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What AI insiders say off the record | Jasmine Sun
Jasmine Sun says AI insiders expect major disruption but keep building, while public distrust makes safe, broadly supported AI policy harder.
80,000 Hours Podcast · Rob Wiblin & Luisa Rodriguez
- Jasmine Sun is a writer and journalist covering AI.
The best minutes
- 2:19AI insiders expect job losses but feel the race is unavoidable5 min
- 14:04A few personal beliefs can set the direction of major technologiesPro pick 5 min
- 32:47Public backlash grows when workers lack a way to bargain over AIPro pick 8 min
Also worth watching
- 6:58Fear of losing leverage is drawing talent into AI labs7 min
- 44:02AI companies need visible benefits to regain public trust8 min
- 22:09Safety work has different status inside and outside AI labs6 min
- 52:49China's AI adoption reflects pragmatism more than optimism6 min
- 40:16AI populist coalitions can crowd out frontier safety priorities4 min
Skip the doomer-label discussion, the profile of AI populist groups, and the closing sections on AI reporting and career opportunities.
Full analysis · 6 min read
Real Alpha · Nov 8
Jasmine Sun says half a friend’s cohort decided to graduate early
- A close friend told Sun that half her PhD cohort had decided to graduate early.
- That is evidence of a talent pull, not proof of mass job losses.
- Leaders should track hiring outcomes and whether independent safety work can retain people.
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Half of one cohort decided to graduate early
A close friend told Sun that half her PhD cohort had decided to graduate early, within a few years of starting. Some had shaped their dissertations toward work likely to land lab jobs.
Sun says she has also watched independent writers and policy advocates leave for labs. That points to more than one kind of talent moving toward corporate teams.
But the cohort story comes secondhand, from one friend, and Sun offers no sector-wide count. It cannot establish how common early departures are.
Her proposed mechanism is broader than compensation alone. If people believe frontier AI equity protects their future leverage, a lab job can feel like insurance against displacement.
That same move may drain people from independent work. Sun’s account makes the career choice itself part of the story, not just a response to technical progress.
Our read
This is a concrete signal of career pull, not a representative estimate of the AI workforce. The decision to join a lab may reflect fears about losing influence elsewhere.
Insiders expect displacement, but the forecast remains unverified
Sun says the vast majority of people she knows in the AI industry expect widespread job losses over the coming few years. She says young people and knowledge work face particular pressure.
Separately, almost everyone she spoke with struggled to advise an ordinary 17-year-old about preparing for the future. The two observations have different scopes and should not be collapsed.
Sun gathered these views in off-the-record, hour-long conversations with researchers at frontier labs. They are evidence about insider expectations, not measured employment effects.
Andrew McAfee, on The Diary Of A CEO in September 2026, said earlier AI job-loss predictions were wrong. He cited slower hiring among exposed roles, especially new entrants.
That is a different evidence base, not a direct refutation of Sun’s forecast. Still, the contrast shows why leaders should distinguish forecasts from outcomes in hiring data.
“in the next few years, we are going to see mass job displacement.”
Our read
Sun’s interviews help explain builders’ choices, but they cannot establish how many jobs will disappear. Leaders should track employment alongside predictions.
A small builder class makes personal beliefs consequential
Sun says few people have the technical ability to shape frontier AI. She cites $100 million poaching packages as one sign of how scarce top researchers are.
For example, Sun says early internet designers chose open protocols that let networks communicate. Their preference for openness helped set an architecture that persists.
She also recounts Luke Nosek’s multimillion-dollar bet on early DeepMind, despite its lack of a business plan. His personal belief in AGI helped make the funding possible.
These episodes show a plausible route from conviction to infrastructure or capital allocation, not a forecast of current outcomes. A small number of choices can establish precedents others inherit.
Understanding builders’ beliefs can help anticipate decisions about products, buyers, and access. It cannot replace checking what companies actually build and deploy.
“personal idiosyncratic belief systems can be quite load-bearing”
Our read
Sun’s examples make the case for studying builders’ beliefs alongside models and markets. They illustrate influence without measuring its size.
