As it faces a growing number of lawsuits alleging it helps facilitate child sexual exploitation, online gaming platform Roblox has unveiled a new age verification system. That system, however, could open it up to a different sort of criticism.
The popular app, which has roughly 151 million users, announced last week that it plans to require a facial age check for all users who utilize the Roblox chat system. User verification can be accomplished by either submitting a government ID or by submitting a selfie, which AI will examine to estimate the age of the user.
The verification will begin rolling out in early December in select markets (which do not include the U.S.) and expand globally in January 2026.
“This initiative is designed to provide even more age-appropriate experiences for all users, which we believe will improve interactions for users of all ages on Roblox,” Roblox Chief Safety Officer Matt Kaufman said in a statement. “Enforcing age checks allows us to implement age-based chat, which helps users better understand who theyre communicating with and limits chat between minors and adults.”
Roblox is facing at least 35 lawsuits that allege users met and abused children on the platform. (More than one-third of the platform’s users are under the age of 13.) Attorneys general in Kentucky and Louisiana filed separate lawsuits accusing the company of harming children earlier this year. And a California judge, earlier this month, denied Roblox’s attempt to force one father’s dispute into a private resolution.
Roblox already has parental controls and blocks photo sharing and the exchange of personal information. It also uses a mix of human and AI to moderate text and voice interactions.
Under the new system, though, users who verify their age will only be allowed to chat with others in a similar age range (unless they are classified a “Trusted Connection” with people they know). Those age groups will be broken into six categories: Under 9, 9 to 12, 13 to 15, 16 to 17, 18 to 20, or over 21. (Chat will not be offered to users under 9 years old, unless a parent provides consent after an age check.)
Because families have kids of all ages, Roblox says it will soon roll out solutions for direct chat between parents and children younger than 13 or between siblings in different age groups.
Submitting age verification is still optional, but will be required for any user who wishes to utilize the system’s chat feature, which is a popular component with users.
Roblox says submitted selfies will be completed through the app using a smartphone’s camera. It also tried to get ahead of possible security concerns, saying “images and video for age checks completed through Facial Age Estimation are processed by our vendor, Persona, and deleted immediately after processing.”
Still, some parents could be wary of letting their young children submit photos to the company, given the number of lawsuits and the polarizing nature of facial recognition.
In 2021, Facebook abandoned its facial recognition program, which suggested name tags for people in pictures, following privacy watchdog warnings and European Union regulators cracking down on the practice. (The company brought back facial recognition tools last year to assist with reclaiming compromised accounts.)
Even Senate Republicans have expressed wariness over facial recognition software, proposing a limit on that technology in U.S. airports (though the bill has not found momentum so far). Folks dont want a national surveillance state, but thats exactly what the TSAs unchecked expansion of facial recognition technology is leading us to,” said Oregons Democratic Senator Jeff Merkley, a cosponsor of the bill, in May.
Roblox says its age checks won’t stop with the current program. Early next year it will require age checks to access social media links on user profiles, communities, and experience details pages.
In late October, Tucker Carlson invited Nick Fuentes, a 27-year-old white-nationalist streamer, onto his popular podcast and Youtube show for a friendly interview. Fuentes has amassed a loyal following with hundreds of thousands of viewers who tune into the racist, misogynist, and antisemitic sentiments he voices in lucid monologues on his nightly show, America First. A talented broadcaster with a biting sense of humor and a combative persona, hes tailor-made for the no-holds-barred environment of big-tech platformsso long as he manages to stay on them. In 2021, he was booted from essentially every tech platform for hate speech, forcing him to start his own streaming service to host his show.Where did Fuentes come from? Why are old-guard conservative institutions and media stalwarts alike catering to himor even cowering before him?The answer lies in how Fuentes has mastered the right-wing online swamps of the Trump era, and the increasingly porous boundaries between the extremely online right and the Republican establishment, explains Ben Lorber, an analyst at Political Research Associates, a group that monitors and studies the far right. You cant tell the story of Fuentess rise without telling the story of alternative tech platforms and transformations of large tech platforms, Lorber says.As the Fuentes interview rippled across social media, conservative sites and prominent figures on the right including Senator Ted Cruz and Jewish commentator Ben Shapiro, asked: What, exactly, had Carlson been thinking by platforming a figure like Fuentes? Three days after the Carlson appearance, Kevin Roberts, the president of the Heritage Foundation, the storied conservative think tank that produced the Project 2025 roadmap for the Trump administration, weighed in. I disagree with, and even abhor, things Nick Fuentes says. But cancelling him is not the answer, either, Roberts said in a video on X, in which he also defended the right of conservatives to criticize Israel as well as Carlsons decision to host Fuentes. Carlsons critics, Roberts added, were globalists and part of a venomous coalition, language that many decried as trafficking in antisemitic tropes.
Within the halls of Heritage, Robertss video provoked an insurrection, forcing him to issue a lengthy apology condemning Fuentes. In a speech, Roberts explained that hed wanted only to reach the disaffected young men that comprise Fuentess audience, many of whom identify as Groypers.But the damage has been done. Heritage staff lambasted him at a town hall-style discussion. Numerous employees and a member of the board of trustees have resigned. The cochairs of their antisemitism task force, the creator of Project Esther, a campaign targeting pro-Palestine protestors, also announced they would be severing ties with Heritage. Last Thursday, Democratic Senate Minority leader Chuck Schumer announced he would introduce a resolution condemning Fuentes, and he called on his Republican colleagues to join him.
They have to engage
Once, figures like Fuentes were relegated to the far-right fringes of the internet. Cassie Miller, an analyst with the Southern Poverty Law Center, explains that an older generation of conservative activists learned to speak in dog whistles to code racist appeals to voters. This model was pioneered by people like Lee Atwater, an advisor to Ronald Reagan and George H.W Bush, whose southern strategy infamously deployed euphemisms like states rights in place of explicit appeals to racism.
But acolytes of Fuentes grew up in an entirely different media and technology environment, one where the far right saw the rise of Donald Trump and his MAGA movement as a vehicle to seed their ideas into mainstream politics. There are a lot of younger people, even within the institutionalized right, who are far more comfortable with the kind of overtly racist, transgressive language of someone like Fuentes, Miller says.
Fuentes has built his profile through a command of the incentive structures of large tech platforms. He forces people to contend with his views and feel like they have to respond to him. They have to engage in some sort of discourse with him, and it ends up platforming him and legitimizing what hes saying, says Miller. Thats what he did here with Tucker Carlson.
Short-form video has also proven to be a powerful weapon for Fuentes. His followers take bite-sized clips from his broadcasts and pump them out on X and other platforms. You might not have context when you come into contact with it, and you might think that, well, he has some legitimate points, Miller adds.
Theres also Fuentess ugly blend of fair critiques of Israels wanton slaughter of Palestinians with outright antisemitism, a rhetorical strategy since adopted by figures like Candace Owens and Carlson. Carlson, Owens, and Fuentes, and others are all competing for the same kind of market on the anti-Zionist right, Lorber says. Theyve identified that almost as a growth market.
