Spotify launched, it was really sort of competing for the type of music listener who had become accustomed to the kind of digital library that they had access to in the post-Pirate Bay years, the post-Napster years, you know, the type of digital music listener who was used to opening their laptop, opening their music library, and being able to push play on whatever they wanted to hear at any moment.

Speaker 11 Yeah.

Speaker 10 So at some point, Spotify begins pushing people away from this search bar experience and more toward playlists. What's the origin of that?

Speaker 13 So

Speaker 13 up until around 2012, when you looked at the branding of Spotify, the way it sort of characterized itself on its own website, it would really focus on words like

Speaker 13 instant, simple, free, and they would talk about giving you access to a world of music.

Speaker 13 And it really wasn't until later in 2012, around a year after they'd launched in the United States, when the way in which they positioned themselves started to change.

Speaker 13 They had also, around this time, commissioned a research agency to research their user base and try to give them information about what people were actually coming to the platform for.

Speaker 13 And in a sense, they had started to realize that their users weren't only looking for access to music, but were also looking for the ability to get a recommendation or hit play and get

Speaker 13 a feed of appropriate music. So

Speaker 13 the end of 2012, early 2013 is when you start hearing Daniel Eck and the press talking about how, okay, maybe he'd been too precious about this idea of a non-curated service.

Speaker 13 And they started redesigning the homepage. And by 2013, they really started to lean into this idea of a more curated service.

Speaker 11 And that's when I first started hearing about things like the Rap Caviar playlist, which was a very popular playlist that a lot of people were using. And actually, artists were angling to get into it.

Speaker 11 And labels were angling to get their artists into the Spotify playlist because Spotify's increasingly large user base was just sort of, you know, discovering new music through the playlists.

Speaker 11 And so there was an element of that that I feel like is familiar to, you know, radio had the same thing where artists and labels would fight to get their songs played.

Speaker 11 But this started to feel like Spotify was actually getting its own market power because it had all these subscribers and it could sort of start to direct them towards certain music and away from other music.

Speaker 13 Definitely. So as the years went on, these playlists became pretty influential in the music business.

Speaker 13 Like you said, they started to become a really integral part of how record labels thought about promoting music.

Speaker 13 And musicians, both major label and independent musicians alike, started to be pitched on and sold on the promotional opportunities of this whole system.

Speaker 13 When I started writing about Spotify, which is in the mid-2010s, one of the things that was really interesting to me at the time was the way in which independent musicians were being sold on this playlist system as a democratizing force.

Speaker 13 Spotify always said things like, you know, the playlist ecosystem is going to level the playing field.

Speaker 13 And they talked a lot about this pyramid of playlist curation where they would start artists on these low-tier feeder playlists, look at streaming data, and then they would move you up in the playlist system if the song reacted or if there was a high completion rate.

Speaker 13 This was kind of like a myth that was sold to artists, but a lot of independent artists weren't necessarily feeling the magic of this data-driven. supposedly meritocratic system.
Right.

Speaker 10 So, and I want to ask you about that, because I have to say, from my perspective, when it comes to the rise of playlists, that's basically okay with me.

Speaker 10 Like, it sounds from the way that you're talking about it, a lot of the reason that playlists came to be on Spotify was just user demand. People wanted kind of a guide to their music.

Speaker 10 They didn't want to be responsible for thinking up every single thing that they wanted to listen to at any given moment.

Speaker 10 But you write in your book that over time, Spotify became increasingly concerned with shaping user behavior on the platform. So aside from the playlist that you described, how does that manifest?

Speaker 10 How do they try to shape the way that we use the app?

Speaker 13 And I think this is similar to across the platform economy.

Speaker 13 Platforms want to shape user behavior in order to boost engagement, to hook people on their platforms, to extend the amount of minutes and hours that people are spending on their platforms so that people have tighter relationships with their products, see their products as more valuable.

Speaker 13 In the case of a streaming service, a streaming service endeavors to keep people on the platform longer so that they view it as a useful part of their lives and retain their subscriptions, right?

Speaker 11 But it's not just about boosting engagement, right? Because my understanding is that Spotify pays pays out a huge chunk of its revenue to record labels for their music. I mean, billions of dollars

Speaker 11 is paid to artists and record labels.

Speaker 11 And so if you're Spotify and you're trying to grow your business, you could either grow your subscription base or you could just pay out less money to artists and labels. And

Speaker 11 one of the ways that you could do that is by steering people away from sort of headline acts and artists with leverage and negotiating power and the big labels and toward maybe smaller or more lesser known musicians who maybe can't command the same types of market power.

Speaker 11 So is that something that Spotify was also doing?

Speaker 13 Yeah, that's a great point too.

Speaker 13 You know, part of the reason why a streaming platform wants to control more of the user experience is so that they can have more influence over the types of music that is being recommended to users.

Speaker 13 And in the case of Spotify, one of the things that I try to trace throughout my book is this series of cost-saving initiatives that the company developed in order to try to nudge users towards content.

Speaker 13 And I hate using the word content to describe music, but this is how they refer to it.

Speaker 13 In order to nudge users towards content that's cheaper for them to license. So there's two specific

Speaker 13 instances of this that I talk about in the book. One being

Speaker 13 around 2017, this phenomenon that people started to notice where

Speaker 13 their playlists for studying, chilling, sleeping, relaxing, people started noticing that there were tracks on these playlists that didn't necessarily seem to be from artists who were real.

Speaker 13 People were noticing their playlists increasingly filled with what appeared to be royalty-free stock music.

Speaker 13 So one of the investigations in the book is into the rise of what internally at Spotify is called perfect fit content, which is music commissioned for certain playlists and moods with improved margins.

