Building a Civilian Labor Corps: Bracing for the AI Job Apocalypse.

The progressive movement stands at a crossroads. While the right continues its march toward ethnonationalist populism and the center clings to the status quo, the left has failed to articulate a coherent vision that speaks to the material conditions of working Americans.

Over the past several weeks, we’ve outlined five non-negotiable pillars that must form the foundation of any serious progressive coalition: Housing First, because stable shelter is a prerequisite for human flourishing; a federal guarantee of meaningful work through a new Civilian Labor Corps; Medicare for All, because healthcare is a human right; Climate Action, because there is no prosperity on a dead planet; and Campaign Finance Reform, because democracy dies in darkness (and dark money).

Today we’re tackling our second pillar of establishing a Civilian Labor Corps, and the timing couldn’t be more critical. You may have picked up on chatter in the wind about the impending job apocalypse at the hands of artificial intelligence (AI). I’m here to tell you that this is real. It is coming faster and more furiously than you realize and we are wholly unprepared.

This is the ultimate force multiplier adding to intensified demographic headwinds from low birth rates to retiring boomers, slow growth in Europe and China, looming deregulation and tax cuts that will widen inequality, and disappearing social safety nets. Unf*ckers. This is more than a gathering storm. It’s a tsunami.

Introduction: Storm Clouds

Let’s start with some sobering reality: the U.S. labor force participation rate has been declining for decades, from a peak of 67.3% in early 2000 to 62.5% today. In our Boiling Point essay we covered the difference between the standard rate and the prime age labor participation rate, which represents adults between 25 and 54. Prime age participation is at an all-time high, which is why financial analysts tend to ignore the larger trend of Americans outside of this range sitting on the sidelines.

I see this as a dual threat though. We already have millions in the non-prime age labor force sitting it out. But the cost of living is such in America that more and more of these age groups are facing a crisis. The conventional wisdom chalks this up to retiring Boomers, but that’s only part of the story – and the story is about to get much more complicated because of rising inequality. The bigger issue is that the prime-age chunk in the middle is at risk of massive job losses across multiple sectors due to the AI revolution. More on that in a moment.

So if we dig into it, we’re actually facing a triple threat to labor market stability.

First, the Baby Boomer retirement wave is accelerating. Over the next decade, an estimated 41 million Boomers will exit the workforce. This represents not just a loss of workers, but a massive brain drain of accumulated skills and experience.

Second, historically low birth rates combined with increasingly restrictive immigration policies (likely to intensify under a second Trump administration) mean we can’t count on population growth to fill the gap. The U.S. fertility rate has fallen to 1.64 births per woman, well below the replacement rate of 2.1.

But the third factor is the real game-changer: artificial intelligence is poised to automate or dramatically transform millions of knowledge work and service sector jobs—the very categories that have traditionally absorbed displaced workers from other sectors. Unlike previous technological disruptions, AI’s impact will be felt across the skill and education spectrum, from call center workers to radiologists, paralegals to financial analysts.

To truly comprehend what’s coming so it doesn’t sound like Chicken Little proclamations of the past, we need to understand what AI actually is and how it’s going to be deployed throughout the economy in such a way that it will destroy the job market without backfilling with new opportunities as disruption and innovation has done in the past. We’ll talk this out in detail and then get into why current economic models and the capitalist framework don’t contemplate the fallout of this event. And it will be an event rather than a process.

Chapter One: The Coming AI Job Apocalypse

Joseph Schumpeter’s theory of “creative destruction” has long helped us understand how capitalism’s endless drive for innovation simultaneously destroys and creates jobs and industries. To wit, the transition from agricultural to industrial work, while ultimately contributing to rising living standards, was tremendously disruptive for displaced farm workers. The shift from manufacturing to services similarly upended communities and careers. And so on.

But here’s the crucial difference: those transitions played out over generations. A factory worker in the 1970s could reasonably expect their children to find opportunities in growing service sectors. Today’s AI revolution threatens to compress that creative destruction into a matter of years, not decades.

Consider that it took roughly 40 years for automated teller machines to reduce the average number of tellers per bank branch from 20 to 13. Yet recent analysis suggests that current AI technology could automate about 50% of total work hours across the U.S. economy within just five to ten years. The pace of change has fundamentally accelerated.