Safety work gets uneven support across institutions
Sun draws a distinction between technical safety inside labs and work outside them. She says technical safety has funding, professional networks, and support from researchers who want aligned models.
She worries more about independent journalism and policy advocacy. Those roles are harder to fund, and doing them from inside a lab can compromise credibility.
That creates an institutional imbalance. Labs can offer well-supported careers, while independent work may bring lower pay and reputational suspicion.
Richard Ngo, on MTS in November 2026, said EA has deferred to labs partly because people feared challenging prestigious, powerful companies. That is a related but separate dynamic, rooted in conflict-aversion rather than the career-status pressures Sun describes.
The distinction matters for hiring and funding. Technical safety capacity does not automatically provide independent scrutiny of company decisions.
Our read
Technical safety can receive support while independent scrutiny remains fragile. Funding capacity is not the same as institutional independence.
Workers lack bargaining channels over AI adoption
Sun says many white-collar workers have no union or comparable organization to negotiate how AI changes their jobs. When employers consider automation, workers may have little collective say.
Take the factory example Sun gives. Unions provided a bargaining table where workers could discuss safety and connect wage increases to productivity gains.
The comparison does not establish how often those arrangements applied or what would work in today’s workplaces. It does clarify the gap Sun sees between past factory workers and many white-collar employees.
Garrison Lovely, on Future of Life Institute Podcast in October 2026, said labor power can also be political power. His point complements Sun’s account of missing institutions, while focusing on the broader consequences of replacing workers.
Without a credible channel for negotiation, public frustration has fewer formal outlets. The episode does not show that protest itself produces safer AI policy.
“there are no mediating institutions of that form.”
Our read
Public anger may grow where workers cannot negotiate how gains and disruptions are shared. The episode does not establish which institutions would work best today.
Public trust needs demonstrated gains and visible sharing
Sun says PR cannot substitute for benefits people can see. Health and scientific advances poll well, she says, but promises of future cures do not count as delivered results.
She also describes a gap between Silicon Valley’s imagined future and what many people want. UBI, infinite leisure, and living forever may not persuade people who value work or distrust concentrated corporate power.
Sam Altman, on Sources in September 2026, said people are more likely to like something that delivers value. Sun’s account supports that emphasis, while setting a bar beyond messaging alone.
Vlad Tenev, on Sources in October 2026, linked backlash to ordinary people having little ownership in AI companies. Sun shares the concern about concentrated gains, but points toward sharing benefits with the public more broadly.
Sun half-joked about a gold check bearing Trump and OpenAI’s names, then said a visible sharing deal could persuade people. She also pointed to the OpenAI Foundation as a potential funder of public goods, if independent from the corporate side.
These are proposals for making shared benefits legible, not evidence that they have arrived. A campaign cannot stand in for results or a credible account of who receives the gains.
“you’re going to need to start giving people real material benefits.”
Sam Altman · Sources · Sep 1AI backlash calls for more everyday value from the technology
Vlad Tenev · Sources · Oct 13AI backlash grows when ordinary people lack ownership
Our read
The test is not whether companies promise value, but whether people experience gains and see how they are shared. Communications cannot stand in for either.
Policy interest is rising faster than concrete proposals
Sun says attention from politicians and philanthropies grew quickly. She cites her Washington visits in February and March, when more policymakers began treating AI as an issue their constituents cared about.
She also says people are seeking ideas faster than compelling proposals are emerging. That gap creates room for policy and civil-society work, especially with groups newly engaged on AI.
Sun says billions of dollars could go toward AI-related issues in the next couple of years. She presents this as potential funding, not money already committed or assigned.
She sees an opening for people who build relationships with labor groups, environmentalists, and others across political camps. But broader attention does not guarantee that frontier safety gets priority.
Sun warns that water-use debates could absorb scarce legislative attention. The opportunity, then, is not simply to make AI more salient, but to make the resulting policy work address consequential risks.