Staying power
Fuentess proficiency across online platforms, and the way those platforms have changed in recent years, have allowed him to stage his comeback.
After Elon Musk purchased Twitter and renamed it X, he reinstated Fuentess account, where he now has over 1 million followers. His show went on to find a home on Rumblea conservative competitor to Youtube with financial backing from Silicon Valley billionaire and Republican donor Peter Thiel, among otherswhere it is broadcast to thousands nightly.
All this has coincided with the slow death of once good faith efforts at hate-speech moderation by large tech platforms, Miller says. A lot of his career, hes been pushed to the margins of online spaces. But what weve seen is that hes had really incredible staying power, she adds.
That staying power in the online world may have already spilled over into the real world. Fuentes and others on the far-right like the pseudonymous author Bronze Age Pervert have advised their followers to hide their power level and infiltrate so-called normie conservative institutions.
Recently, right-wing writer Rod Dreher wrote of the remarkable prevalence of Groypers among the Republican partys professional ranks in Washington, including, he alleged, in the Trump administration. Reports from Politico have revealed text threads of young Republicans and one Trump appointee sympathizing with Nazism, showing the embrace of Groyper-like ideology.
But trying to pinpoint the exact percentage of closeted Groypers might be missing the point. Theres very little difference between whether someone is a dedicated Groyper, or whether they just agree with Fuentess politics independently of being one of his followers, Lorber says. It might be better, Lorber says, to think of Fuentes as a stand in for a worldview and a brand of politicslike an ambassador of the Gen Z radical right.
On the rise
There is no reason to think that the recent controversy will slow Fuentess ascendancy within the GOP. Trump has long since made common cause with the extreme right. Trump infamously claimed there were very fine people, on both sides of the 2017 United the Right rally in Charlottesville, where men marched with tiki torches chanting Jews will not replace us. (An 18-year-old Fuentes was in attendance). In 2022, Fuentes himself attended a dinner at Mar-a-Lago with Trump and the artist formerly known as Kanye West.
Examples, in other words, are not hard to find. Great Replacement ideology is now mainstream. Christian Nationalism is now mainstream, and antisemitism is rapidly becoming mainstream too, Lorber says. So for people like Nick Fuentes, the movement has caught up with him.
As for Heritage, the fine print of Project 2025 reveals an extremist vision in its own right, one that seeks to transform the country into a Christian Nationalist autocracy. A softening stance towards Fuentes, in other words, doesnt seem so odd. Drawing the line at outright Nazism is certainly preferable to welcoming it. But the time for condemnation may be long since past.
Fuentes, meanwhile, will keep posting and streaming, and likely continuing to bend the party to his will in the process. He has a really clear understanding of the way the media environment works, Miller says. For Fuentes, its a huge victory just to have people say his name.
Theres a scene in Office Space where Peter sits across from two consultants during a company downsizing. They ask him, What would you say you do here? He hesitates, smirks, and admits he only works about 15 minutes a week. The rest of the time, hes pretending. It was comedy in 1999. Its confession now.
That question has come back to us.
For years, we filled our calendars, stayed visible, and kept the machine moving. Our worth was measured in hours, output, and presence. It had to be. Humans were the system, and the system required us to keep it running. We didnt question it because that was how things got done.
AI has changed that.
It can now do many of the things we once did to keep things moving: the summaries, the reports, the follow-ups, the updates, the spreadsheets. It can organize, calculate, write, and execute at a pace we cant match.
That realization feels strange at first, but its also freeing.
Now we get to hand that part over. We can give the robotic work to the robots and return to the human work. The work of thinking, deciding, designing, and connecting.
So what does that look like?
For one, it means our conversations are changing. When the noise quiets, the meetings sound different. Theres more space to ask better questions. We can finally talk about what matters: What is the business really trying to accomplish? Whats next? What do we need to build the product, craft the strategy, organize the team, and align around purpose?
Its fantastic, really.
Because when people stop being buried in repetitive work, they start showing up differently. They bring curiosity. They tell the truth. They collaborate in new ways. Im hearing it everywherein companies that are deep into their AI transformation and in those that are just starting. The tone is changing. The conversations are more human.
Were still in the waiting room of this transition. Some are pacing the floor, some are seated patiently, some are already being called in. Wherever a company sits on that curve, the shift has begun.
Deloittes 2024 Global Human Capital Trends report describes this moment as a readiness gap. Most leaders recognize that AI and technology will transform their organizations in the coming years, yet few say they feel prepared to lead their people through that change. The tools are ready. The humans are still catching up.
For leaders, this is the moment to adjust the focus. The work still needs watching, but the focus of that attention is different. Its no longer about overseeing tasks; Its about overseeing direction. How we design. How we execute. How we build and with whom. Leadership now is about being intentional and accountable for how work is created, not just how it is completed.
Many leaders are rebuilding, or at least redesigning, how they lead. The language is changing. The tone is shifting. Its not a different language, but it has a new accent. And those who thrive in this era will be the ones who can translate it.
Theyll know how to take complexity and turn it into clarity. Theyll bring forward a sharper vision, a stronger purpose, and a deeper ability to communicate the why. Theyll be what I call full-stack leaders: people who can support the front, the back, and the middle layer. They understand product, people, and process, and they move fluidly across them all.
AI has taken the repetitive pieces off our plates and has given us back the chance to think, create, and build with intention. It gives us room to lead.
When an X user recently pointed out the eye-popping increase in billionaires wealth since 2015, entrepreneur Mark Cuban, a billionaire himself, responded with his opinion on why, but he urged followers to consider a different question:
Why are we not giving incentives to companies to require them to give shares in their companies to all employees, at the same percentage of cash earnings as the CEO? Cuban said.
It is the right question to be asking. Because while the debate over wealth inequality continues, the solution has been hiding in plain sight for decades.
The top 10% of U.S. households now control 67% of all wealth, while the bottom half holds just 2.5%. The typical American worker approaches retirement with about $4,000 in savings, which is less than the cost of one month in an assisted living facility. That imbalance is not sustainable, economically or socially.
The fix does not require new legislation or another corporate responsibility pledge. It lies in a proven model that has been quietly transforming companies and communities for 50 years: employee ownership.
From Silicon Valley to Main Street
Silicon Valley figured this out long ago. Equity compensation has been the foundation of the tech sectors innovation economy since the 1970s. Stock options allowed startups to attract world-class talent without paying top-tier salaries, align employee incentives with company performance, and build wealth for workers who might otherwise never own an asset.
Yet outside of tech, broad-based ownership remains rare. Fewer than 7,000 U.S. companiesmostly in traditional sectors like manufacturing, construction, and distributionoperate under an employee stock ownership plan (ESOP). The results, however, mirror the Valleys success.