Don’t take it from me, take it from Vampire Squid HQ, Goldman Sachs, who has suggested that up to 30 million jobs will disappear in the next decade. Here’s an excerpt from their 2025 projections that speaks to the process behind the revolution:

“Companies will integrate AI with their proprietary data, either with retrieval-augmented generation (RAG) — an architecture that can connect LLMs to external, specialized datasets — or via a process known as fine-tuning, which involves enhanced training of an LLM with a smaller, specialized dataset. As a result, expert AI systems, or large expert models, will gradually emerge with advanced capabilities and industry-specific knowledge — for example, specialized models for medicine, robotics, finance, or material sciences.”

If we think about how companies are designed, there are three distinct layers in traditional economies. The foundation, operations and management. At the foundational level we’re talking about core structures and platforms, physical plants, factories, distribution centers or software. The operations layer is where the work in these places or on these platforms is done. Management represents ownership, directors, executives and leaders.

Due to the historically fast adoption of artificial intelligence tools, the operations layer will be most at risk in the coming years. The impact will be felt first in the knowledge and service sectors, followed by massive disruptions in the manufacturing sectors and supply chain. Traditional businesses that rely on complex interdisciplinary skills and interaction with the physical environment will be far less impacted. So think industries like agriculture, healthcare, environmental sciences, food and beverage, social work and skilled trades. However, even some of these industries will experience growth in efficiencies such as diagnostics in healthcare, climate modeling in environmental sciences, custom tool production in the skill trades and so on. But the ability for human involvement to be replaced entirely in these disciplines is remote.

Take the finance industry as an example. Financial institutions rely on a foundation of currency, asset management platforms, trading platforms and data warehousing; all of which must be organized into compliance and regulatory frameworks. Analysts, compliance officers, traders and financial managers exist in the operational layer. At the top, the management layer directs activities and decisions based upon inputs and information from the foundational and operational layers. The operational layer is most at risk in the early stages of AI agent adoption because routine organizing tasks can be done far more efficiently and with better outcomes.

We have already experienced similar disruption in the retail economy. Brick and mortar intermediaries have been impacted by the growth of online platforms that bring consumers and manufacturers together without the need for physical interaction. Importantly, there are several factors that allowed physical retailers to adapt to this new reality and carve out important niches that combine service and retail (like health and beauty) and offer experiences that cannot be replicated online (think restaurants and recreation).

However, the knowledge and service sectors that are geographically agnostic—meaning they can provide services online without the need for in-person interactions—have benefitted from the growth of software-as-a-service (SaaS) platforms. Other service providers have taken advantage of Business Process Offshoring (BPO) such as call centers and customer service centers. These support industries are highly at risk in the age of AI agents.

Business-to-Consumer (B2C) activities are likely to be in the vanguard when it comes to adopting AI agent technologies. You’re going to hear a nauseating amount about agents in 2025 before we move to quantum and robots in 2026. If you’re not attuned to agent conversations, here’s what it basically boils down to. Massive companies such as OpenAI, Microsoft, Amazon, Google, Meta, Anthropic and others are developing AI technology to perform certain tasks. Most people who interact with these tools are using them in the creative realm, which is where the buzz is at the moment. Doing research. Generating content and images or videos. Tools such as Google’s Gemini, OpenAI’s ChatGPT and Anthropic’s Claude are allowing users to supercharge their output in these areas.

But deeper in the AI universe there is a push to use these tools as foundations for other activities because of their reasoning power. Large language models (LLMs) have already trained on, or ingested every bit of publicly available information. That’s an astounding development in and of itself. Companies are using this core technology to build on top of, and that’s where the concept of agents comes in. A company can build a custom prompting environment to perform very specific tasks and the industry is referring to these as “agents.” A quick example in the workforce might be something like this.

• A customer service department has five employees who handle specific complaints, questions or concerns.
• The company receives 100 requests or service tickets every day that cover a range of issues.
• A custom AI agent can sort through each one, determine the nature of the request, and deliver it to the person most qualified to handle the request.

Fair enough. Now add another layer to it.

• The agent learns enough about the answers to these queries over time that it begins to answer many of them before delivering them to a representative.
• As a result the number of requests that pass through to a human drop from 100 to 20.
• This allows the company to fire their specialists and hire one head of service that has the capacity to answer the most complex queries.
• In this instance the company created a higher paid position while automating the routine knowledge jobs and reducing its headcount.

This isn’t creative destruction, it’s creative implosion. Now magnify this instance a million times over to comprehend the level of disruption we’re about to experience.