Speaker 11 What you're describing is music that is made for Spotify. It is not Spotify going out and curating music that exists in the world and putting it into playlists.
This is like,

Speaker 11 we want to make a new lo-fi study playlist.

Speaker 11 And so we are going to go out and have a bunch of studio musicians make this music. And then we're going to pay them much less than we would pay Taylor Swift.

Speaker 13 Right. So, you know, there's this handful of production companies that are part of this scheme.
And those production companies will then go find producers and composers who can make this stuff.

Speaker 13 And one of the most interesting parts of reporting my book was talking to a handful of musicians who had made work for these production companies with these privileged deals.

Speaker 13 And, you know, they talk about how sometimes they'd be cranking out 12 or 15 of these tracks in an hour.

Speaker 13 And the idea is to just sort of create as much content as they can to make it as simple as possible so it goes well in the background.

Speaker 13 They'd be studying music on certain playlists provided to them by the production companies as examples, which would basically be songs that had done well in the lean back environment on Spotify previously, and then try to kind of replicate similar styles in order to hopefully make content that would stream really well.

Speaker 11 And I should say, like, I understand the impulse to do this. Like, personally, I am,

Speaker 11 you know, what you might call a lean back listener.

Speaker 11 I listen to a tremendous amount of Spotify many hours a day, mostly in the context of trying to go to sleep and it plays while I'm sleeping or trying to study.

Speaker 11 I'm a huge consumer of all of the like lo-fi, uh, you know, music to study to.

Speaker 11 I assume that most of that is now, like, after reading your book, I assume that most of that is sort of this, this perfect fit content and that artists are not being paid very much for that.

Speaker 11 But I, that is like useful. I don't really care what the music is that puts me to sleep.
I just want some music that's sort of in the right genre with the right kind of sound.

Speaker 11 So that's, I should just say, like, I understand the market forces at work here because I am part of the universe of Spotify subscribers who do use this more ambient kind of music.

Speaker 10 Kevin is one of the reasons why the music industry is falling apart.

Speaker 13 Well, you know, it's interesting because according to some of the interviews that I did,

Speaker 13 a justification that would be used is, yeah, that some of the senior executives would say things like, well, most people don't know and also they don't care.

Speaker 13 And I, you know, I understand that there are certain types of users that won't care, but I think there are certain types of users that would care.

Speaker 13 They can't decide whether or not they care or not if they don't know.

Speaker 13 So one of the things with these cost-saving initiatives to me that stands out as a glaring issue is the fact that none of this material is labeled as sponsored or labeled as, you know, this is being recommended due to a commercial deal.

Speaker 13 I think from the beginning, these sorts of playlists have operated under the umbrella of editorial on streaming services. And we're not just talking about Spotify.

Speaker 13 I think that there is reason to believe that other streaming services are likely engaging in similar practices as well.

Speaker 13 But if something is operating under the umbrella of editorial, I do think that there's some sort of expectation that if something's being recommended due to a commercial partnership, that should be labeled in some way.

Speaker 11 Aaron Powell, Jr.: I completely agree with you.

Speaker 10 And by the way, if they did have to label those things through regulation, you'd see a lot less of it because they would be embarrassed.

Speaker 10 I want to talk, in addition, though, about the effect on the culture. And maybe we should use lo-fi beats as a jumping off point since you brought it up, Kevin.

Speaker 10 There is a chill lo-fi study beats playlist on Spotify that is very popular. It's been saved about 2 million times.
And

Speaker 10 in your book, Liz, you write about how the rise of lo-fi beats really reflects this era.

Speaker 10 I'm curious if you can tell us what lo-fi beats were before it became a big Spotify and YouTube phenomenon.

Speaker 10 Like, what was it as an actual culture before it became like a low-cost alternative to paying record artists?

Speaker 13 Yeah, I think it's interesting to

Speaker 13 know

Speaker 13 that the phenomenon that is now known as lo-fi hip-hop beats to study and relax to had a sort of prehistory online.

Speaker 13 In the early 2010s, the lo-fi hip-hop community online was based more in forums and it's people making these sort of J Dilla Mad Lib inspired beats, sharing them with each other.

Speaker 13 And it was more based on SoundCloud. People were just, you know, making music inspired by these producers that they really loved and that it involved

Speaker 13 more kind of sample flipping, people trying to outdo each other with impressive drums, less sort of mellowed out, not exclusively background music made for studying.

Speaker 13 And according to some of the people I talked to, as this scene

Speaker 13 kind of moved to YouTube, moved to Spotify, as playlist curators got in the game, there was this sort of flattening effect that happened where certain types of music from this subculture was being put onto playlists for studying.

Speaker 13 And then the types of music that did well on playlists for studying was financially incentivized. So more people started making that type of music.

Speaker 10 I mean, that push and pull that you identify is so interesting, right? Where it's like, on one hand, yeah, this doesn't feel great because now people aren't really hearing the authentic lo-fi beats.

Speaker 10 They're hearing the like the cheap version and they don't even know that they're hearing the cheap version.

Speaker 10 But on the other hand, the playlist became so popular that they incentivized the creation of a lot more of this music.

Speaker 10 And so people, you know, wound up hearing a lot more of this thing that they like. So how do you think about that kind of push and pull?

Speaker 10 Is the sort of picture of what Spotify doing to the culture more mixed than just, eh, algorithms are flattening everything?

Speaker 13 I think for me, it's an important distinction is that I don't necessarily just think the issue is that people are listening to less authentic music or that people are listening to fake music.