Employee-owned firms grow more than 2% faster per year than their peers and are half as likely to go bankrupt. During the 2008 financial crisis, they laid off workers at only one-third the rate of conventional firms. For employees, the impact is just as powerful. ESOP participants hold 92% higher median household wealth, twice the retirement savings, and 33% higher median income than comparable workers.
This is not philanthropy. It is a durable, market-tested strategy that drives growth, resilience, and equity at the same time.
The Timing Could Not Be Better
Today, several powerful trends make this the perfect moment to bring ownership to scale.
A massive generational handoff is underway. Ten thousand baby boomers retire each day, many of them owners of successful small and midsize businesses with no succession plan. Transferring ownership to employees keeps those businesses rooted in their communities, preserves good jobs, and rewards founders with fair market value.
The retirement crisis demands new solutions. With average savings at historic lows, workers need wealth-building tools that go beyond 401(k) plans. Ownership creates an asset base that compounds over time, restoring what traditional pensions once offered.
Labor shortages are reshaping industries. As skilled workers grow scarce, companies that offer ownership will win the competition for talent, not only by paying well but by giving people a reason to stay.
Economic volatility favors resilience. Employee-owned companies outperform during downturns because people at every level have a stake in the outcome. Ownership builds both financial and cultural strength.
Beyond Good Intentions
America has no shortage of programs designed to help workers. What it lacks is awareness and adoption of the ownership mechanisms that allow employees to share in the value they create. As long as labor and ownership remain separated, inequality will continue to deepen.
When employees have an equity stake, their focus shifts from completing tasks to building lasting value. They think like owners because they are owners, and that mindset fuels innovation, strengthens loyalty, and creates a powerful cycle of trust and accountability.
The impact case is clear, and the business case is even stronger. Broad-based ownership builds companies that last. It keeps wealth circulating within communities instead of extracting it, and it turns employees into long-term investors in the enterprise they help build.
The Moment to Act
We are standing on the edge of a once-in-a-generation opportunity to reimagine capitalism for shared prosperity. Employee ownership will not fix every inequity in our economy, but it addresses one of the most fundamental: who benefits from the value a company creates.
Cubans challenge should not disappear into the social media ether. It should become a call to action for policymakers, investors, and business leaders to make employee ownership the standard, not the exception.
America does not need another wealth redistribution debate. It needs a wealth participation strategy.
Employee ownership represents capitalism at its best: fair, inclusive, and fiercely competitive. It aligns profit with purpose and ensures that the people who build our companies share in their success. If we scale it now, we can turn todays inequality into tomorrows shared prosperity.
You’ve heard the gospel: AI is going to change everything. Good, great, grand.
But when youre staring down a deadline and 80 unread emails, you don’t need philosophy, you need a cheat sheet.
The fastest way to master AI isn’t by watching lectures, it’s by finding a way to replace an hour of your grind with a 10-second prompt. Here are five specific, repeatable ways to automate your most time-consuming professional tasks.
Grab your chatbot of choice (Gemini, ChatGPT, Claude, Copilotwhatever floats your boat) and let’s get to work.
Writing
Staring at a blank page. Tedious, formulaic first drafts. Enough.
You are a professional. You shouldn’t be spending an hour drafting a boilerplate email to a client or writing the first three paragraphs of a report. Thats grunt work.
Instead, master constraint-based prompting. This is where you tell the AI exactly what to write and how to write it, forcing it to follow your specific, professional rules.
Heres a prompt example:
“You are a [job title]. Draft a [document type (memo, email, etc.)] to [target audience]. The tone must be [tone]. The three key takeaways are [list three specific bullet points]. The final memo should be around [length in words] and include a subject line.
Post-meeting action items
Sifting through long transcripts and meeting notes for action items?
You’re doing it wrong. Let the AI do the heavy lifting of synthesis.
Its time to leverage deliverable-based prompting. Instead of asking for a summary, ask the AI to produce specific, structured outputs from a large body of text, such as a meeting transcript or a dense PDF.
For example:
“Analyze the following [meeting transcript/document]. Do not summarize the entire text. Instead, produce three distinct outputs: 1) A table listing all action items, the person responsible, and the deadline mentioned. 2) A list of three open questions that were not resolved. 3) A short, two-sentence email subject line for the follow-up.”
In less than a minute, you can transform raw data into a clean, actionable task list.
Research
To turn generative AI into a true, trusted research assistant that can search and cross-reference information scattered across multiple work files requires using tools that let you upload your own content, such as Googles NotebookLM or similar features in other platforms.
This is called contextual grounding, and it involves uploading a handful of annual reports, project documents, or extensive research files. Check with your organization first to see if there are any rules against this.
Heres a prompt you can use:
“Based only on the uploaded documents, what is the biggest discrepancy between the Q4 2024 revenue projection [from Document A] and the actual Q1 2025 marketing spend [from Document C]? Explain the gap in three bullet points, referencing the specific document where the information was found.”
This lets you stop relying on the AIs general knowledge and start using it as a hyperefficient analyst for your own private data, generating insights that would take hours to gin up on your own.
Brainstorming
Thanks to AI, hitting a creative wall or falling victim to groupthink during brainstorming is nothing like it used to be.
While your brain thinks linearly, AI can think exponentiallybut you have to force it to show its work.
Employ critical reasoning prompting, also called “chain-of-thought.” This forces the AI to debate, critique, and explore alternatives before settling on an answer.
A sample prompt formula:
“I have an idea for a new product feature: [describe the feature]. Before you propose a name for it, I need you to first: 1) Act as a skeptical customer and list three reasons why this feature is useless. 2) Act as a competitor and list three ways they could easily copy and neutralize the feature. 3) Only after those two steps, propose three distinct, benefit-driven names for the feature.”
This forces the AI to act as a constructive adversary, getting you to a better, more robust idea much faster.
The low point in Palantirs very first quest for investors came during a pitch meeting in 2004 that CEO Alex Karp and some colleagues had with Sequoia Capital, which was arguably the most influential Silicon Valley VC firm. Sequoia had been an early investor in PayPal; its best-known partner, Michael Moritz, sat on the companys board and was close to PayPal founder Peter Thiel, who had recently launched Palantir. But Sequoia proved no more receptive to Palantir than any of the other VCs that Karp and his team visited; according to Karp, Moritz spent most of the meeting absentmindedly doodling in his notepad.
Karp didnt say anything at the time, but later wished that he had. I should have told him to go fuck himself, he says, referring to Moritz. But it wasnt just Moritz who provoked Karps ire: the VC communitys lack of enthusiasm for Palantir made Karp contemptuous of professional investors in general. It became a grudge that he nurtured for years after.
[Image: Avid Reader Press]
From The Philosopher in the Valley: Alex Karp, Palantir, and the Rise of the Surveillance State by Michael Steinberger. Copyright 2025. Reprinted by permission of Avid Reader Press, an Imprint of Simon & Schuster Inc.