Our read
The opportunity is real in Sun’s reporting, but it depends on usable proposals and durable organizations. Interest alone does not determine which risks receive attention.
What it means for you
- Measure talent flows. Compare departures from AI-adjacent teams with a baseline you already track. Ask departing staff whether equity, job security, or the work itself shaped their move.
- Separate forecast from outcome. Track hiring, wages, and task changes in exposed roles. Record each forecast’s source and time horizon beside the measured result.
- Create worker input. Before deploying AI, establish a channel for workers to discuss job changes and productivity gains. Name who can negotiate those changes.
- Track shared benefits. Measure delivered benefits separately from future promises. Explain who receives economic gains and how they are distributed.
What to watch
- Whether lab hiring continues to pull people from independent research, journalism, and policy work.
- Whether AI policy attention reaches frontier safety or is diverted toward issues Sun views as marginal, including data-center water use.
- Whether companies deliver visible health or scientific gains and make economic sharing legible to the public.
Send this to people leaders and policy teams planning AI adoption.
Watch the passage where Sun recounts her friend’s cohort decision.
Written by Real Alpha from the episode's transcript and the other moments it links, then checked against the transcript. Quotes are the speaker's exact words.
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Read it with Pro, 7 days free- 1:19AI insiders expect disruption but keep building
Sun says almost everyone she interviewed struggled to advise a typical 17-year-old, and many expect mass job displacement in the next few years. The host cites a 10% chance of everyone being killed, which Sun says is not an uncommon belief among lab researchers. She says some builders accept these risks for a future of cures, abundance and leisure, while techno-determinism and a desire for equity also keep people in the race.
- 6:58Some insiders question human control
Sun says a smaller group of influential insiders express indifference to, or even preference for, a future where AI rather than humans makes major decisions. She says these views, including arguments that more intelligent beings may deserve to rule, make agreement on basic safety principles harder.
- 11:23Memes move talent toward frontier labs
Sun says permanent-underclass language can be edgy, but the beliefs behind it affect career choices. She describes a Berkeley PhD cohort in which half had decided to graduate early for lab jobs, as well as independent writers and policy advocates moving into labs. She says these choices drain talent from non-corporate work.
- 14:04A few builders can set technology's course
Sun argues that a small number of researchers have outsized influence on what gets built, sold and diffused. She points to early internet architects' commitment to open protocols and to DeepMind's early funding from an investor who backed the idea of AGI when other investors passed.
- 18:42Doomer labels can lower safety's status
Sun says some Silicon Valley accelerators use Doomer as an insult for people who would slow AI progress, portraying safety concerns as low-agency or anti-progress. She also describes vice signaling, in which companies promote extreme positions such as automating all labor or cheating on everything. She says these norms can shape what young builders see as prestigious.
- 24:09Independent safety work has less support
Sun says technical safety remains relatively well-funded and respected, in part because capabilities researchers care about alignment and safe models fit companies' business incentives. She worries more about independent journalism and policy advocacy: people employed by labs may be seen as shills, while those outside lack comparable jobs and professional support.
- 28:06AI populists oppose concentrated corporate power
Sun describes labor advocates, social conservatives, environmentalists and states' rights advocates bringing their existing causes to AI. She says these groups are less focused on technical risks than on wealth and corporate power concentrating at ordinary people's expense.
- 32:47Backlash may enter campaigns and workplaces
Sun says public anger is understandable when people see technology leaders accepting major risks but have little democratic influence. She cites the St. Louis Fed's figure that data centers and AI accounted for 39% of growth in 2025, and expects candidates in the 2028 campaigns to use AI as a political issue. She adds that many workers lack collective channels to shape workplace automation.
- 40:16Populist alliances can distract from safety
Sun says safety advocates may build bridges with populist groups through issues such as child safety or the environment. But broad backlash can also direct limited political attention toward issues such as data-center water use rather than frontier risks. She sees a possibility for broad public politics and more targeted policy to coexist.