Speaker 13 For me, my concerns have more to do with with the reality that there are so many independent musicians today who are trying to figure out how to make a living in the streaming era, or maybe not even make a living, but just how to connect meaningfully with listeners in the streaming era.

Speaker 13 And they're all impacted by these practices. One of the things that Spotify would say as a defense was that, you know, they turned to the stuck music because they had found a need for content.

Speaker 13 But there's no shortage of music in genres like lo-vi, hip-hop, jazz, classical, or ambient that fill out these lean back playlists by musicians who could really use the boost.

Speaker 13 So for me, I'm always thinking more about those musicians who are really impacted by being removed from these playlists, replaced with stock music, or who have never been able to access these sorts of promotional opportunities in the streaming era.

Speaker 10 There's a great excerpt of your book in Harper's Magazine that I read and loved and shared on Blue Sky. And I had a surprisingly heated back and forth with a reader who I think was a musician himself.

Speaker 10 And he said to me, essentially, look,

Speaker 10 this ghost musician stuff that you're talking about, this stock music, musicians have always taken stock music gigs to pay the rent, right? It's always been a tough job.

Speaker 10 And, you know, on some level, a gig is just a gig. And so let's not shame musicians for taking, you know, these gigs, making stock music.
And I know that you're not shaming them.

Speaker 10 But I wonder what you made of that argument that this isn't as different as maybe

Speaker 10 we may think.

Speaker 13 Well, I would encourage that person to read my book because I'm not shaming the musicians who make this work.

Speaker 13 And in fact, there's a whole chapter where I talk to a number of musicians who make this work.

Speaker 13 And what I try to explain is that this practice is as deceptive for listeners as it is for them because When I was interviewing musicians who made music for companies that were part of the PFC practice,

Speaker 10 That's the perfect fit content for Spotify.

Speaker 13 Yeah, like these musicians didn't know anything about the broader arrangement that they had signed up to be part of.

Speaker 13 They would tell me things like they make their tracks, they submit them, get paid, and they don't know what happens

Speaker 13 after that. But their arrangements are dictated by their contracts between them and the production company that's hiring them.
So that'll look different from contract to contract.

Speaker 13 Some of them told me that the arrangement was a buyout where they're getting a flat fee for the master, and then maybe there's some other royalty rights that they're entitled to.

Speaker 13 You know, each company has its own arrangement. I talked to a couple of composers from this songwriter advocacy group based in the UK called Ivers Academy.

Speaker 13 And they talked about how from their perspective, they felt like companies like Epidemic Sound in these arrangements are trying to buy composers out of their luck.

Speaker 13 How when you make production music, part of what you're doing is making lots and lots of music.

Speaker 13 You never know which tracks might take off and take on a life of their own own and then end up being a really sustainable source of income for you for years to come.

Speaker 13 And by encouraging these buyouts, encouraging this flat fee model, they were buying out composers' luck and how this sort of, you know, was a change and that composers should hold on to their

Speaker 13 chances of a song going viral or being used in a commercial and them being able to see some success off of it.

Speaker 11 So I think a lot of listeners to our show will be thinking about AI when it comes to the future of services like Spotify.

Speaker 11 We've talked on the show about services like Suno and Yudio, which can basically generate new music along the lines of existing music.

Speaker 11 And to me, it just seems inevitable that at least for these ambient sort of lean back playlists, Spotify will eventually just start creating music on the fly using AI so that they don't have to pay any royalty to any human artist or any production company.

Speaker 11 Is that happening already? And we don't know about it?

Speaker 11 Do you think that this is the future of this kind of music?

Speaker 13 Daniel Eck in the press already in recent years has said things about how he finds the potentials of generative AI music to be exciting, that it could be great culturally and help boost engagement on Spotify.

Speaker 13 So to me, that sort of framing or that optimism about it sort of signals to me that it would seem unsurprising if that direction was explored eventually, though I should say that like in my

Speaker 13 reporting on PFC and ghost music, it's not necessarily something that I directly observed, although companies like Epidemic Sound, who

Speaker 13 work with Spotify in this way, have directly signaled that they're excited about the potential of their composers working with generative AI tools and open to it.

Speaker 13 So it's not definitely not hard to imagine. I think that from my perspective, there are certainly a lot of

Speaker 13 important

Speaker 13 concerns about generative AI content and its impact on streaming services. There already is so much AI generated music flooding streaming services every day, but I also think it's as

Speaker 13 important to remember the different ways in which different systems that might be called AI, systems of machine learning, automated recommendations, algorithmic recommendations, personalization over the past

Speaker 13 15 years have

Speaker 13 reshaped the way that people understand music, our recommended music, the context within which music is served and presented to listeners, I think is

Speaker 13 equally worthy of

Speaker 13 consideration and critique.

Speaker 11 Yeah.

Speaker 10 Let me put some of my own cards on the table. Like, I have to say that Spotify often feels like a miracle in my life.

Speaker 10 Like, I still remember being a high schooler who had to scrimp and save to buy a single CD for $18. And I wanted to know so much more about the canon of pop music.

Speaker 10 And it was just completely inaccessible to me. But now Spotify exists and I can just inhale it.

Speaker 10 But Liz, your writing on this subject really unsettles me because it reveals the extent to which Spotify has built systems to manipulate my listening in ways that are completely invisible to me.

Speaker 10 And I do worry that as the years go on, my tastes in music is becoming less and less my own. So I wanted to ask you

Speaker 10 how you might reconcile those two things or how you think I might reconcile them and how you try to personally cultivate your own taste in music in this age.

Speaker 13 Absolutely. Yeah.
Something that I think can sort of be complicated or seem like a contradiction in some ways is that I actually am in favor of universal access to music.