But the meetings on Sand Hill Road werent entirely fruitless. After listening to Karps pitch and politely declining to put any money into Palantir, a partner with one venture capital firm had a suggestion: if Palantir was really intent on working with the government, it could reach out to In-Q-Tel, the CIAs venture capital arm. In-Q-Tel had been started a few years earlier, in 1999 (the name was a playful reference to Q, the technology guru in James Bond films). CIA Director George Tenet believed that establishing a quasi-public venture capital fund through which the agency could incubate start-ups would help ensure that the U.S. intelligence community retained a technological edge.
The CIA had been created in 1947 for the purpose of preventing another Pearl Harbor, and a half century on, its primary mission was still to prevent attacks on American soil. Two years after In-Q-Tel was founded, the country experienced another Pearl Harbor, the 9 11 terrorist attacks, a humiliating intelligence failure for the CIA and Tenet. At the time, In-Q-Tel was working out of a Virginia office complex known, ironically, as the Rosslyn Twin Towers, and from the twenty-ninth-floor office, employees had an unobstructed view of the burning Pentagon.
In-Q-Tels CEO was Gilman Louie, who had worked as a video game designer before being recruited by Tenet (Louie specialized in flight simulators; his were so realistic that they were used to help train Air National Guard pilots). Ordinarily, Louie did not take part in pitch meetings; he let his deputies do the initial screening. But because Thiel was involved, he made an exception for Palantir and sat in on its first meeting with In-Q-Tel.
What Karp and the other Palantirians didnt know when they visited In-Q-Tel was that the CIA was in the market for new data analytics technology. At the time, the agency was mainly using a program called Analysts Notebook, which was manufactured by i2, a British company. According to Louie, Analysts Notebook had a good interface but had certain deficiencies when it came to data processing that limited its utility.
We didnt think their architecture would allow us to build next-generation capabilities, Louie says.
Louie found Karps pitch impressive. Alex presented well, he recalls. He was very articulate and very passionate. As the conversation went on, Karp and his colleagues talked about IGOR, PayPals pioneering fraud-detection system, and how it had basically saved PayPals business, and it became apparent to Louie that they might just have the technical aptitude to deliver what he was looking for.
But he told them that the interface was vitalthe software would need to organize and present information in a way that made sense for the analysts using it, and he described some of the features they would expect. Louie says that as soon as he brought this up, the Palantir crew got out of sales mode and immediately switched into engineering solving mode and began brainstorming in front of the In-Q-Tel team.
That was what I wanted to see, says Louie.
He sent them away with a homework assignment: he asked them to design an interface that could possibly appeal to intelligence analysts. On returning to Palo Alto, Stephen Cohen, one of Palantirs co-founders, then 22 years old, and an ex-PayPal engineer named Nathan Gettings sequestered themselves in a room and built a demo that included the elements that Louie had highlighted.
A few weeks later, the Palantirians returned to In-Q-Tel to show Louie and his colleagues what they had come up with. Louie was impressed by its intuitive logic and elegance. If Palantir doesnt work, you guys have a bright future designing video games, he joked.
In-Q-Tel ended up investing $1.25 million in exchange for equity; with that vote of confidence, Thiel put up another $2.84 million. (In-Q-Tel did not get a board seat in return for its investment; even after Palantir began attracting significant outside money, the company never gave up a board seat, which was unusual, and to its great advantage.)
Karp says the most beneficial aspect of In-Q-Tels investment was not the money but the access that it gave Palantir to the CIA analysts who were its intended customers. Louie believed that the only way to determine whether Palantir could really help the CIA was to embed Palantir engineers in the agency; to build software that was actually useful, the Palantirians needed to see for themselves how the analysts operated. A machine is not going to understand your workflows, Louie says. Thats a human function, not a machine function.
The other reason for embedding the engineers was that it would expedite the process of figuring out whether Palantir could, in fact, be helpful. If the CIA analysts didnt think Palantir was capable of giving them what they needed, they were going to quickly let their superiors know. We were at war, says Louie, and people did not have time to waste.
Louie had the Palantir team assigned to the CIAs terrorism finance desk. There they would be exposed to large data sets, and also to data collected by financial institutions as well as the CIA. This would be a good test of whether Karp and his colleagues could deliver: tracking the flow of money was going to be critical to disrupting future terrorist plots, and it was exactly the kind of task that the software would have to perfrm in order to be of use to the intelligence community.
But Louie also had another motive: although Karp and Thiel were focused on working with the government, Louie thought that Palantirs technology, if it proved viable, could have applications outside the realm of national security, and if the company hoped to attract future investors, it would ultimately need to develop a strong commercial business.
Stephen Cohen and engineer Aki Jain worked directly with the CIA analysts. Both had to obtain security clearance, and over time, numerous other Palantirians would do the same. Some, however, refusedthey worried about Big Brother, or they didnt want the FBI combing through their financial records, or they enjoyed smoking pot and didnt want to give it up. Karp was one of the refuseniks, as was Joshua Goldenberg, the head of design. Goldenberg says there were times when engineers working on classified projects needed his help. But because they couldnt share certain information with him, they would resort to hypotheticals.
As Goldenberg recalls, Someone might say, Imagine theres a jewel thief and hes stolen a diamond, and hes now in a city and we have people following himwhat would that look like? What tools would you need to be able to do that?
Starting in 2005, Cohen and Jain traveled on a biweekly basis from Palo Alto to the CIAs headquarters in Langley, Virginia. In all, they made the trip roughly two hundred times. They became so familiar at the CIA that analysts there nicknamed Cohen Two Weeks. The Palantir duo would bring with them the latest version of the software, the analysts would test it out and offer feedback, and Cohen and Jain would return to California, where they and the rest of the team would address whatever problems had been identified and make other tweaks. In working side by side with the analysts, Cohen and Jain were pioneering a role that would become one of Palantirs signatures.
It turned out that dispatching software engineers to job sites was a shrewd strategyit was a way of discovering what clients really needed in the way of technological help, of developing new features that could possibly be of use to other customers, and of building relationships that might lead to additional business within an organization. The forward-deployed engineers, as they came to be called, proved to be almost as essential to Palantirs eventual success as the software itself. But it was that original deployment to the CIA, and the iterative process that it spawned, that enabled Palantir to successfully build Gotham, its first software platform.
Ari Gesher, an engineer who was hired in 2005, says that from a technology standpoint, Palantir was pursuing a very ambitious goal. Some software companies specialized in front-end productsthe stuff you see on your screen. Others focused on the back-end, the processing functions. Palantir, says Gesher, understood that you needed to do deep investments in both to generate outcomes for users.
According to Gesher, Palantir also stood apart in that it aimed to be both a product company as well as a service company. Most software makers were one or the other: they either custom-built software, or they sold off-the-shelf products that could not be tailored to the specific needs of a client. Palantir was building an off-the-shelf product that could also be customized.