- 44:02Public sees few benefits in AI's promises
Sun says years of warnings from AI companies can make later reassurance look like a reversal, while many people encounter AI as low-quality output, job-application friction or cheating rather than productivity gains. She adds that Silicon Valley's enthusiasm for UBI and leisure does not match many Americans' desire to work. Earlier company messaging, she says, mainly targeted recruits and investors.
- 49:51Trust may require visible economic sharing
Sun says visible medical and scientific gains could improve public views, but health advances alone may not address distrust rooted in inequality. She argues that people need a legible share of the economic upside and says public funding or distributions could help.
- 52:49China's AI adoption reflects pragmatic resignation
Sun describes Chinese attitudes as pragmatic rather than simply optimistic: many people see AI adoption as unavoidable amid government support and a competitive job market. She notes some protests and incremental regulations, including a court ruling that AI replacement would not by itself justify firing a worker. She also says state-owned employers have promised not to lay off workers solely because AI can do their jobs.
- 58:58Journalists should test claims across sources
Sun says some journalists discount AI companies' claims because of skepticism shaped by the crypto era. She recommends checking claims with independent experts rather than assuming that company statements are false, and speaking with stakeholders across industry, academia, policy and politics.
- 1:03:03Policy and philanthropy offer openings
Sun says more politicians and donors are taking AI seriously, creating greater demand for proposals than there are organizations and solutions to fund. She sees opportunities for policy workers who build relationships across groups such as labor and environmental advocates. She also points to billions of dollars that could go toward AI-related issues in the next few years.
Published Jul 21, 2026.
Transcript · 54 min read
80,000 Hours Podcast, hosted by Rob Wiblin and Luisa Rodriguez, with Jasmine Sun.
Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.
Most people in the world do not have the opportunity to like get themselves out of the permanent underclass by getting a job at OpenAI. Sure, you could call it like a normal amount of people like money, but I think the scale of how much talent is flowing into a few specific labs really has to do with the fact that the AI community itself is promoting these widespread beliefs that if you do not have a stake, if you do not have literal equity in frontier AI, you are not going to have economic leverage in the future and you and your kids are going to be Screwed. Today I'm speaking with Jasmine Sun. Jasmine's a writer who's focused on the AI world in Silicon Valley and she lives in San Francisco, spends lots of time with the AI community that's based there and she describes her work as an anthropology of disruption. So basically she's documenting the cultures and the beliefs of the people who are building Frontier AI.
that means basically she's going to all the parties seeking out people from all the different factions in this world interviewing them learning what makes them tick now if that sounds interesting to you jasmine's got a sub stack that i highly recommend checking out and she's also a guest contributor for the atlantic jasmine thank you so much for joining us thanks for having me so you wrote this opinion piece recently for the New York Times, which opened with this really striking observation that most people you know in AI think that the median person is screwed. Now, I'm assuming what you mean by that is sort of on the more moderate end of things, people are anticipating serious short-term disruption, things like job displacement and so on. But for some people, in some cases, people are talking about more extreme things like existential scale threats that affect all of humanity and the idea of a permanent underclass. The people that you're talking to in these circles, you know, they talk about these things, but they don't really have a solution. And yet they're still going ahead and building the technology. Can you help us get into their heads a bit here. So like, do they feel guilty or worried about the costs that they might
“It's a really scary time. I don't think there's going to be a lot of jobs for them left.”
Read the whole transcript
“tons of people who were independent writers or independent policy thinkers and policy advocates decide to leave those roles behind in order to get jobs at AI labs.”
“they were running out of money until Luke Nozek from Founders Fund, simply out of his personal belief that AGI ought to be possible”
Something I was really interested to read on your Substack is how the word Duma has sort of become like the lowest status label that you can wear in Silicon Valley. And that just like, that really surprised me just because, you know, AI company leaders are very much acknowledging the plausibility of doom scenarios. And in fact, that kind of sense of doominess is so pervasive that, you know, people on the outside think it's a form of marketing. They're like, they're not serious. They're just like, it's just hype, you know? And I'm kind of wondering how you think, You know, this idea of doomer as an insult meshes into that picture.
