I recently had approximately this conversation with my own employer's HR department. We're steadily refactoring tasks to find what can be automated, and it's a much larger proportion of what our entry-level hires do. Current AI is an infinite army of interns we manage, three years ago they were middle school age interns and now they're college or grad school interns. At some point, we don't know when, actually adding net economic value will require having the kinds of skills that we currently expect people to take years to build. This cuts off the pipeline of talent, because we can't afford to pay people for years before getting anything in return. Luckily (?) that is a temporary state of affairs until the AI automates the next levels away too, and the entire human economy disappears up its own orifices long before most of use would have retired.
In the intervening months or years, though, I expect a lot of finger-pointing and victim-blaming and general shaming from those who don't understand what's going on, just as I recall happening to many of my friends around my own college graduation in 2009 in the midst of a global recession. "No, mom, there's literally no longer any field hiring anyone with less than a decade of experience. No, even if I wanted to go back to school, there's a thousands times as many applicants as spots now, and most of those that get accepted will find the fields they picked are gone by the time they graduate and they have even more non-dischargeable debt. Sorry, but yes, I have to move back in with you. Also, most likely in a year or five you and dad will get fired and we'll all be living off grandma's savings that are growing at 80% a year."
The effect will at first be most clear in fields where entry-level cognitive tasks are especially prone to near-term AI automation, like software engineering and law as seen above. Other industries where complex human interaction or physical dexterity are crucial, for example healthcare and construction, will hold out for longer before being automated too through a combination of AI and robotics.
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Higher-level posts are normally filled by promoting those who entered at a lower level. When there are no lower level staff, what replaces that process?
I'm not sure this is a big problem. How much net attrition do you really expect over a decade, say? By which point who really cares? You will have so much more AI progress, and accumulated data (particularly if you've been gradually replacing the lower-level employees and you have an 'automation wave' moving through the organization where employees increasingly train their automated replacements or their job is simply reorganizing the jobs to enable automation).
It seems like to the extent there's much attrition at high levels, it is reduced in considerable part by these very dynamics: as returns to high-level human labor go up, presumably, there is less attrition from voluntary retirement or leisure consumption (and if the returns go down, then that implies that there is no 'shortage' of people for such high-level positions and so no problem); and also as the remaining human work becomes more 'white-collar' and based on difficult-for-AI things like reputation or experience or ownership or creativity, aging or opportunity costs begin to matter less, reducing another source of attrition.
(Even if AI or robotics is unable to do the 'core' of a job, they can help deal with various obstacles which might prevent a human from doing the job. An elderly manager who might decide to retire in part because they are low-key becoming worried about safely driving to/from the office will no longer think about that when they have a self-driving car or remote working becomes ever more feasible; older managers who might be slipping in their grasp of details or who have 'senior moments' will be able to rely on AI secretaries to catch those or just pause stuff for a while until they're back to normal; elite women might invest more in careers if they have Claude-bot as a trustworthy nanny and chauffeur, etc. One is reminded of President Biden: his staffers were able to work around his issues by doing things like rescheduling or canceling events to avoid exposing him publicly when he was bad; it was only an event that even the POTUS can't arbitrarily schedule, a presidential debate, that punctured the carefully-constructed illusion. Few of those staffers were qualified to be President of the United States, and yet, you don't have to be a good president to observe "sounds like Joe's having a bad day today" and quietly cancel his evening appointments for him so he can get to bed early.)
This sounds to me kind of like saying Jesus Christ will literally come back to Earth as a ghost for the rapture in 2012. I wouldn't put my money on people not just using the government to make something else happen.
People already wanted to distrust technology; there are plenty of personally fulfilling narrative roles people would gain from simply attempting the ordinary governmental intervention efforts humans have always tended to. I'm not saying it will be competently executed but it would probably be at least as good as internet- and automation-assisted feudalism.
Cross-posted from Substack.
EDIT 12/04/2025: The last two paragraphs were logically inconsistent and overly strong. I’ve updated the final paragraph to fix the issue and better reflect my position after more thought. Thank you to Julian for pointing this out.
AI job displacement will affect young people first, disrupting the usual succession of power and locking the next generation out of our institutions. I’m coining the term youth lockout to describe this phenomenon.
We are on track to build AI agents that can independently perform valuable intellectual labour. These agents will directly compete with human workers for roles in the labour market, often offering services at lower cost and greater speeds.
In historical cases of automation, such as the industrial revolution, automation reduced the number of human jobs in some industries but created enough new opportunities that overall demand for labour went up. AI automation will be very different from these examples because AI is a much more general-purpose technology. With time, AI will likely perform all economic tasks at human or superhuman levels, meaning any new firm or industry will be able to use AI labour instead of human labour. If this becomes true, then the long-term equilibrium is an almost-fully-automated economy, save for specific areas where a human touch remains essential, like childcare.
In the short-term, however, the transition to AI labour will happen in stages as capabilities improve unevenly. Moreover, organisations will be slow to fire existing employees, even after their work can be automated, since mass layoffs are disruptive, unpopular, and often illegal.
