896: AI (Probably) Isn’t Taking Your Job (At Least Anytime Soon)
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This is episode number 896 on AI not taking your job anytime soon. Welcome back to the Super Data Science Podcast. I'm your host, Jon Krohn. Today's topic is whether AI is actually taking jobs. And spoiler alert, the data suggests it's not happening yet, despite all the anxiety out there.

On this podcast, I'm often covering the latest, most exciting AI advances. There's often a dark flip side to that in many of our minds, however. Maybe you've tried ChatGPT or Claude and thought, wow, this thing can do a lot of what I do at work. Well, you're not alone. Earlier this year, global Google searches for AI unemployment hit an all-time high.

In tech hubs like London and San Francisco, how long do you reckon I have left in your job has become standard water cooler conversation.

With AI models now capable of writing detailed reports, creating videos on demand, and tackling increasingly complex tasks with fewer hallucinations, it's natural to wonder if we're all about to become surplus to requirements. But here's the thing, when you actually dig into the data, the AI jobs apocalypse that everyone's worried about, it's nowhere to be found.

Let me walk you through some of these data. First, there's a recent paper by Carl Benedict Frey and Pedro Llanos Paredes. I've got that for you in the show notes. They're both from the University of Oxford, and it's been making the rounds in recent weeks.

Carl and Pedro suggest there's a link between automation and declining demand for translators. Sounds scary for translators, right? But here's where it gets interesting. Official American data show that employment in interpretation, translation, and related fields is actually up 7% year over year. That's not a decline, that's growth.

Then there's the Klarna example that's been cited everywhere. The fintech company made headlines boasting about using AI to automate customer service, but guess what? They're now doing a complete about-face. Sebastian Siemietzkowski, hopefully I'm not pressuring that, Klarna's CEO recently stated that there will always be a human if you want. So much for the complete automation of customer service.

Separately, some folks have been trying to find evidence of AI job displacement in macroeconomic data. One metric that's gotten attention is the unemployment ratio between recent college graduates and the overall American average.

Young graduates are currently more likely than the average worker to be jobless, and the theory goes like this. These young graduates typically do entry-level knowledge work like paralegal tasks, making PowerPoint slides at management consultancies, exactly the kind of work that generative AI excels at. So maybe AI has eliminated these jobs? Well, when you actually examine the data carefully, the narrative falls apart as well.

The relative unemployment rate for young graduates started rising back in 2009. That's 15 years before chat GPT burst onto the screen. And the actual unemployment rate, it's around 6%, which is still quite low by historical standards.

And what of data that directly address whether AI is hitting white-collar workers, the folks everyone assumes are most vulnerable? We're talking about people in back office support, financial operations, sales, and similar types of roles. If AI were decimating these roles, we'd see it in the employment statistics, right? Well, we don't. Over the past year, the share of employment in white-collar work has actually risen slightly. Let me repeat that. It's gone up, not down. I

American unemployment overall remains low at 4.2%, and wage growth is still reasonably strong. It's really hard to square strong wage growth with the idea that AI is causing labor demand to plummet. And this isn't just an American phenomenon.

Earnings growth across much of the rich world, Britain, the Euro area, Japan, remains robust. In 2024, the employment rate for OECD countries, those are developed countries, hit an all-time high. That's the share of working-age people who actually have jobs reaching unprecedented levels at the exact moment when AI capabilities are exploding. So what is going on here? There are two competing explanations here.

And both are probably true to some extent. First, despite all the breathless announcements about companies revolutionizing their operations with AI, actual adoption for serious production work remains surprisingly low. An official measure suggests that less than 10% of American companies are using AI to produce goods and services. Think about that. We're in the midst of what they call an AI revolution, and 90% of companies aren't even using it for real work yet. That's a big opportunity for all you listeners out there.

who are practicing and deploying AI in the real world. Lots more companies that still need your help ahead than behind. All right, so that's the first explanation for why...

AI is not taking jobs. The second explanation is that when companies do adopt AI, they're typically not firing people. Instead, AI is helping workers do their jobs faster and better. It's augmenting human capabilities rather than replacing humans entirely. This makes a lot of sense. Most jobs involve a complex mix of tasks, many of which require human judgment, creativity, emotional intelligence, or physical presence that AI can't replicate. Now,

I want to be clear, I'm not saying AI will never impact employment. Technology has always changed the nature of work, and AI will be no different. But the data suggests we're not facing an imminent jobs crisis. Instead, we're in a phase where AI is creating opportunities for those who learn to work with it effectively. Here's my take. Rather than panicking about AI taking your job, focus on learning how to use these tools to enhance your capabilities.

The most valuable workers in the coming years won't be those who compete against AI, but those who collaborate with it. Experiment daily with the latest LLMs. My favorite for general work today is Anthropix Claude Opus 4, though I reach for OpenAI's deep research for my most complex and important problem.

problems. You can listen to episode 870 of this podcast for more detail on OpenAI's deep research. Yeah, so experiment daily with latest LLMs like those so that you understand what AI can and can't do well, and then figure out how to integrate it into your workflow.

The bottom line is this. Despite all the anxiety, the data show that AI isn't causing mass unemployment. Employment is high, wages are growing, and companies are still hiring. Yes, the nature of work will evolve, but that's been true throughout history. The key is to evolve with it. So take a deep breath.

and smell the opportunities. Start thinking about how you can use AI to become even better at what you do. These are exciting times, and with the right mindset, you can thrive in the age of AI rather than just survive it. All right, that's it for today's episode. I'm Jon Krohn, and you've been listening to the Super Data Science Podcast. If you enjoyed today's episode or know someone who might, consider sharing this episode with them. Leave a review of the show on your favorite podcasting platform. Tag me in a LinkedIn post with your thoughts.

And obviously subscribe if you're not already a subscriber. But most importantly, we just hope you'll keep on listening. Until next time, keep on rocking it out there. And I'm looking forward to enjoying another round of the Super Data Science Podcast with you very soon.