There’s a wonderful book written by Nobel Prize winning, husband and wife economists Abhijit Banerjee and Esther Duflo titled Good Economics for Hard Times. I appreciate the accessibility of their language and how they’re thinking about the post-neoliberal era specifically. The book was published in 2021 but had already considered the toll AI would take on the labor force. This passage perfectly illustrates the example we just gave.

“We suspect the current drive toward replacing human actions with robots cannot be prevented from taking a serious toll on the already dwindling stock of desirable jobs for low-skilled workers, first in the rich countries but very soon everywhere. This will add, to a greater or less extent, to what the China shock and the other changes… have done to the working class in much of the developed world. It could lead to a rise in unemployment or a multiplication of poorly paid, unstable jobs.”

There’s yet another layer to this that’s coming faster than even the leaders in the industry imagined. I don’t want to get too far into the weeds but there were a few major announcements in December of 2024 that were game-changers. The most important one was made by Sam Altman, CEO of OpenAI, who revealed that recent testing against independent benchmarks showed that their system was able to complete a task that it never trained upon.

Essentially, their system was given a puzzle that requires the system to make an intuitive connection; it was a simple puzzle that goes beyond logic and requires human ingenuity. In the AI world this is a concept known as artificial general intelligence (AGI). For reasons not worth covering here, Altman stopped short of claiming they had achieved AGI, but the industry immediately understood what had just happened. OpenAI’s system started thinking.

Sounds dystopian, and it kind of should. But here’s the practical meaning behind this discovery. This means that AI agents will have the ability to not only perform tasks, but make reasoned deductions about the nature of them. So what the industry is working on now is a world in which agents begin to communicate with one another to solve or perform tasks because they intuitively understand what we’re trying to accomplish by prompting them. This takes the vertical agent capabilities and multiplies them in a coordinated manner in AGI “agentic” systems.

Let me explain.

These agentic systems will develop much faster in the consumer arena and have a significant impact on activities that require complex decision making. The example most used in this arena is travel. Imagine having a personalized agent that knows your travel preferences, has access to your payment information and your rewards programs (hotel, credit card points, rental cars, etc.). Agents will be able to communicate with destination and travel partner agents to find flights, incorporate your preferences like: aisle or window, first class or comfort, time of day and weekday or weekend.

From there your personal agent can book hotel stays, make car reservations, make restaurant reservations, purchase tickets to events and provide you with an itinerary that automatically appears on your calendar. It will even be able to make or suggest changes depending upon personal circumstances or even external factors that might impact your travel dates (flight delays, natural disasters, embargoes, etc.).

This is still many months if not years from coming to fruition, but the recent advances toward AGI—where agents can perform more nuanced and independent tasks based on reasoning that allows communication between agents—mean that this has gone from aspirational to simply a matter of time.

In the Business-to-Business (B2B) market this will evolve at a slower pace due to multifaceted activities, legacy technologies, privacy concerns and process variability. Enterprise organizations will be quick to adopt vertical agents to streamline existing processes and workflows, which will eventually lead to a decline in the labor market for certain functions.

Organizations that can figure out how to deploy agents at scale will be able to reduce expenses dramatically, thereby creating an earnings advantage over slower moving organizations. This will prove to be the first major disruption in terms of internal hiring and a reliance upon external service providers such as data analytics firms, cybersecurity firms, marketing agencies, translation services, data entry providers, customer support centers, risk management firms and software developers.

Enterprise organizations will employ internal change agents to design systems that reduce internal and external headcount leading to a collapse in the mid-level labor market and service industry sectors that have traditionally supported them.

This unprecedented speed means we can’t rely on the market’s natural adjustment mechanisms. When technological change outpaces human capital adaptation, we get structural unemployment, wage depression, and social instability. We need a proactive policy response.

Chapter Two: Full Employment

Time to get wonky. Just as we’re suggesting in our non-negotiables that housing, healthcare, democratic representation and a clean environment are fundamental rights, so too is labor. There are sociological reasons to give everyone the right to work that have deep psychological and social benefits to be sure. The feeling of individual empowerment that comes from being able to provide for oneself or family and contributing to a functioning society, etc. Idle hands are the devil’s playground.

The human cost of joblessness is well documented. It can lead to a deterioration of physical and mental health, family stability and social connections. Individual skills atrophy during long stretches of unemployment, which causes a decline in self-worth and increase in substance abuse. And as we’ve seen through history and even more recently, it also provides fertile ground for political extremism.