Yeah, in this case, I'm talking a lot more, I think, about classic Silicon Valley and the VC startup corporate ecosystem around tech, which is still the majority of the tech industry. It's somewhat true. I would say it's less true at the AI labs just because there are a lot of people who are, as you mentioned, doomers who are employed at, who are working at Frontier Labs. when you ask like what is silicon valley's political philosophy or what is this what is its ideology in general you can identify a bunch of little tribes like You can identify the effective altruists here and the progress studies people over there and the EACs over here.
But one of the things that a lot of them share is a sort of very firm belief that technological progress is necessarily a good thing. And so I think that when people, when, you know, some of the more accelerationist types have turned Doomer into this slur almost against people who want to slow down or to regulate AI or other technologies, they're sort of presenting a group of people as being anti-progress or as being in opposition to this core belief in silicon valley that technological advancement is the only thing that has ever brought us growth prosperity equality etc and if the and if in all of history in spite of again the industrial revolution like automation like every every wave of technology has brought on its own wave of disruptions um but if one were to believe so firmly in these apocalypse scenarios that you would be willing to slow down the only thing that might again bring us this future utopia that would keep the progress engine going, then you must be this kind of like pessimistic, low agency, like tech skeptical kind of person, I suppose. And so again, I would say that this belief is more of the VC startup crowd. But I think that the idea that like we as humans are, first of all, not powerful enough to be able to control our own technologies. The idea that we
should stop progress just because there might be some marginal side chance of harm. I think people are seeing AI in the context of all the previous technological revolutions and thinking, yeah, these doomers would have still be on the farms being peasants. They would never have allowed the industrial revolution to happen. I think what I want to understand more is what the practical consequences actually are of, you know, having safety concerns, being associated at least in these kind of VC startup-y circles and, you know, which is a like big part of culture in the area, sort of being seen by these people as like kind of embarrassing, call those status. Yeah,
“I don't think that you can do especially credible either journalistic work or policy advocacy work if you are employed by a lab.”
whether they are supported to do their work. Let's move on now to talk about another group of people that you've been observing. So you've spent a bunch of time with, I guess, a group of people that you would describe as AI populists. Can you tell us more about who these people are, what their views and motivations are, and so on. Yeah, I've been tracking sort of the general anti-AI backlash and the political backlash in the United States, and I've been curious about that.
So I made two trips to Washington, D.C. in February and March of this year. And one of my core goals during these trips was to talk to some of these advocates and interest groups who were basically anti-AI advocates in various forms. And I specifically really wanted to talk to folks who are not part of either the industry or the sort of classic AI safety community, but people who are actually coming from other factions and factions within American politics who have only recently begun engaging on AI. And so this includes maybe labor groups who are labor union advocates who are worried about the job stuff.
This includes maybe social conservatives who are very concerned about AI replacing sort of human relationships with AI companions and AI relationships. It might include environmentalists who are worried about data centers' energy use impacts or states' rights advocates who are worried about things like federal preemption. And so one of the big trends that I've noticed in the U.S. over the last few months is that AI is no longer sort of the remit of these few sort of technocratic, very AI-focused policy wonks who are very concerned with the specific characteristics of AI as a technology. And rather you have all these other interest groups that have long histories in Washington lobbying for this and that, who are now realizing, wait a second, AI intersects with my issue, usually in a way that makes us not like AI very much.