Speaker 13 I don't think universal access to music is a bad thing. And I'm someone who came up in the era of Napster and file sharing and being able to access

Speaker 13 a lot of music that way was really

Speaker 13 influential and formative for me, I should say.

Speaker 13 So I don't necessarily think that it's universal access to music that's the problem. For me, I think it's more it's the rise of and championing of lean back listening, of a sense of passivity, of this

Speaker 13 devaluing of music, not just on a financial level, but in some ways on a more cultural level, that I think happens when this relationship with music is sort of watered down in this way.

Speaker 13 And of course, Spotify didn't and streaming didn't create these conditions, didn't create the idea of the lean back listener, for example.

Speaker 13 But I think that this way of music has been really exacerbated by streaming by making lean back listening sort of, you know,

Speaker 13 the most frictionless way to engage in music. I think that optimization and frictionlessness has been really disastrous for culture beyond even music.
I'm a music critic also and a cultural critic.

Speaker 13 And

Speaker 13 I think that thinking is really important. And I think that encouraging people to think is really important.
And when I talk to

Speaker 13 former Spotify staffers, when I look at the ways in which optimization and frictionlessness are seen as these goals of streaming curation in the platform era.

Speaker 13 You know, like there was one interview that I did with a former staffer who talked about the goals of the curation ecosystem as trying to reduce cognitive work that people have to do when they open the app.

Speaker 13 In my book, I sort of trace Spotify's long-term goal to create a product where the user can open the app and be met with the perfect recommendation at the perfect moment without having to do any deciding or any choosing or any thinking.

Speaker 11 Well, it seems like the TikTok model just applied to music rather than video.

Speaker 11 I mean, lots of social media platforms have had the same realization that if we just remove all of the choice from the user and just give them an endless scroll of algorithmically selected content, we can keep them hooked for longer because statistically, most people don't want to do the work of searching out the things that they want.

Speaker 11 But that is a very cynical view. And I think, unfortunately, it does appear to be profitable.
I mean, Spotify just had its first profitable year.

Speaker 11 So something they're doing is working, but I'm not sure it's working for culture at large. Yeah.

Speaker 13 I mean, yeah, one of the former Spotify engineers that I spoke with referred to the TikTok feed as the ultimate distillation of

Speaker 13 lean back listening. You know, you're not putting in any input.
You're just giving signals based on how long you linger on something.

Speaker 13 And

Speaker 13 I guess, you know, what I was trying to get at earlier is that as a critic, as someone who thinks a lot about the way in which music is contextualized

Speaker 13 as a way of opening up the possibility of new connections with music,

Speaker 13 to me, this idea of encouraging people to think less about what they're listening to is troubling.

Speaker 13 I think that this process of listening, thinking, deciding, hearing things that you don't like, deciding why you don't like them, being challenged by music that is outside of your comfort zone, like, this is all important from my perspective.

Speaker 11 Yeah.

Speaker 10 I think there should be a ghost musician stage at Coachella this year where everyone who's made these playlists that we listen to all year long, they just get on stage and it's just a little twinkly piano, like, you know, from, I don't know, 8 to 9 p.m.

Speaker 11 I love that.

Speaker 10 Let's give these people some attention.

Speaker 11 And here's my feature request.

Speaker 11 I want a toggle switch on Spotify where before I go to sleep and put on my sleep playlist, I can just say, only use human musicians because those people are performing a valuable service for me.

Speaker 11 And I love the idea of like some obscure classical pianist just waking up to a giant royalty check from Spotify because millions of people have been using their music to fall asleep.

Speaker 10 Spotify, of course, is famous for its giant royalty checks.

Speaker 13 I mean, you know, I write in my book, there's no shortage of really inspiring

Speaker 13 ambient music to be discovered these days by

Speaker 13 actual musicians. So if there was going to be a, you know, ambient stage at a major music festival, I would hope that it was,

Speaker 13 you know, those artists and some of the musicians making the music for these ghost artists playlists have their own creative practices. So I would also, you know, hope that

Speaker 13 they'd be able to share that music.

Speaker 11 No, I'm very glad that we had this conversation because I think I am realizing that I am the problem. It's me.

Speaker 10 Which was my hope with this conversation. So I'm excited too.

Speaker 11 I actually do think that the sort of loss of agency and loss of, you know, taste, essentially, that you're describing in your book applies to me.

Speaker 11 I think that I used to be a person who sought out specific musicians and artists, and I think I have just gotten lazy about that. And so I do actually feel challenged by what you have told us today.

Speaker 11 And I am going to start being more intentional about the music that I choose.

Speaker 10 Well, maybe on our way out, Lizzie, as you mentioned, you are a critic.

Speaker 10 Do you have any ambient, chill, lo-fi artist or artist that you might suggest to Kevin so that when he's in more of a lean back mode, when he wants to hear the genuine article and not the dollar store version, that he might be able to enjoy it.

Speaker 11 Okay.

Speaker 13 I will say that probably my favorite ambient music of the past few years has been

Speaker 13 by Emily A. Sprague, who is a singer of this band called Floris, but also makes ambient music that is really beautiful.
And I would recommend checking out that.

Speaker 10 Perfect. Human beings recommending music to each other, just like in the old time.

Speaker 11 How do you spell that? Emily A.

Speaker 13 S-P-R-A-G-U-E.

Speaker 10 Yeah, and just for a change, Kevin, try listening to Emily while you're awake. I just want you, it might actually improve your appreciation of music.
It would be my guess.

Speaker 11 That's a good tip.

Speaker 10 Liz, fascinating conversation. Congratulations on the book.
Thank you for joining us on Hard 4.