Despite his lack of technical trainingor, perhaps, because of itKarp had also come up with a novel idea for addressing worries about civil liberties: he asked the engineers to build privacy controls into the software. Gotham was ultimately equipped with two guardrailsusers were able to access only information that they were authorized to view, and the platform generated an audit trail that indicated if someone tried to obtain material off-limits to them. Karp liked to call it a Hegelian remedy to the challenge of balancing public safety and civil liberties, a synthesis of seemingly unreconcilable objectives. As he told Charlie Rose during an interview in 2009, It is the ultimate Silicon Valley solution: you remove the contradiction, and we all march forward.
In the end, it took Palantir around three years, lots of setbacks, and a couple of near-death experiences to develop a marketable software platform that met these parameters.
There were moments where we were like, Is this ever going to see the light of day? Gesher says. The work was arduous, and there were times when the money ran short. A few key people grew frustrated and talked of quitting.
Palantir also struggled to win converts at the CIA. Even though In-Q-Tel was backing Palantir, analysts were not obliged to switch to the companys software, and some who tried it were underwhelmed.
But in what would become another pattern in Palantirs rise, one analyst was not just won over by the technology; she turned into a kind of in-house evangelist on Palantirs behalf. Sarah Adams discovered Palantir not at Langley, but rather on a visit to Silicon Valley in late 2006. Adams worked on counterterrorism, as well, but in a different section. She joined a group of CIA analysts at a conference in the Bay Area devoted to emerging technologies. Palantir was one of the vendors, and Stephen Cohen demoed its software. Adams was intrigued by what she saw, exchanged contact information with Cohen, and upon returning to Langley asked her boss if her unit could do a pilot program with Palantir. He signed off on it, and a few months later, Adams and her colleagues were using Palantirs software.
Adams says that the first thing that jumped out at her was the speed with which Palantir churned data. We were a fast-moving shop; we were kind of the point of the spear, and we needed faster analytics, she says.
According to Adams, Palantirs software also had a smartness that Analysts Notebook lacked. It wasnt just better at unearthing connections; even its basic search function was superior. Often, names would be misspelled in reports, or phone numbers would be written in different formats (dashes between numbers, no dashes between numbers). If Adams typed in David Petraeus, Palantirs search engine would bring up all the available references to him, including ones where his name had been incorrectly spelled. This ensured that she wasnt deprived of possibly important information simply because another analyst or a source in the field didnt know that it was Petraeus.
Beyond that, Palantirs software just seemed to reflect an understanding of how Adams and other analysts did their jobsthe kind of questions they were seeking to answer, and how they wanted the answers presented. She says that Palantir made my job a thousand times easier. It made a huge difference.
Her advocacy was instrumental in Palantir securing a contract with the CIA. Similar stories would play out in later deploymentsone employee would end up championing Palantir, and that persons proselytizing would eventually lead to a deal.
But the CIA was the breakthrough: it was proof that Palantir had developed software that really worked, and also the realization of the ambition that had brought the company into being. Palantir had been founded by Peter Thiel for the purpose of assisting the U.S. government in the war on terrorism, and now the CIA had formally enlisted its help in that battle.
Palantirs foray into domestic law enforcement was an extension of its counterterrorism work. In 2007, the New York City Police Departments intelligence unit began a pilot program using Palantirs software. Before 9/11, the intelligence division had primarily focused on crie syndicates and narcotics. But its mandate changed after the terrorist attacks. The city tapped David Cohen, a CIA veteran who had served as the agencys deputy director of operations, to run the unit, and with the citys blessing, he turned it into a full-fledged intelligence service employing some one thousand officers and analysts. Several dozen members of the team were posted overseas, in cities including Tel Aviv, Amman, Abu Dhabi, Singapore, London, and Paris.
The rationale for the N.Y.P.D.s transformation after September 11th had two distinct facets, The New Yorkers William Finnegan wrote in 2005. On the one hand, expanding its mission to include terrorism prevention made obvious sense. On the other, there was a strong feeling that federal agencies had let down New York City, and that the city should no longer count on the Feds for its protection. Finnegan noted that the NYPD was encroaching on areas normally reserved for the FBI and the CIA but that the federal agencies had silently acknowledged New Yorks right to take extraordinary defensive measures.
Cohen became familiar with Palantir while he was still with the CIA, and he decided that the companys software could be of help to the intelligence unit. In what was becoming a familiar refrain, there was internal resistance. For the average cops, it was just too complicated, says Brian Schimpf, one of the first forward-deployed engineers assigned to the NYPD.
Theyd be like, I just need to look up license plates, bro; I dont need to be doing these crazy analytical processes. IBMs technology was the de facto incumbent at the NYPD, which also made it hard to convert people.
Another stumbling block was price: Palantir was expensive, and while the NYPD had an ample budget, not everyone thought it was worth the investment. But the software caught on with some analysts, and over time, what began as a counter terrorism deployment moved into other areas, such as gang violence.
This mission creep was something that privacy advocates and civil libertarians anticipated. Their foremost worry, in the aftermath of 9/11, was that innocent people would be ensnared as the government turned to mass surveillance to prevent future attacks, and the NSA scandal proved that these concerns were warranted.
But another fear was that tools and tactics used to prosecute the war on terrorism would eventually be turned on Americans themselves. The increased militarization of police departments showed that defending the homeland had indeed morphed into something more than just an effort to thwart jihadis. Likewise, police departments also began to use advanced surveillance technology.
Andrew Guthrie Ferguson, a professor of law at George Washington University who has written extensively about policing and technology, says that capabilities that had been developed to meet the terrorism threat were now being redirected on the domestic population.
Palantir was part of this trend. In addition to its work with the NYPD, it provided its software to the Cook County Sheriffs Office (a relationship that was part of a broader engagement with the city and that would dissolve in controversy). However, it attracted much of its police business in its own backyard, California. The Long Beach and Burbank Police Departments used Palantir, as did sheriff departments in Los Angeles and Sacramento counties. The companys technology was also used by several Fusion Centers in Californiathese were regional intelligence bureaus established after 9/11 to foster closer collaboration between federal agencies and state and local law enforcement. The focus was on countering terrorism and other criminal activities.
But Palantirs most extensive and longest-lasting law enforcement contract was with the Los Angeles Police Department. It was a relationship that began in 2009. The LAPD was looking for software that could improve situational awareness for officers in the fieldthat could allow them to quickly access information about, say, a suspect or about previous criminal activity on a particular street. Palantirs technology soon became a general investigative tool for the LAPD.
The department also started using Palantir for a crime-prevention initiative called LASER. The goal was to identify hot spotsstreets and neighborhoods that experienced a lot of gun violence and other crimes. The police would then put more patrols in those places. As part of the stepped-up policing, officers would submit information about people they had stopped in high-crime districts to a Chronic Offenders Bulletin, which flagged individuals whom the LAPD thought were likely to be repeat offenders.