A hiring freeze, on the other hand, is much easier to implement and saves the organisation money as hiring is expensive. The process of screening CVs, interviewing candidates, and performing work trials takes up dozens of hours of employee time, while hiring entry-level employees is even more costly as inexperienced hires must be extensively trained before becoming productive.
With AI labour available as a substitute for this expensive process, companies will therefore reduce their hiring of new employees, or even stop hiring entirely.
There are already signs of reduced hiring in AI early-adopter industries. In tech for example, the CEO of IBM said in 2023 it would stop hiring for roles that could be done by AI, with around 30% of 26,000 non-customer-facing roles being open to automation over a five year period. Klarna has been under a hiring freeze since early 2024, with their CEO saying “the fairest way to deal with the efficiency gains of AI was to halt recruitment”, and Salesforce will hire no more software engineers in 2025 because of a 30% productivity boost from AI.
Elsewhere, legal firms have been looking to automate entry-level work for years with a 2023 report saying law firms “will not need to recruit armies of young lawyers to perform services that are no longer needed”, and instead “will need to make much more discriminating hiring decisions”. More recently, in January 2025 Thomson Reuters noted the following trend which they directly attribute to AI (emphasis mine):
The composition of law firms is in flux, with a shift toward more experienced lateral hires, growth in two-tier partner structures and less emphasis on junior associate hiring.
These effects will likely spread within software engineering and law as well as to other fields as AI models become more capable over time.
Hiring freezes will disproportionately affect young people and lead to youth lockout as they will be seeking precisely those costly entry-level positions that get cut. Graduate hiring will fall, youth underemployment and unemployment will rise, and we may see a rise in the proportion of young people living with their parents.
The effect will at first be most clear in fields where entry-level cognitive tasks are especially prone to near-term AI automation, like software engineering and law as seen above. Other industries where complex human interaction or physical dexterity are crucial, for example healthcare and construction, will hold out for longer before being automated too through a combination of AI and robotics. While new roles managing or interacting with AIs may emerge, these roles will be scarce and short-lived as AIs become more capable, in addition to the increasingly competitive job market meaning these roles will often be filled by more capable and qualified workers rather than untrained graduates.
At a societal level, youth lockout will disrupt the succession of power from the current generation to the next. With limited opportunities to gain skills and contribute, young people will have no consistent source of income and very few ways to gain influence. There will be fewer and fewer young people within our organisations, with AI workers performing the tasks previously assigned to entry-level workers. Our current weak form of meritocracy will degrade as young people lose the chance to show they can be trusted with power, causing social mobility to fall and reversing decades of progress.
While growing anger and dissatisfaction among the youth may push governments to implement new forms of social welfare, like mandatory hiring or even universal basic income, the political reality of an aging population and low youth voting rates could mean democratic governments move slower than they would otherwise.
Schools and universities will also be forced to respond, as the rationale of education being necessary for employment falls apart when there are fewer and eventually no jobs on the market. We may therefore see a shift in their self-justification towards learning as an end in itself or perhaps simply a status symbol as these institutions fight to remain relevant.
This widespread lockout will not be absolute. There will still be returns to brilliance for the lucky few with outstanding talent. Entrepreneurship will continue to offer a path to power for those young people with the right skillset, alongside other fields that require vision, taste, conviction, and talent. Organisations may continue to hire and train individuals with exceptional potential so that they can eventually replace the old executives and continue the organisation’s mission.
For the vast majority, however, youth lockout will mean a life of dependence and powerlessness. We could see a crisis of meaning once an entire generation finds themselves forced to sit on the side-lines, unable to contribute and shape the world as they watch it change around them.
We’re on track to lock young people out of our institutions and prevent them from steering their own future. Youth lockout is a natural consequence of full AI job displacement, and it will permanently disrupt the systems of meritocracy and economic participation that past generations fought to create.
Youth lockout would be a precursor to further societal disruption from AI job displacement and far from its worst impact. For one, it would signal a wider breakdown of our system of allocating economic power through paying people in exchange for creating value. With first the youth and then almost all ordinary people unable to contribute to the economy, we would lose the continual churn of talent and its side effect of capable people being given power to then use effectively.
Low employment at a time of high economic growth would also cause profits to accumulate in the hands of a few unless the government intervenes, and when the populace is no longer needed to produce value a disconnect could develop between economic activity and the desires of the people.
Historically, automation has been a force for good, lifting billions out of poverty and allowing us to support a much larger global population. It has also come with many costs, however, such as enabling the World Wars and causing huge environmental damage, and it is only with hindsight and on net that we can judge that the choice to automate was the right one.
Similarly, upcoming AI job automation will also have many positive and negative effects, only one of which I’ve analysed here. The overall impact of such a change to our economy must be thoroughly examined and understood before we make this likely-irreversible decision as a society. It is difficult to reason about such a transformative technology before its deployment, and impossible to foresee all the potential impacts. We should however continue to identify likely consequences, such as youth lockout, to make a more informed decision and steer towards positive outcomes.