Speaker 13 Thanks so much for having me.

Speaker 11 When we come back, we're going to tell you what AI tools we're using in our new segment called Tool Time.

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Proudly NASDAQ listed, built for the future. Visit arm.com slash discover.

Speaker 14 This podcast is supported by the all-new 2025 Volkswagen Tiguan.

Speaker 11 A massage chair might seem a bit extravagant, especially these days. Eight different settings, adjustable intensity, plus it's heated and it just feels so good.

Speaker 11 Yes, a massage chair might seem a bit extravagant, but when it can come with a car,

Speaker 11 suddenly it seems quite practical. The all-new 2025 Volkswagen Tiguan, packed with premium features like available massaging front seats, it only feels extravagant.

Speaker 11 Well, Casey, it is time for a new segment that we're calling tool time.

Speaker 10 It's tool time.

Speaker 11 Now, if you are a 90s kid, you might remember home improvement.

Speaker 10 Only 90s kids will remember home improvement.

Speaker 11 Tim the Tool Man Taylor had a TV show called Tool Time, but this is different.

Speaker 10 That's right, because whereas Tim Taylor was often working on his car in his garage, we are working on laptops in our home offices.

Speaker 11 Yes, this is more of a knowledge worker tool time.

Speaker 11 But we do get a lot of questions from listeners about the tools that we're using, whether it's AI to help us be more productive at work or maybe just in our personal lives.

Speaker 11 People want to know what is going on out there and what the latest and greatest tools on the market are.

Speaker 10 Yeah, they hear us doing hard work and they think they clearly are not doing this without computer assistance. There is some sort of something that they're using to aid themselves.

Speaker 10 And today we're actually going to tell you what those things are.

Speaker 11 And Casey, this is a segment about AI and AI tools, so we should make our AI disclosures.

Speaker 10 Well, here's one for you, Kevin. Casey's boyfriend works at Anthropic.

Speaker 11 Kevin works for the New York Times, which is currently suing OpenAI and Microsoft over alleged copyright violations related to the training of large language models.

Speaker 11 Is that the first time we've ever referred to ourselves as a third person on the show?

Speaker 11 No, but I kind of like it. All right.
So the first tool that we want to talk about on Tool Time today is Deep Research. This is a new feature out from OpenAI.

Speaker 11 It's available to subscribers to the $200 a month ChatGPT Pro plan, although they have said that they plan to make it more widely available.

Speaker 11 And Casey, just explain deep research for people who haven't heard about it or tried it.

Speaker 10 Sure. So deep research is a way to get a lengthy, extensive, detailed report on a subject that you are interested in.

Speaker 10 You access it through the normal ChatGPT interface, but when you type in your query, you click a button that says deep research. And then deep research will read your query.

Speaker 10 It'll ask you a few follow-up questions so it can try to really hone in on what you want and then it will use this as yet unreleased model called o3

Speaker 10 And so what sort of reports have you been asking deep research to create?

Speaker 11 So I have been experimenting with this and I've been really impressed so far. I mean, I have done it with a couple of different topics.

Speaker 11 One of them, I was just curious about the history of the term AGI, artificial general intelligence.

Speaker 11 And so I I asked Deep Research to make a report for me about, you know, trace the sort of intellectual history of this term and the idea behind it, a computer capable of doing everything the human brain can.

Speaker 11 And first it asked me some questions to clarify. It said, are you looking for an academic style research document with citations or a more general historical overview?

Speaker 11 What timeframe should I focus on? Do you want to include like science fiction or just general references to scholars and other people talking about AGI.

Speaker 11 And I answered those questions and then it went away for 10 minutes. It consulted 36 sources and it returned a seven or eight page report about the intellectual history of the term AGI.

Speaker 10 Right. And as you read through this report,

Speaker 10 what did you notice? Like, is this a sort of subject where you actually had a lot of familiarity with and so you were able to kind of follow it?

Speaker 10 Or was this something that where you really didn't know a lot of the information that it was telling you?

Speaker 11 So I have done this kind of research project before for my last book i i did a document very similar to this and um this was good it was really good it went all the way back to 1956 to the dartmouth workshop where the term artificial intelligence was coined it went back even further than that into the 17th century when thomas hobbes uh talked about how reasoning was akin to computation so it just traced like the the entire intellectual history of this term and i i didn't see anything obviously wrong in it and when i started checking some of the citations, it actually all looked pretty good.

Speaker 10 Well, I have been doing my own explorations with deep research, and I have to say, this feels like the first good AI agent.

Speaker 10 There's been a lot of talk over the past six months in particular about how this next era of AI is going to be these advanced tools that can do multi-step projects on your behalf in the background while you're not paying attention.

Speaker 10 I haven't used any so far that felt like they were meeting that bar until this one. I'm somebody who writes a column three times a week.

Speaker 10 That column is usually rooted in some set of historical events that I need to refresh my memory about.

Speaker 10 And because it involves subjects I've written about before, I'm a little bit more confident as I am using it because while it does make mistakes, and I have to say, I have never done a deep research report where I have not found at least one mistake.

Speaker 10 Other stuff is actually true. And more importantly, it helps to to structure my thinking a bit, right? It can create a timeline of events for me.

Speaker 10 It can bracket out different ideas into different buckets and offer citations.

Speaker 10 And, you know, I have to say, if I had an editorial assistant and I said, hey, in the next hour, put together a report for me about, you know, this sort of thing, I would be surprised if they could do something that comprehensive in that short amount of time.

Speaker 11 Yeah. So I think it's also useful for just more personal things.