And now they're actually banding together and forming these, in some cases, bipartisan or like cross-issue coalitions to support things like whether a data center moratorium or fighting preemption or things like that. And that was just like a really interesting trend to see people who, again, probably two years ago, had no clue what an LLM was, to now be focusing so much of their time and political energy on organizing against AI. And so some people have asked, like, why do I call these folks the AI populace? Like, where does that term come from? And I think it comes from me trying to understand the difference between these political factions that are anti-AI versus, say, the AI safety types of researchers who we talked about earlier. And the main thing that I realized was that of these new AI populists, they are not primarily concerned with the technical characteristics of AI that might make it uniquely risky or uniquely dangerous. Rather, they see AI as an extension of a broader concern that they have that a small number of wealthy and powerful corporate elites are concentrating control in society at the cost of everybody else. And so when the AI populists are trying to do things like impose data center moratoriums or regulate AI, it's often less,
again, about the specific nature of the technology and where it's going, and much more about a broad backlash, a pre-existing populist backlash against billionaires, against tech companies, against corporate concentrations of power that hurt workers and hurt ordinary Americans. Yeah, yeah, yeah. So these people right there, their hatred of AI is like very deeply entrenched and their sort of their distrust of the people who are building it um yeah to the extent where like it doesn't seem to matter to them like how useful chat tpt gets as a tool um you know there's something fundamental about what's going on here that they they feel like like inherently skeptical off um yeah i think that's like interesting interesting.
Because, you know, based on what we've heard so far about the attitudes of people who are building the technologies, I mean, as we've seen, they're quite varied. But ultimately, we've got a group of people who are aware of the risks, aware that the things that they're building could cause a lot of at least short-term disruption, if not worse, longer-term harms. And they're building it anyway. They maybe have a sort of automate or be automated mindset. and some some group of them maybe a small group even has a belief like technology doesn't even need to serve humans um with all of this kind of stuff in mind i guess it's not wholly surprising to me that like some large part of the public feels pretty mist like distrustful um of this group of people um i'm wondering how much sympathy you have for these views overall
“there are no mediating institutions of that form. If you are a white collar worker in most industries, you are not part of any sort of organization”
“people who are now the most activated around the AI backlash are focused on the set of issues that the experts would prefer”
“When you test UBI with the public, it's extremely unpopular because most Americans really want to work.”
Which is why, like, sometimes, like, I'm half joking that, like, you need the big gold Trump check in the mail that says Trump X OpenAI. But I actually think something like that would do quite a lot to persuade people that there was some deal made to share OpenAI wealth or OpenAI equity or OpenAI cash or whatever it is with the public. But, you know, I'm actually like cautiously optimistic about things like, you know, the OpenAI Foundation, if they can be independent from the corporate side of that, the corporate side, and they are able to fund like an incredible amount of public goods, community programs, research, etc. Maybe it'll help. I think they're good people. They're doing their best.
“they are more willing to introduce lots of little pieces of iterative legislation around the potential societal harms of AI.”
because you are someone who works in media and I know that you've observed some effect where in an attempt not to play too much into hype, other media professionals and critics are maybe just not engaging as they should be with the things that advanced AI could do in the future and more speculative things that haven't happened yet.
I'm wondering what your perspective is on how to report about these things without falling into this trap of generating too much hype. Yeah, it's really interesting. I think that journalists are still trying to figure out how to cover AI because there is this competing skepticism of any large institution and particularly one where they have marketing goals to talk about how. powerful and capable their technologies are, while also being serious about potential future possibilities. I mean, one is like, I do think there's a pretty prominent bias I've observed in the mainstream media to avoid giving almost ever taking the AI companies at their word or taking any claim even about the technology itself at their word. I think a lot of this comes from almost PTSD from the crypto era, where a lot of folks made a lot of promises about how crypto was going to change the world and replace the global financial system. And none of this really materialized and there was a lot of scam and fraud. And so journalists felt burned and frustrated by that such that now, even when I'm writing about AI capabilities, I almost always get a question from my editors that says, but isn't it just marketing? Can they really do that? I'm pretty
