One of the key points I repeated when talking about the state of the tech industry yesterday was the salient fact that half a million tech workers have been laid off since ChatGPT was released in late 2022. Now, to be clear, those workers haven’t been laid off because their jobs are now being done by AI, and they’ve been replaced by bots. Instead, they’ve been laid off by execs who now have AI to use as an excuse for going after workers they’ve wanted to cut all along.

This is important to understand for a few reasons. First, it’s key just for having empathy for both the mindset and the working conditions of people in the tech industry. For so many outside of tech, their impression of what “tech” means is whatever is the most recent transgression they’ve heard about from the most obnoxious billionaire who’s made the news lately. But in many cases, it’s the rank and file workers at that person’s company who were the first victims of that billionaire’s ego.

Second, it’s important to understand the big tech companies as almost the testing grounds for the techniques and strategies that these guys want to roll out on the rest of the economy, and on the rest of the world. Before they started going on podcasts pretending to be extremely masculine while whining about their feelings, or overtly bribing politicians to give them government contracts, they beta-tested these manipulative strategies within their companies by cracking down on dissent and letting their most self-indulgent and egomaniacal tendencies run wild. Then, when people (reasonably!) began to object, they used that as an excuse to purge any dissenters for being uncooperative or “difficult”.

It starts with tech, but doesn’t end there

These are tactics they’ll be bringing to other industries and sectors of the economy, if they haven’t already. Sometimes they’ll be providing AI technologies and tools as an enabler or justification for the cultural and political agenda that they’re enacting, but often times, they don’t even need to. In many cases, they can simply make clear that they want to enforce psychological and social conformity within their organizations, and that any disagreement will not be tolerated, and the implicit threat of being replaced by automation (or by other workers who are willing to fall in line) is enough to get people to comply.

This is the subtext, and sometimes the explicit text, of the deployment of “AI” in a lot of organizations. That’s separate from what actual AI software or technology can do. And it explains a lot of why the majority AI view within the tech industry is nothing like the hype cycle that’s being pushed by the loudest voices of the big-name CEOs.

Because people who work in tech still believe in the power of tech to do good things, many of us won’t just dismiss outright the possibility that any technology — even AI tools like LLMs — could yield some benefits. But the optimistic takes are tempered by the first-hand knowledge of how the tools are being used as an excuse to sideline or victimize good people.

This wave of layoffs and reductions has been described as “pursuing efficiencies” or “right-sizing”. But so many of us in tech can remember a few years back, when working in tech as an upwardly-mobile worker with a successful career felt like the best job in the world. When many people could buy nice presents for their kids at Christmas or they weren’t as worried about your car payments. When huge parts of society were promising young people that there was a great future ahead if they would just learn to code. When the promise of a tech career’s potential was used as the foundation for building infrastructure in our schools and cities to train a whole new generation of coders.

But the funders and tycoons in charge of the big tech companies knew that they did not want to keep paying enormous salaries to the people they were hiring. They certainly knew they didn’t want to keep paying huge hiring bonuses to young people just out of college, or to pay large staffs of recruiters to go find underrepresented candidates. Those niceties that everybody loved, like great healthcare and decent benefits, were identified by the people running the big tech companies as “market inefficiencies” which indicated some wealth was going to you that should have been going to them. So yes, part of the reason for the huge investment in AI coding tools was to make it easier to write code. But another huge reason that AI got so good at writing code was so that nobody would ever have to pay coders so well again.

You’re not wrong if you feel angry, resentful and overwhelmed by all of this; indeed, it would be absurd if you didn’t feel this way, since the wealthiest and most powerful people in the history of the world have been spending a few years trying to make you feel exactly this way. Constant rotating layoffs and a nonstop fear of further cuts, with a perpetual sense of precarity, are a deliberate strategy so that everyone will accept lower salaries and reduced benefits, and be too afraid to push for the exact same salaries that the company could afford to pay the year before.

Why are we stirring the pot?

Okay, so are we just trying to get each other all depressed? No. It’s just vitally important that we name a problem and identify it if we’re going to solve it. 
Most people outside of the technology industry think that “tech” is a monolith, that the people who work in tech are the same as the people who own the technology companies. They don’t know that tech workers are in the same boat that they are, being buffeted by the economy, and being subject to the whims of their bosses, or being displaced by AI. They don’t know that the DEI backlash has gutted HR teams at tech companies, too, for example. So it’s key for everyone to understand that they’re starting from the same place.

Next, it’s key to tease apart things that are separate concerns. For example: AI is often an excuse for layoffs, not the cause of them. ChatGPT didn’t replace the tasks that recruiters were doing in attracting underrepresented candidates at big tech companies — the bosses just don’t care about trying to hire underrepresented candidates anymore! The tech story is being used to mask the political and social goal. And it’s important to understand that, because otherwise people waste their time fighting battles that might not matter, like the deployment of a technology system, and losing the ones that do, like the actual decisions that an organization is making about its future.

Are they efficient, though?

But what if, some people will ask, these companies just had too many people? What if they’d over-hired? The folks who want to feel really savvy will say, “I heard that they had all those employees because interest rates were low. It was a Zero Interest Rate Phenomenon.” This is, not to put too fine a point on it, bullshit. It’s not in any company’s best interests to cut their staffing down to the bone.

You actually need to have some reserve capacity for labor in order to reach maximum output for a large organization. This is the difference between a large-scale organization and a small one. People sitting around doing nothing is the epitome of waste or inefficiency in a small team, but in a large organization, it’s a lot more costly if you are about to start a new process or project and you don’t have labor capacity or expertise to deploy.

A good analogy is the oft-cited need these days for people to be bored more often. There’s a frequent lament that, because people are so distracted by things like social media and constant interruptions, they never have time to get bored and let their mind wander, and think new thoughts or discover their own creativity. Put another way, they never get the chance to tap into their own cognitive surplus.

The only advantage a large organization can have over a small one, other than sheer efficiencies of scale, is if it has a cognitive surplus that it can tap into. By destroying that cognitive surplus, and leaving those who remain behind in a state of constant emotional turmoil and duress, these organizations are permanently damaging both their competitive advantages and their potential future innovations.

AI Spring

When the dust clears, and people realize that extreme greed is never the path to maximum long-term reward, there is going to be a “peace dividend” of sorts from all the good talent that’s now on the market. Some of this will be smart, thoughtful people flowing to other industries or companies, bringing their experience and insights with them.

But I think a lot of this will be people starting their own new companies and organizations, informed by the broken economic models, and broken human models, of the companies they’ve left. We saw this a generation ago after the bust of the dot-com boom, when it was not only revealed that the economics of a lot of the companies didn’t work, but that so many of the people who had created the companies of that era didn’t even care about the markets or the industries that they’d entered. When the get-rich-quick folks left the scene, those of us who remained, who truly loved the web as a creative and expressive medium, found a ton of opportunity in being the little mammals amidst the sad dinosaurs trying to find funding for meteor dot com.

What comes next

I don’t think this all gets better very quickly. If you put aside the puffery of the AI companies scratching each others’ backs, it’s clear the economy is in a recession, even if this administration’s goons have shut down reporting on jobs and inflation in a vain attempt to hide that reality. But I do think there may be more resilience because of the sheer talent and entrepreneurial skill of the people who are now on the market as individuals.