Speaker 11 One of the things that I had deep research do, I have this stack of parenting books that I have been meaning to read ever since like before my kid was born. And I just never got around to it.

Speaker 11 A lot of the advice in parenting books sort of overlaps with itself or overlaps with other books.

Speaker 11 So it's not a very efficient way of like understanding sort of what you're supposed to do when a toddler is having a temper tantrum or something.

Speaker 11 And so I basically just said, go off, read all of the things you can from this set of, you know, parenting literature and like give me the cliff notes. And it went out and it did that pretty well.

Speaker 10 Wow. And so now for the first time you'll know what to do when your toddler throws a tantrum which is what by the way

Speaker 11 well i i haven't made my way through the 10 000 word report yet but i'll get there and i'll let you know so we should say deep research from open ai this is not the only deep research tool on the market google also has a product called gemini deep research um how would you say this stacks up to other similar tools that you have tried so i mean in short google's version is not as good that is to be expected google is using a regular large language model, whereas OpenAI is using what they call a reasoning model, which is just built better to do this sort of thing.

Speaker 10 I think the fact that OpenAI asks questions before it gets to work is really, really useful because it does help you hone in on what you want.

Speaker 10 You can also watch the chain of thought as it goes. We talked about this recently with DeepSeek.
It does something similar where you can sort of try to understand what is this model doing.

Speaker 10 And if it's doing something you don't like, you can sort of ask a follow-up later to maybe guide it better.

Speaker 10 And then finally, you just get much longer output. So when I ran similar queries in Google's version and OpenAI's version, OpenAI's version was generally at least twice as long.

Speaker 10 That's a mixed blessing, of course, because now you have twice as much stuff to read. But in general, I found it much more comprehensive.

Speaker 10 The final thing that I would say was there is just more stuff in the OpenAI deep research results that feels like thinking.

Speaker 10 And I know that will drive some people crazy and they will scream at us and say you're anthropomorphizing these things.

Speaker 10 But I'm telling you, while I do not think that the AI is sentient, I do think it can create very good human reasoning that can sort of verge on the insightful. And that's really powerful.

Speaker 10 And it is something that Google's version cannot yet do. What do you think?

Speaker 11 Yeah, I think deep research is really useful. And I think it's potentially a very big deal.
I mean, a lot of white collar knowledge work is about. research.

Speaker 11 That is sort of the one of the fundamental tasks involved in jobs like consulting or

Speaker 11 even finance or journalism. Like knowing the sort of capsule history of the thing that you are writing or thinking or preparing a presentation about is often quite useful and pretty time consuming.

Speaker 11 So I think the implications of tools like deep research on the sort of white collar labor market are potentially very steep.

Speaker 11 But just as a tool, I think this is very useful already for people who want to quickly get up to speed on new topics. It's a very good learning tool.
I've been using it to teach myself things.

Speaker 11 So right now you only get 100 queries per month, even if you pay $200 a month to OpenAI for the pro subscription. It is very compute intensive and you are somewhat limited in what you can do.

Speaker 11 But I think we should keep tabs on this. And I'm personally going to keep my pro subscription just so that I can have access to this.

Speaker 10 I feel the same way.

Speaker 10 So I subscribed to ChatGPT Pro within the past couple of weeks because I wanted access to this operator agent, which it released a week ago, which we talked about in our most recent episode.

Speaker 10 And I used it and I wrote about it and I thought, I don't want to use this anymore. It's not that good.
So I was truly getting ready to cancel.

Speaker 10 And then OpenAI said, well, if you subscribe to Pro, we'll also throw in these 100 deep research queries a month. And I thought, that actually might be worth 200 bucks a month to me.

Speaker 11 Totally. All right.
Next tool on our list. This is a tool that I've been using for the past week or two called Granola AI.
Casey, are you a granola user?

Speaker 10 I am. And this one tickled me because I had started using granola in November, I think, and I just hadn't mentioned it to you yet.

Speaker 10 And so when you told me you were into it, I was like, that's cool, because I am too.

Speaker 11 So the way Granola AI works is it's an app, you download it, you install it on your computer. And then anytime you open a new video meeting, like a Zoom or a Google Meet or

Speaker 10 a Cisco WebEx

Speaker 11 or a Cisco WebEx, if you're still at one of the three companies in America that still uses that.

Speaker 11 You can have Granola take notes on your meeting. And what it does is sort of interesting.
It's not recording the meeting.

Speaker 11 I'm sure you've also seen these meeting note-taking tools where kind of the robot joins the video meeting as a sort of, you know, hidden participant and records and transcribes.

Speaker 11 Granola works slightly differently. It doesn't record the meeting.

Speaker 11 It basically just takes the sound that's coming out of your computer and transcribes it in real time and then presents you with a pretty detailed summary of what happened in the meeting.

Speaker 11 So if you are a person who likes to take notes on meetings, this is a good replacement for that.

Speaker 11 It's also got some cool features where you can like chat with the meeting transcript afterwards and you can say, you know, what did Bob say?

Speaker 11 What are some action items that we might want to, that might come out of this?

Speaker 10 I used it to say, what was Kevin's worst idea this week in our editorial planning meeting?

Speaker 11 So I have found this very useful. What about you?

Speaker 10 Yeah, I have as well. And look, I'm sure that at this point, people have seen these AI note takers.
They might be wondering, what's so, you know, special about this one?

Speaker 10 To me, what has made it stand apart is in these summaries that it gives you after the meeting. Like it's really good at identifying here were the most important things that came up.

Speaker 10 Oh, did you talk about some sort of milestone in the media? We're going to put that at the top.

Speaker 10 Were the things you wanted to work on? That's going to be at the top. And so it's just really smart.
And they have different templates depending on what you're doing.