A job is not just a paycheck—it’s a source of dignity, purpose, and social integration. When we allow mass unemployment to persist, we pay the price through increased healthcare costs, crime, family breakdown, and social alienation. The purely economic costs of joblessness (lost tax revenue, unemployment benefits, social services) often exceed what it would cost to simply employ people in socially useful work.

With that, let’s dig into the economic side of the equation.

So to be clear, I’m advocating for a government sponsored Civilian Labor Corps. The concept itself is pretty basic and nothing new, but the urgency due to AI is extreme.

So what would a modern Civilian Labor Corps look like? We envision a program that combines the best elements of the New Deal’s Civilian Conservation Corps with contemporary needs and capabilities. I’ll offer some examples before addressing the typical resistance offered from neoliberal economists and their capitalist mouthpieces.

First off, to dip our toes into the climate non-negotiable, we have a pretty substantial problem on our hands. The wildfires in Los Angeles are a devastating current reminder that we are nowhere near prepared for what’s coming. The extreme weather events that ripped through so-called “climate havens” provide further proof. We have a desperate need to build infrastructure and climate resilience but the private sector lacks the incentives to go to the lengths required to protect significant regions of the country.

Projects like renewable energy installations and maintenance, grid modernization, coastal protection, forest management and fire prevention, urban greening and heat mitigation and public transit expansion are all mission critical in this day and age.

On the human side of things, considering the aging population and economic precarity most of us face, we are facing an increasing need for elder care assistance, child care support, disability services, mental health peer support networks and community health workers.

These are very low profit parts of the economy that the free market simply won’t fix.

We can extend this further into community services such as affordable housing construction, historic preservation, arts and culture programs, youth recreation, adult education and literacy training.

Again, these kinds of low-profit motive but high community value endeavors are key to a healthy society and can function alongside market driven industries if the government is willing to step in.

Widen the lens even further and we have environmental protection initiatives that have enormous public benefits and low returns on capital investments such as ecological restoration, wildlife conservation, water quality monitoring, pollution cleanup and waste reduction.

The kinds of programs offered under the umbrella of a Civilian Labor Corps would offer living wage employment with benefits to anyone willing and able to work, with opportunities matched to skills and local needs. Training would be integrated into job placements, creating career ladders into both public and private sector employment. These have the added benefit of being non-competitive with the larger industrial and commercial base of companies that participate in the market economy. The key on this side, though not for today, is to prevent monopolistic behavior in private industry that gathers political clout and pricing advantages. Again, not for today’s discussion.

We’re not the first to recognize the need for bold public employment programs. Dr. Sadie Alexander, the first Black economist in U.S. history, argued forcefully in the 1940s that the federal government had both the responsibility and the capability to serve as an employer of last resort. She understood that private sector employment alone would never fully solve structural unemployment, particularly for marginalized communities.

Hyman Minsky, writing in the 1960s and ‘70s, developed this concept further through his proposal for a job guarantee program. Minsky argued that unemployment was not just a waste of human potential but a source of financial instability, as jobless workers default on debts and reduce consumption, triggering broader economic contraction.

More recently, economists like William Mitchell at the Centre of Full Employment and Equity have demonstrated how a job guarantee could serve as an automatic stabilizer, expanding during downturns and contracting during booms while maintaining a true full employment economy without triggering inflation.

Even Thomas Piketty, in his exhaustive work on inequality, has highlighted how periods of shared prosperity have historically required robust public sector employment and investment. The private sector alone tends toward increasing concentration of wealth and opportunity.

Even if we dismiss the idea of a job collapse and remain somewhere near the modern concept of full employment, the loss of operational layer jobs still holds destructive potential. Let’s return to Banerjee and Duflo to break it down.

“Even if the total number of jobs does not fall, the current wave of automation tends to displace jobs that require some skills (bookkeepers and accountants) and increase the demand, either for very skilled workers (software programmers for the machines) or for totally unskilled workers (dog walkers, for example), which are both much more difficult to replace with a machine. As software engineers become richer, they have more money to hire dog walkers, who have become relatively cheaper over time, since there is little alternative employment for those with no college education. Even if people remain employed, this leads to an increase in inequality, with higher wages at the top and everyone else pushed to jobs requiring no specific skills; jobs where wages and working conditions can be really bad. This accentuates a trend that has taken place since the 1980s. Workers without a college education have increasingly been pushed out of mid-skill jobs, such as clerical and administrative roles, into low-skill tasks, such as cleaning and security.”

Chapter Three: Breaking from Neoliberal Thinking

The first question is always, how do we pay for it?