This was predictive policing, a controversial practice in which quantitative analysis is used to pinpoint areas prone to crime and individuals who are likely to commit or fall victim to crimes. To critics, predictive policing is something straight out of the Tom Cruise thriller Minority Report, in which psychics identify murderers before they kill, but even more insidious. They believe that data-driven policing reinforces biases that have long plagued Americas criminal justice system and inevitably leads to racial profiling.
Karp was unmoved by that argument. In his judgment, crime was crime, and if it could be prevented or reduced through the use of data, that was a net plus for society. Blacks and Latinos, no less than whites, wanted to live in safe communities. And for Karp, the same logic that guided Palantirs counterterrorism work applied to its efforts in law enforcementpeople needed to feel safe in their homes and on their streets, and if they didnt, they would embrace hard-line politicians who would have no qualms about trampling on civil liberties to give the public the security it demanded. Palantirs software, at least as Karp saw it, was a mechanism for delivering that security without sacrificing privacy and other personal freedoms.
However, community activists in Los Angeles took a different view of Palantir and the kind of police work that the company was enabling. An organization called the Stop LAPD Spying Coalition organized protests and also published studies highlighting what it claimed was algorithmic-driven harassment of predominantly black and Latino neighborhoods and of people of color. LASER, it said, amounted to a racist feedback loop. In the face of criticism, the LAPD grew increasingly sensitive about its predictive policing efforts and its ties to Palantir.
[Photo: Ryoji Iwata/Unsplash]
To Karp, the fracas over Palantirs police contracts was emblematic of what he saw as the lefts descent into mindless dogmatism. He said that many liberals now seemed to reject quantification of any kind. And I dont understand how being anti-quantitative is in any way progressive.
Karp said that he was actually the true progressive. If you are championing an ideology whose logical consequence is that thousands and thousands and thousands of people over time that you claim to defend are killed, maimed, go to prisonhow is what Im saying not progressive when what you are saying is going to lead to a cycle of poverty?
He conceded, though, that partnering with local law enforcement, at least in the United States, was just too complicated. Police departments are hard because you have an overlay of legitimate ethical concerns, Karp said. I would also say there is a politicization of legitimate ethical issues to the detriment of the poorest members of our urban environments.
He acknowledged, too, that the payoff from police work wasnt enough to justify the agita that came with it. And in truth, there hadnt been much of a payoff; indeed, Palantirs technology was no longer being used by any U.S. police departments. The New York City Police Department had terminated its contract with Palantir in 2017 and replaced the companys software with its own data analysis tool. In 2021, the Los Angeles Police Department had ended its relationship with Palantir, partly in response to growing public pressure. So had the city of New Orleans, after an investigation by The Verge caused an uproar.
But Palantir still had contracts with police departments in several European countries. And since 2014, Palantirs software has been used in domestic operations by U.S. Immigration and Customs Enforcement, work that has expanded under the second Trump administration, and earned criticism from a number of former employees.
In 2019, when I was working on my story about Palantir for The New York Times Magazine, I tried to meet with LAPD officials to talk about the companys software, but they declined. Six years earlier, however, a Princeton doctoral candidate named Sarah Brayne, who was researching the use of new technologies by police departments, was given remarkable access to the LAPD. She found that Palantirs platform was used extensivelymore than one thousand LAPD employees had access to the softwareand was taking in and merging a wide range of data, from phone numbers to field interview cards (filed by police every time they made a stop) to images culled from automatic license plate readers, or ALPRs.
Through Palantir, the LAPD could also tap into databases of police departments in other jurisdictions, as well as those of the California state police. In addition, they could pull up material that was completely unrelated to criminal justicesocial media posts, foreclosure notices, utility bills.
Via Palantir, the LAPD could obtain a trove of personal information. Not only that: through the network analysis that the software performed, the police could identify a person of interests family members, friends, colleagues, associates, and other relations, putting all of them in the LAPDs purview. It was a virtual dragnet, a point made clear by one detective who spoke to Brayne.
Lets say I have something going on with the medical marijuana clinics where theyre getting robbed, he said. I can put in an alert to Palantir that says anything that has to do with medical marijuana plus robbery plus male, black, six foot. He readily acknowledged that these searches could just be fishing expeditions and even used a fishing metaphor. I like throwing the net out there, you know? he said.
Braynes research showed the potential for abuse. It was easy, for instance, to conjure nightmare scenarios involving ALPR data. A detective could discover that a reluctant witness was having an affair and use that information to coerce his testimony. There was also the risk of misconduct outside the line of dutyan unscrupulous analyst could conceivably use Palantirs software to keep tabs on his ex-wifes comings and goings. Beyond that, millions of innocent people were unknowingly being pulled into the system simply by driving their cars.
When I spoke to Brayne, she told me that what most troubled her about the LAPDs work with Palantir was the opaqueness.
Digital surveillance is invisible, she said. How are you supposed to hold an institution accountable when you dont know what they are doing?
Adapted from The Philosopher in the Valley: Alex Karp, Palantir, and the Rise of the Surveillance State by Michael Steinberger. Copyright 2025. Reprinted by permission of Avid Reader Press, an Imprint of Simon & Schuster Inc.
In the modern working world, employees have a lot on their minds. From stressing about high costs of living and pressing political issues, there are no shortage of worries to go around. But worries at work are stacking up, too, with many feeling uncertain about their future employment in the face of AI.
While workplaces are seeing some benefits to automating tasks with AI, there’s another not-so-secret problem with the technology taking off: employee anxiety. In part, that’s because workers are deeply stressed about being replaced, but there are also learning curves that come with working alongside the technology.
Also notable, one recent study found that AI is making workers’ jobs harder in another way. It messes with managers’ expectations, meaning they end up giving employees more work that they expect completed in less time.
Holding space for AI-xiety
In the face of such significant change, some say that leaders have a new job to do: They need to hold space for all the anxiety around AI, or, AI-xiety, if you will.
Heidi Brooks, a leadership expert and senior lecturer in organizational behavior at the Yale School of Management, tells Fast Company that because anxiety is now “a central part of the workplace experience,” leaders need to meet the moment.
But it’s not necessarily about trying to calm or settle worries, and it’s definitely not about ignoring them altogether. Instead, it’s about being present.
“Presence isnt just about showing upits about how you show up, Brooks explains. “Its the groundedness, the way you stay in touch with people in the midst of ambiguity or distress, without rushing to fix or smooth things over.”
Brooks adds that while it may feel more comfortable to avoid the worries, “choosing to stay steady in the face of uncertainty is a quiet but powerful form of leadership.”
Communication is key
As concerns around AI are booming, at the same time issues like burnout are skyrocketing. It’s no secret that many employees are feeling unsettled. That means bosses need to do more than just say they’re there for workers.
As Brooks puts it, “Presence is in the eyes of the beholder. Therefore, employees have to feel that from you.