Speaker 10 So Granola, I think some of their first big users were venture capitalists. And many of the meetings that VCs are taking are people who are pitching them for their startups.

Speaker 10 So Granola has a template for that. So, it like the AI essentially knows what information to look for that is going to be useful to a VC afterwards.

Speaker 10 Similarly, you know, if you have a one-on-one meeting with the same person every week, Granola has a template for that.

Speaker 10 So, it's really bringing in a lot of structure to the kinds of regular standing meetings that people have and just making those notes super useful.

Speaker 11 Yeah, I like the feature where if you have like a bullet point of something that happened in the meeting, you can click on it in the granola transcript and it will like sort of enhance that by giving you like a direct quote from the part of the conversation where you were talking about that thing.

Speaker 11 It sort of like hones in on the sentence or the two sentences that most directly talk about the thing in the bullet point.

Speaker 10 Yeah, now I will say granola is not perfect for me as a journalist because I want to be able to use this for my interviews as well.

Speaker 10 But because it is not keeping a recording, I have to use something else in addition, right?

Speaker 10 Because sometimes I actually do need a direct quote and I need to double-check it to make sure I'm quoting the person absolutely accurately, right?

Speaker 10 So I actually just wrote in to the like hello at granola email address and be like, hi, I'm a journalist. I would really like it if I could do that.

Speaker 10 And they wound up putting me on a meet with the CEO. And I got to make my case in real time.

Speaker 10 And, you know, what I learned was basically they've been nervous to do this sort of thing because they like the fact that they don't keep recordings. It feels much more private and secure.

Speaker 10 And I respect that. I think it's good to build technologies that preserve privacy.

Speaker 10 But I'm like, man, if Granola did this, then I could get rid of my other thing that does the other, you know, that does that part for me. Yeah.

Speaker 11 But we should talk about this because because this is an interesting question that's come up a few times in my usage of this which is that because it is not joining your meetings it can be running in the background without the other person that you're talking to or the people that you're talking to knowing so Do you have any privacy concerns about using a note-taking AI like this without informing the other person?

Speaker 10 I mean, look, as a podcaster, I assume I'm being recorded at all times. And when I'm not, I get upset because I think we got to use that for the podcast.

Speaker 10 But yeah, I mean, certainly when you are recording somebody in an interview setting, you always want to tell them that you're doing that up front obviously there are circumstances where you don't want to be recorded or the other person doesn't want you to record them you kind of have to work that out um but you know i think for the most part if you're in meetings it's because you're generating some sort of information that you want to use afterward and having a tech tool that helps you do that makes all the sense in the world to me yeah you know granola has a page up on their website saying you should definitely get people's consent before you do this um i did not get the uh consent of our editorial team before i started using this in meetings although i did notify them afterwards.

Speaker 11 So I apologize. I'm sorry.

Speaker 10 Well, let me just say, you're in a lot of legal hot water, my friend. So lawyer up.

Speaker 11 All right, Casey, the third tool that I want to talk about today is not really a tool. It is a request for a tool.

Speaker 11 So for months now, I have been. wishing and hoping for a tool that would essentially allow me to automate my email.
Email overload is a huge problem for me. I get way more email than I can deal with.

Speaker 11 I spend hours a day trying to slog through my inbox. It is a huge time expenditure.

Speaker 11 And so one of the exciting things for me when large language models came on the scene was like, maybe I can have an AI sort of take a first pass at responding to my emails or at least the ones, at least populate a draft for me that I can just sort of go through and click send on or edit to my own liking.

Speaker 11 But that tool has not arrived yet, at least in a form that I have used. So Casey, when it comes to AI and email, what have you tried? What are you using?

Speaker 11 What's your level of automation of your own email inbox?

Speaker 10 It is much lower than I want it to be, Kevin. I have all of the same frustrations that you do.
When I look at email,

Speaker 10 I see a data extraction problem, right? There are only like nine or 10 different kinds of emails that I get. You know, some of them are pitches for me to write about.

Speaker 10 Some of them are people who are inviting me somewhere. Some are people who want me to go on the radio.

Speaker 10 And it seems like it should be almost trivial at this point for some kind of AI to just notice that, bucket it out, draft responses, and let me just click a couple of buttons and be done with it.

Speaker 10 But nothing I have tried gets close. I have tried two different AI-enhanced email apps so far.
One is in a very early beta Notion, which makes the popular collaboration software.

Speaker 10 They have a Notion mail client. I don't want to give a full review of that one because it truly isn't beta.

Speaker 10 They're making a lot of changes over there, but I would just say that so far it has not been able to do what I wanted it to do.

Speaker 10 The other one i tried is called shortwave um which i like paid a subscription for which sort of promised to do what i just described in terms of extracting all of that data out of my email i just found like it couldn't do that you know i remember running the query like um of the emails in my inbox which ones have action items that i need to do and it just it completely failed to do that so you know i i canceled the ceo emailed me and was like you know we're changing it we're making it better and i'm sure they have improved it since the last time i use it but i got to say i have felt burned by my experiences with AI email, and so I am no longer using them.

Speaker 11 What about you?

Speaker 11 So I have been interested in a few different solutions here, but one of the things that worries me about these third-party apps is I don't want to send, you know, I have 20 years of Gmail sitting in my account.

Speaker 11 And I don't want to send all of those emails to a company that I don't necessarily trust to keep that information private.

Speaker 11 All these apps that are sort of popping up, they want to learn how to write like you, which involves ingesting a ton of your previous emails. And that's just a privacy concern for me.