First, the United States is uniquely positioned to promote a Civilian Labor Corps. As a sovereign currency issuer, the U.S. government’s spending is not constrained by tax revenue. As Modern Monetary Theory scholars have demonstrated, the real constraint is inflation, not dollars. As long as we’re employing real resources that would otherwise be idle (i.e., unemployed workers), the program is non-inflationary.

Second, many of these investments would generate significant returns through increased tax revenue from wages, reduced social service spending, healthcare cost savings and crime reduction.

Third, we’re already paying massive costs for unemployment and underemployment through lost GDP, social safety net spending, a sick population, an overburdened criminal justice system, reduced consumer spending and lost tax revenue.

We should note that we never seem to question the affordability of tax cuts for the wealthy or military spending increases. A program that puts Americans to work building public goods is at least as worthy an investment.

Okay. So, on the face of it, if this sounds like pretty sound economic policy, then where is the pushback on this concept?

Privately, or out loud on Fox News, I think a lot of people just consider these handouts. There are people in the GOP who are against public employment like this and social safety nets, but are in favor of work requirements for welfare. It doesn’t make any sense. I think the cold reality is the rich in this country simply despise poor people. This attitude has also created a culture of shame among the poor and working classes who hold billionaires in high esteem.

That’s the true magic trick the neoliberals pulled off. To convince people to vote for people who don’t want them to succeed and in fact hold them in contempt.

Publicly, the more official position against a Civilian Labor Corps is that it’s inflationary. And that’s not just a talking point. They really believe this. The entire Chicago school belief system is built around this concept and nearly every economist would agree that inflation is the biggest threat in any market based economic system. At this, I enter John Maynard Keynes into evidence (no matter how hard neoliberals try to deny his contributions).

It’s a laughable comparison, really. The face of the Chicago school known for his hatred of consumer protections, desire to eliminate public education and worldview built around the premise that there’s no free lunch against the man who helped Britain recover from World War I, rebuilt the global economy in 22 days at Bretton Woods and created global financial institutions that worked—until they were corrupted by neoliberals. It’s no match.

Moving on.

Keynes was very much in favor of public employment programs to manage precisely all of the activities we mentioned before. Keynes had a nuanced approach to the matter because he believed the foundation of a successful economy is built upon full employment. And I mean “full.” Everyone who can work is working, period.

Detractors such as neoliberal economists believe that full employment necessarily leads to inflation because it leads to growth in demand and therefore pressures pricing and wages. This concept in its strictest sense is known as the Phillips Curve and we’ve been operating under the most extreme interpretation of it since it was introduced in the 1950s. But Keynes understood that there were ways to manage aggregate demand through progressive taxation, interest rates, public and private investment incentives and competition.

Keynes maintained that aggregate demand, which relies on all of these factors, declines during recessionary periods and therefore the government should pull certain levers to boost aggregate demand to rebalance the economy. He also believed that you didn’t shut off features completely during boom cycles because of the nature of public investments in particular. Barack Obama found this out the hard way by introducing a massive public stimulus to boost project spending from scratch. The concept of “shovel ready” proved elusive in the early years of the Obama stimulus plans.

These things take time to plan and develop. Therefore, the government should always be investing in non profit-driven projects from conservation to art so it has the ability to manipulate levels of investments and employment in these arenas.

To Keynes, the economy is a delicate dance where the government takes center stage during a crisis but never fully retreats from the stage when things recover. Pavlina Tcherneva of The Levy Economics Institute of Bard College speaks to Keynes’ approach in a white paper titled, “Keynes’s Approach to Full Employment: Aggregate or Targeted Demand?”

“For Keynes, the first objective of policy was to hire people by whatever means possible. Once full employment had been reached, policy must plan, redesign, and substitute expenditures to make these public works useful and effective and to integrate them into a broader agenda for long-term, stable public investment. We can call Keynes’s approach to full employment a ‘on the spot’ approach.”

We’ve gone through long stretches of statistical full employment when the labor participation rate was much higher and inflation was level. This should automatically discredit the Fed’s neoliberal dual mandate approach on its face, but we still adhere to these Chicago school shibboleths for some reason. These periods and Keynes’ approach demonstrate that just because everyone is working doesn’t mean aggregate demand heats up to promote inflation.