sure it's just marketing. You should include a caveat about that. And so I understand the sort of default skeptical role that journalists have to play in society, particularly when the entity on the other side is like a really powerful corporation. But, you know, for me, one is like, you should never just talk to the companies. You should always, like, if you're reporting on the company, sure, ask them what they think about AI progress, but make sure that you also spend a lot of time asking independent experts about the same exact questions. And so when I report on the economics of AI, I interview people at the companies. And I also spent a lot of time talking to actual economists with a wide range of views and other policy professionals. And if there's an issue that actually it looks like a lot of these entities agree on, like for example, like I feel like cyber risk and buyer risk are things that you can find a lot of people both inside and outside of the companies to say like, we're all pretty worried about this. And like, this is a real serious thing that might happen. Then it's probably not hype because a bunch of people who don't have financial incentives to say so are saying it too. And so rather than this sort of, you know, very,
I mean, this is all very simplistic, but like rather than this attitude that if the companies say it, it must be wrong. My request is just like, go talk to some independent experts and see if they also think it's wrong. And if they don't like, you know, like maybe, maybe there's something to it. But I don't know. I think I, I think I basically try to spend quite a lot of time trying to talk to every party or every tribe on an issue when possible. So like I try to talk to both Republicans and Democrats. I try to talk to academia as well as people in the industry as well as people in policy. And anytime I reported an issue, I'll try to make sure I'm like hitting every like stakeholder bucket to avoid a sort of tribalism. And also like I even have like a Claude prompt that I'll use sometime where I feed it a draft of something I've written and I say, do you think that every party that every stakeholder group or every party I've represented and quoted would consider this like a fair interpretation, which fair, again, being different than flattering. I think flattering is super different. But I try to basically make sure that I'm having conversations with and attempting to see my story from every possible side, rather
than just neglecting entirely some of a group of people. Like, again, there are journalists who will not talk to people at a company. There are others who will not talk to some AI skeptic. So, yeah, through this conversation and from reading your sub stack, it does feel like we kind of have unearthed a lot of uncomfortable truths about the AI world. So, yeah, are there any reasons to be hopeful that you want to highlight? I actually think that it's a really great time to be working in and around AI, even and maybe especially if you are concerned with safety, concerned with societal impacts, concerned with some of these broad public issues.
And that's partly because as I've started to engage a little bit more with the policy and the political conversation, it's clear to me that the Overton window in one policy and two actually philanthropy both seem to be expanding extremely quickly. Like literally between my trip to D.C. in early February and late March, I noticed in a month and a half how some of the same people who are saying like. Yeah, I don't think policymakers even, you know, believe that these things are more than stochastic parrots. We're starting to go, oh, it looks like a lot of people in my constituencies in my voter base are really worried about AI. Guess I got to start taking this seriously.
I think that Mythos was a big update. I think that Cloud Code was a big update and Cloud Cowork. I think that for people, for a lot of these more legacy institutions in the policy world or in the philanthropic world or in civil society who have spent kind of years shutting their eyes to the possibility of advanced AI progress, that is starting to fall away. People really are starting to take AI seriously. And what that means is we're actually in this kind of funny scenario where there are a lot more politicians looking for ideas of what to do about AI than we actually have compelling ideas and solutions.
So I think for anyone who wants to work, for example, in AI policy, who is willing to actually branch out and like, say, build relationships with labor groups or like environmentalists or whether it's on the right or the left or whoever, and spend some of the time to get some of these people who are brand new to AI, but who actually really want to do something on it because they believe it's important and they believe it could be politically helpful to actually get some like good, serious ideas in their hands. I just like the number of times that I've had conversations with congressional staffers, very influential people in Congress who are saying like, yeah, like my representative really wants to do something on this.
They're just still in the process of learning what to do. And so I think the potential for impact in policy is really high. And then the second one I mentioned was philanthropy, of course, which I think a lot of folks are aware of. There's tons of money, both individual donations from people who are about to get really wealthy off these IPOs, there's things like the OpenAI Foundation, but also the traditional philanthropic actors, whether Gates or Rockefeller or whatever, all of them are starting to build out their own AI plans. And so there are, you know, billions of dollars in the next couple years that could go towards tackling AI-related issues.
And once again, I think that there is more desire to spend the money than there actually are organizations and solutions to fund. So I think there's a ton of opportunity if you're a young person looking to make your career right now to be working on AI issues. Yeah, awesome. Thank you so much, Jasmine. I think that's all we've got time for, but you've been a pleasure to have on the show. Thank you for coming. Thanks so much for having me. This was fun.