“Communication, in this anxious context, becomes more than just information-sharing. Its a form of containment, Brooks says. Silence can promote fear, and in the absence of communication, people can fill the gaps with worst-case scenarios.” Therefore, even if leaders aren’t necessarily sure themselves how to fix the issues employees are worried about, keeping communication open is, in itself, still an effective tool.
Recent research supports the expert’s insight, too: A recent survey on frontline workers in the AI age found that while only 17% of said their organization is transparent about AI integration, 63% said communication about the technology is essential.
If you explain it, well accept it, one worker said. If you dont, well resist.
Brooks says employers don’t need to have all the answers to be good communicators and to calm fears.
“Its not about false certainty,” she explains. Its about helping people feel less alone in the uncertainty, and perhaps even inviting them to be part of the learning process by inviting their voice.”
Leaders need check-ins, too
Undoubtedly, leaders are in a new era, too. They have big challenges ahead of them as they learn to work with automation. Brooks says leaders are also learning to “hold space for human experience . . . as we find our way forward” in the AI age.
But not only do leaders have to worry about their teamsthey also need to check in with themselves, especially around their own anxieties and struggles when it comes to new technology.
“Its a good time not only to be intentional about touching base with people on your teams, but for you to do the same for yourself,” Brooks says. Leaders, then, also need the space to air their own fearsin addition to being a sounding board for others.
Brooks adds, “When we can be real about naming what we are going through, we are often wiser together, because we can discuss whats happening and learn our way forward.”
A snaggle tooth. A gap in someones smile. A birthmark or mole. What do each of these facial features have in common? They all have wabi-sabi.
Thats according to TikToks latest trend, which has users highlighting their imperfections and labeling them wabi-sabi.”
Not to be confused with the sushi accompaniment, wabi-sabi is a Japanese aesthetic philosophy that finds beauty in imperfection and the natural process of agingsomething we could all use a little more of in the age of preventative facelifts.
The concept celebrates imperfection and the natural wear and tear that occurs with the passage of time, whether thats a gently worn step, a chipped mug, or smile lines.
A sound featuring the term has since gone viral on TikTok, introducing many to the idea for the first time. Nearly half a million videos have been posted under the viral audio, originating from the animated sitcom King of the Hill.
In one episode, the character Bobby Hill picks up a rose and says, I like how mines a little off-center. Its got wabi-sabi. That clip has since been repurposed by users celebrating everything from crooked teeth to aquiline noses as wabi-sabi.
As with any concept that takes off on TikTok, some of the subtlety of the original philosophy has been lost as it spreads online. Yet, in an age of unrealistic beauty standards, looksmaxxing, and aesthetic micro trends, one that celebrates individuality and acceptance of perceived flaws is a step in the right direction.
In 2019, The New Yorker declared it “The Age of Instagram Face.” Six years on, Dazed wrote We have entered the age of TikTok Face. Aesthetic inflation or the normalization of more and more extreme cosmetic interventions over time, defined by Flesh World writer Jessica Defino, has eaten our collective brain.
In just the past few weeks, headlines about the skinny BBL (thats Brazilian butt lift, for the unitiated) and facelifts at 28 demonstrate the pervasiveness of the pursuit of aesthetic perfection. Its a vicious feedback loop that also bleeds into our offline reality, with plenty of research finding a correlation between time spent online and desire for plastic surgery.
If youve noticed the faces you see online slowly morphing into one and the same, you are not losing your mind. These days, we could all stand to embrace more wabi-sabi.
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Zillow economists just published their updated 12-month forecast, projecting that U.S. home pricesas measured by the Zillow Home Value Indexwill rise 1.5% between October 2025 and October 2026.
Heading into 2025, Zillows 12-month forecast for U.S. home prices was +2.6%. However, many housing markets across the country softened faster than expected, prompting Zillow to issue several downward revisions. By April 2025, Zillow had cut its 12-month national home price outlook to -1.7%.
In late spring, Zillow stopped issuing downward revisions. In August, it revised its 12-month outlook to +0.4%. In September, the forecast increased to +1.2%, and in October Zillow upgraded its 12-month national home price forecast to +1.9%.
This month, Zillow revised down its 12-month outlook for U.S. home price growth just a tad to +1.5%.
While Zillows national home price forecast is no longer negativeit isnt exactly bullish either.
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Among the 300 largest U.S. metro-area housing markets, Zillow expects the biggest home price increase between October 2025 and October 2026 to occur in these 15 metros:
Atlantic City, New Jersey +5.3%
Rockford, Illinois +4.8%
Concord, New Hampshire +4.6%
Knoxville, Tennessee +4.3%
Saginaw, Michigan +4.3%
Jacksonville, North Carolina +4.2%
Kingston, New York +4.2%
Fayetteville, Arkansas +4.1%
Green Bay, Wisconsin +4.1%
Torrington, Connecticut +4.1%
New Haven, Connecticut +4.0%
Hartford, Connecticut +3.9%
Hilton Head Island, South Carolina +3.9%
Manchester, New Hampshire +3.8%
Norwich, Connecticut +3.8%
Among the 300 largest U.S. metro-area housing markets, Zillow expects the biggest home price decline between October 2025 and October 2026 to occur in these 15 metros:
Houma, Louisiana -7.8%
Lake Charles, Louisiana -7.3%
New Orleans -4.7%
Shreveport, Louisiana -4.3%
Lafayette, Louisiana -4.2%
Beaumont, Texas -4.0%
Alexandria, Louisiana -3.9%
Odessa, Texas -3.0%
Monroe, Louisiana -2.7%
Punta Gorda, Florida -2.7%
Austin -2.6%
Chico, California -2.5%
Corpus Christi, Texas -2.4%
San Francisco -2.2%
Texarkana, Texas -2.2%
U.S. home prices, as measured by the Zillow Home Value Index, are currently up 0.01% year over year. If Zillows latest 12-month outlook (+1.5%) comes to fruition, it would represent a small acceleration nationally.
Below is what the current year-over-year rate of home price growth looks like for single-family and condo home prices. The Sunbelt, in particular Southwest Florida, is currently the epicenter of housing market weakness.
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In a report published in October, Kara Ng, a senior economist at Zillow, wrote, A year ago, 6 of the nations 50 largest metros were buyers markets; this September, buyers have the edge in 15 metros. Zillows market heat index shows the strongest buyers markets are Miami, New Orleans, Austin, Jacksonville, and Indianapolis. Thats due, in large part, to a surge of new construction in many of those areas in recent years. The hottest markets for sellers are in the Northeast and Bay Area: Buffalo, Hartford, San Jose, San Francisco, and New Yorkplaces where builders face some of the most stringent land use restrictions.
As best I can tell, the über-wealthy believe the world as we know it is ending, that there wont be enough to go around, and that this means they need to accumulate as much money and land as possible in order to position themselves for the end of days.