We just lived through this exact experience. It wasn’t the stimulus checks and direct child credit payments that caused inflation; it was corporate greed, supply chain shocks and lack of competition that caused the spike in 2022 and 2023. They just blamed it on the consumer and conveniently ignored that the lack of competition in major consumer goods allowed these companies to “take price,” leading to the most significant corporate profits ever recorded. Just one of Keynes’ solutions would have tamped down on this whether it was progressive taxation or antitrust regulations. People having jobs doesn’t increase the demand for food, it just means they don’t have to go into debt to buy it.

This gets into another great point from Banerjee and Duflo. When we talk about taxation, there’s an interesting paradigm that we don’t talk about enough. To bring this back to the destruction of jobs due to AI, there’s a reason why corporations are pursuing this beyond padding profits.

“The US tax code taxes labor at a higher rate than capital. Employers have to pay payroll taxes on labor, but not on robots. They get an immediate tax rebate when they invest in the robot, since they can often claim ‘accelerated depreciation’ for a capital expenditure and if they finance it with a loan they also get to deduct the interest from their earnings. This tax advantage gives employers an incentive to automate, even if it would otherwise cost less to keep the workers…Robots won’t demand maternity leave or protest a wage cut in a recession.”

We continue to see how our version of capitalism, which is more corporate colonialism as we’ve mentioned before, is unfit to manage life as it currently is let alone handle the coming apocalypse. A Civilian Labor Corps is a massive policy initiative that will work to mitigate the catastrophic job losses, but it must be combined with our other non-negotiables if we are to begin shifting our economic paradigm to one that centers the working class and the planet.

Bring it home, Max.

The confluence of AI disruption, demographic shifts, and mounting social and environmental challenges creates both an urgent necessity and a historic opportunity. We can either allow these forces to further concentrate wealth and opportunity while leaving millions behind, or we can use this moment to build a more inclusive and sustainable economy.

Non-inflationary full employment guarantees fulfilled by a Civilian Labor Corps help create a wage floor for the private sector. No more need to fight for a minimum wage. It would help build infrastructure and ecological resilience projects that the private sector has little incentive to address. And the private sector would greatly benefit from things like improved public transportation, a healthier population, clean air and water and fewer climate catastrophes. We all do.

On the social front, it would strengthen communities and enhance economic stability among the masses, leading to more affirmative political engagement rather than fearful conspiracy rhetoric born of desperation. On this count alone, one can understand why a certain party would be opposed to this. Ahem.

The other pillars of our progressive agenda—universal healthcare, housing as a right, climate action, and democratic renewal—are essential. But without the foundation of economic security that comes from guaranteed employment, they remain incomplete. The time has come for progressives to embrace a job guarantee as a defining issue.

The right will cry socialism. The center will claim it’s unrealistic. But for millions of Americans facing technological displacement, stagnant wages, and uncertain futures, it offers something far more powerful: hope backed by a concrete plan of action.

The only question is whether we have the political will to match this moment of transformation with the bold response it demands. The cost of inaction—in human potential, social cohesion, and economic stability—far exceeds any price tag for this program. The future of work is coming. This is undeniable. Not only will a Trump administration eliminate any guardrails or protections against unethical applications, it will hasten the despair among the population by eliminating core services and welfare programs.

One of the chapters in Good Economics for Hard Times is titled “Player Piano,” referencing Kurt Vonnegut’s dystopian near-future America. In the book, the country has been almost entirely mechanized after a third world war, eliminating the need for human labor. This widespread automation has created a stark divide between two classes: the wealthy upper class of engineers and managers who run society, and the lower class whose skills have been replaced by machines.

Our lives are about to imitate this art if we’re not careful about this next phase.

They’ll tell you it’s a brave new world brimming with miracles from cancer cures to 15 hour work weeks where agents manage our daily lives and eliminate stress. And, look. AI might cure cancer. Could happen. And some people have 15 hour work weeks with AI agent assistants in their future for sure. But the masses won’t participate, and you can be sure that only the very few will have access to the modern miracles of medicine. More to the point, these are the sales pitches. The real reason why up to a trillion dollars has been invested into AI research and development from the private and public sectors is to find ways to eliminate jobs. Or as Banerjee and Duflo put it:

“Notwithstanding the grandiose talk about singularities, the bulk of R&D resources these days is directed toward machine learning and other big data methods designed to automate existing tasks, rather than the invention of new products that would create new roles for workers, and hence new jobs.”

You’re not part of their plans, unless being eliminated from the game counts. These companies can talk all they way about ethical AI and the shared social responsibility they have in helping society. These companies are in the biggest foot race in human history and they’re going to run right over us to get to the finish line; even if there’s no one left to meet them there.

Here endeth the lesson.