Speaker 11 I don't want to hand over that many years of my email to OpenAI or Anthropic or another company without knowing if they're training on that or retaining that in some way.

Speaker 11 So what I've been trying to do is to build my own homespun email autopilot app. So a couple of days ago, I went into Claude and I just said, here's my problem.

Speaker 11 I want it to all run locally on my machine so that it's not sending my emails anywhere else. And can you help me build it?

Speaker 10 And can it?

Speaker 11 Well, TBD. Because so far, I've only been working on it for a few days, but what I have is sort of a bad prototype now.

Speaker 11 Claude helped me sort of install local LLMs on my machine.

Speaker 11 We've been going back and forth about how this app should work, how it's going to learn from an archive of my old emails, how to write like me, but it is still pretty buggy.

Speaker 11 It did start responding to spam emails emails for me.

Speaker 10 So I just like, would I, I, I would, it said, this sounds amazing. I'll take all that Viagra that you got.

Speaker 11 So I still have to do some more fine-tuning, but I think I am rapidly approaching the limits of my own very limited programming skill.

Speaker 11 And so if there are any hard fork listeners out there who are programmers, and I know there are,

Speaker 11 You would earn my undying devotion and gratitude if you helped me build an app that would do essentially the following.

Speaker 11 Three or four times a day, scan my inbox, pick out anything important and draft or apply to it.

Speaker 11 Populate a little box and give me one button that I can hit to send it or another button that I can hit to edit it.

Speaker 11 Also give me a digest every day of the most important things that happened in my email inbox and any action items. If you're feeling fancy, connect to my calendar.

Speaker 11 But you don't even have to really do that. I would just settle for the email drafting tool that I just described.

Speaker 10 Yeah, I think that that's beautiful. And I would like to make a prediction, Kevin.
What's that?

Speaker 10 We are going to publish this podcast and you are going to get several emails from people who make email apps and they're going to tell you, we can actually do this already.

Speaker 10 And then you're going to go through the trouble of setting it up and then you're going to find it cannot actually do that. I don't know why this happens, but this happens.
Okay.

Speaker 11 I need to send another message.

Speaker 10 What's that?

Speaker 11 This is to the people who listen to this podcast who work at the Google Corporation.

Speaker 10 The total bardasses.

Speaker 11 The total bardasses. I need you to do this yesterday.
You have my email. You know everything about me.
You have my browsing history. You have my photos.

Speaker 11 You know everyone that I've ever contacted in my life and everywhere that I've ever been and everything that I've ever searched for.

Speaker 11 The fact that there is not a tool built into Gmail that allows you to put your inbox on autopilot is a failure of imagination, and I want it fixed.

Speaker 10 This sounds like a great job for 2.0 flash thinking experimental apps, Kevin.

Speaker 10 That, of course, is a new model that Google released.

Speaker 11 this week. Okay, so Casey, let's end this tool time segment with a question from a listener.

Speaker 10 Love a listener question.

Speaker 11 So this came in just today. It's from a listener named Ray Keen, and we're keen to answer it.

Speaker 11 And he asks, if you were to choose just one paid subscription, I guess he means AI subscription, which would it be? So Casey, what is the answer for you?

Speaker 10 You know what's crazy about this question, Kevin, is that I feel like my answer to it probably changed within the past couple of days.

Speaker 10 Because I think the truth is that if I could only pay for one AI subscription, if I'm on some sort of desert island with only one AI, it would be ChatGPT Pro. And the reason really is deep research.

Speaker 10 You know, we've talked before about how the AI labs are mostly at parity when it comes to the basic questions that people ask. Some

Speaker 10 LLMs seem to have like a better personality. Maybe they're a little bit better at mentoring, tutoring, coaching, whatever.

Speaker 10 But deep research felt useful to me in a way that made me feel like I am going to use this most days now.

Speaker 10 And I don't think I would want to be without it.

Speaker 10 So, I don't know, maybe a week or two will go by, and the bloom will come off the rose, and I'll say, oh yeah, this deep research thing, like it turns out I don't actually want to read three 10,000 word reports a day, but right now I feel like that, you know, obviously at $200 a month is extremely expensive for a software subscription.

Speaker 10 But if I can only pick one, I think it'd be that. How about you?

Speaker 11 Yeah, I think it's good for people who have an interest in this stuff to at least try the latest and greatest coming out from Open

Speaker 11 But for me, the answer to this question is Claude. I pay for Claude, the pro version.
It's 20 bucks a month. And Claude has some limitations.
It can't browse the web. It's not good at everything.

Speaker 11 It doesn't have some of the same multimodal capabilities that some of the OpenAI models do. But it is just a very good daily driver all-around AI model for the things that I use it for.

Speaker 10 Yeah, makes sense. Claude is really, really great.

Speaker 10 But I do wish it could browse the web. And I do wish it had some sort of research feature or even just a reasoning model yeah yeah

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Speaker 11 A massage chair might seem a bit extravagant, especially these days. Eight different settings, adjustable intensity, plus it's heated, and it just feels so good.

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Speaker 11 Hard Fork is produced by Whitney Jones and Rachel Cohn. We're edited this week by Rachel Dry and fact-checked by Ina Alvarado.
Today's show was engineered by Chris Wood.

Speaker 11 Original music by Alicia Bautup, Marion Lozano, Rowan Nemostowe, and Dan Powell. Our executive producer is Jen Poyant.
Our audience editor is Nell Galogli. Video production by Chris Schott.

Speaker 11 Special thanks to Paula Schuman, Hui Wing Tam, Dahlia Haddad, and Jeffrey Miranda. You can email us at hardfork at nytimes.com.
And hopefully, my email autopilot bot will respond.