The way they do that is with an induced form of disaster capitalism, where they intentionally crash the economy in order to have some control over what remains. So the function of tariffs, for example, is to bankrupt businesses or even public services in order to privatize and then control them. Stall imports, put the ports out of business, and then let a sovereign wealth fund purchase the ports. Or as is happening right now: Use tariffs to bankrupt soybean farmers, who have to foreclose on their farms so that a private equity firm can purchase the farmland as a distressed asset, then hire the farmers who used to own and work that land as sharecroppers.
The über-wealthy, in collaboration with the current White House administration, are engaged in a controlled demolition of this civilization because they realize the pyramid is collapsing and they dont have faith that there will be enough left to feed and house everyone. The best they can do is earn a ton of money, buy a lot of land, control an army, and get people accustomed to seeing that army deployed. Thats what were watching on TV and on our city streets.
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It’s no coincidence that AI is emerging at this same moment in our civilizations history. As Lewis Mumford observed, new technologies are often less the cause of societal changes than they are the result. Culture is like a standing wave, creating a vacuum or readiness for a new medium or technology. If we really are at the end of capitalismthe end of this 800- or 900-year process of abstraction, exploitation, and colonialismthen we would also, necessarily, be at the end of the era of employment. I will get to why I think that may ultimately be a good thing, but lets go through the scenario thats running through everyones heads right now, and then find our way through to what I think are better days.
The spreadsheet people
Yes, AI is coming for our jobs. Not the super-creative ones, or the high-touch human ones, but the ones that maintain administrative control over everything. The majority of your jobs, dear Fast Company readers. All the people in the mortgage departments, the insurance companies . . . the spreadsheet people, the PowerPoint people. Doomers say its 90% of jobs, but lets say its just half of office jobs taken by AIs and, of course, blue-collar jobs taken by robots.
The problem with that, from a business perspective, is if you have no employees earning money out there in the world, then who will be your consumers? Even Henry Ford, despite his enthusiasm for fascism, understood that workers commoditized by his own assembly lines still needed to earn enough money to buy a Ford car. But how are AI billionaires going to continue to make money if there are no gainfully employed people capable of buying AI services from themor at least buying products from the companies that do purchase AI services?
And this is the weird part; in their vision, it won’t be by selling products to people, but selling stuff to the AIs themselves. It’s a tricky idea, but once you wrap your head around it, it all makes perverse sense. In today’s economy, a small number of wealthy people and corporations employ us and sell to us. They don’t really need to care what species we are, or whether we are human or android, as long as we are producing value for their companies and then purchasing products from them.
We already see how AIs can replace us as workers. But how could AIs also become the new population of consumers? They dont have time off to spend money. What do AIs need? To do their jobs better.
The humans dont matter
Instead of retailers selling food and clothes and entertainment to human consumers, tech companies will be selling energy, memory, network access, and processing power to the AIs so that they succeed in their jobs working as agent contractors for other corporations. The AIs will earn crypto for completing their agentic tasks, and then spend it with technology companies who provide them the resources they need to function.
As far as the owners of the companies are concerned, there’s no difference between a population of human employees with whom you have no contact and a population of artificial employees with whom you have no contact. The only game that matters is the competition with the other big companies for the agents business. The humans don’t matter.
So, assuming this tech-bro dream comes true, we end up with a small elite of big-business owners living in luxury with a small number of human servants, and a huge population of AIs doing the work and consumption. And, of course, in their vision for how this plays out, the rest of us humans become so disenfranchisedespecially the ones who live in citiesthat we will need to be kept under control until we presumably die out. We are simply not needed.
The good news
Sounds like a nightmare for most of us, but it also offers clues to an emancipatory vision for the end of employment. So lets consider that good option: For close to 1,000 years, growth-based capitalism has depended on real human beings doing work while a small elite extracted value from that work at ever greater degrees of leverage. In order to get that leverage, capitalism abstracted again and again and again. Each level of abstraction further removed from the people and places actually providing or creating the value. There’s a mineral in the ground. There’s a company mining the mineral, and another company selling the mineral. There’s yet another company investing in the company selling the mineral, there’s a stock company leveraging that investment, there’s a derivative on the stock, and a derivative on the derivative, and a platform trading the derivatives, and so on.
Or, more simply, there’s a person who needs to live in a house, but they just rent from someone who owns the house. Thats called the rentier. But the rentier has a mortgage on the house, and pays up to the bank, which pays up to another investor that owns the security, and so on and so on.
Thats the pyrmid of capitalism, with each investor or participant trying to move further up and away from the mineral or labor or living person into the abstraction of pure financial instruments. And this pyramid has simply grown too top-heavy to support itself. Theres only so much one can leverage up there before it comes tumbling down.
Total abstraction
AI, at least theoretically in the minds of crazy tech billionaires who believe AGI is genuinely around the corner, allows them to move on from the employment, exploitation, and colonialism of people, and simply level up in what they believe is a simulation anyway. We humans are discarded as capitalism moves up into a layer of total abstraction. It becomes the video game it was destined to become, with the humans replaced by non-player characters represented by digital icons or NFTs instead of flesh-and-blood mammals.
Our real-world economy only had so much stuff anyway. We matter-based entities cant scale as much as they need, so they leave us behind while they move into a layer of total and absolute abstraction. They live in a realm made entirely of digital representations, themselves manufactured by digital agents in exchange for digital currencies. It works because at least the AI agents value that crypto as much as the billionaires need them too. Instead of just 9 billion human customers, they get trillions of AI customers. We are not required.
But this is a good thing. Its akin to an enslaved population being released by the owners who no longer have use for them. We were not born to be their employees. As Ive explained in some of my books, the whole concept of employment was invented as a way of preventing us from getting wealthy. In the late Middle Ages, right before this capitalism was invented, people in Europe were starting to do really well. They learned how to make and trade stuff at local markets. They were doing so well that people were only working two or three days a week, and got taller than at any time until the 1980s.
Thats when the aristocracy came up with the idea of a chartered monopoly, and made it illegal for people to be in business for themselves. They had to become employees of one of the chartered companies, or face a penalty of death. Thats when we started working for companies instead of ourselves, and ended up in an economy built to favor those monopolies over small businesses.
A moment of transition
So the end of this scheme is not necessarily a bad thing. We simply have to return to the real economy that isnt worth capitalisms attention. Human commodities like food and housing are no longer asset classes worthy of their time, so theres no point in making growth-based markets for them. We can instead look at them as the commons-based resources they areoptimize for distributed flourishing instead of extraction and profit.
Yes, there will still be competition for energy. The AI economy would probably end up needing a bunch of nuclear power plants and better ways of dealing with all those spent fuel rods (if any of that AI scenario even becomes a reality). The current state of the technology doesnt fill me with hope for much more than a fierce market correction.
To me, its less important whether it happens than that we take advantage of this moment of transition. The ultra-rich have accepted the end of capitalismor at least the end of capitalism that depends on human labor and consumption for its survival. So its time we accept we are no longer valuable to the capitalist extraction machine and begin to look instead at how we are valuable to one another.
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