Unemployed

I keep seeing and hearing that AI is going to take our jobs. 

On podcasts, in the newspaper, in water cooler chats at the office, people seem worried. There are people throwing around stats that there will be 30% fewer jobs in the next decade, there’s going to be nothing left for collect graduates to do, that the next phase of Gen Alpha is worried about not having a job at all, etc., etc. 

My hot take: AI is not coming for our jobs. 

I may be biased – it’s possible that one of the reasons I don’t believe this narrative is because we’re growing, hiring like crazy (Intelligems will more than double headcount this year), and I still feel behind. I’ll be the first to admit that my personal bias might be real. But we’re also using AI pretty heavily internally at Intelligems (a topic for a future week) and I’m fairly familiar with Parkinson’s Law, which states that “work expands so as to fill the time available for its completion”. 

So here are my thoughts about why AI is NOT coming for our jobs:

Precedence

First, there is historical precedent of technological revolution without mass unemployment. From the agricultural revolution through the dot-com boom, we have continued to reinvent and evolve how we work. 

In the middle of the 20th century there were more than 340,000 telephone switchboard operators in the United States. And, by 1984, there were about 40,000. So, yes, technology took that job away, but those people found new jobs. This chart clearly shows employment steadily rising throughout the 20th century save a few dips during recessions. 

While technology advancements killed a single particular job, you could make a compelling argument that the ability for businesses to connect faster (and in an automated fashion) helped grow the economy and create new jobs, maybe even to the tune of doubling the number of jobs in the United States. Nobody needs to pull and push cables for telephone calls anymore, but that doesn’t mean they can’t work!

The same argument could be drawn using the spreadsheet. There are estimates out there that more than 1 million bookkeeping jobs went away thanks to Excel (and its predecessors), but the US job market has grown 2X again since the 1980s. Where did the bookkeepers go? They got new jobs!

Efficiency ≠ Savings

Second, an efficiency gain does not necessarily mean savings!

Imagine the hypothetical: Would you rather make your team 5% smaller to achieve the same product or keep your team its current size to achieve a 5% better output? 

The answer, to me, is pretty clear: You optimize for the 5% better product. If we play this out game-theory style, imagine my competitors decide to take savings and pocket it. Now my 5% advantage turns into a lead over my competitor and I can capture the entire market with that advantage. On the flip side, if my competitor also decides the path of investment, I need to be 5% better just to keep up or I’m toast.

Money Principles

Lastly, I believe there is a simple economic principle at play around ROI (return on investment).

Another hypothetical: Imagine two investment opportunities, one where $1 turns into $2 and a second where $1 turns into $2.05. Of course you’d choose the latter, 105% return is certainly better than 100%. But what if I asked you, knowing that the returns are higher you can choose to invest the same amount, less, or more money. Which would you choose? I would invest as much as I could! 

If we believe (which I’m assuming we do) that AI is making us more productive and improving our output, then wouldn’t I want even more super-powered employees? The more 5% gains I can acquire, the more it compounds. 

And that, I think, is where we’re headed first. We’re going to find that AI lets us get done work the work we want to get done, but can’t get to; and we’re going to find that that work creates more work (much in the way of Parkinson’s Law), because we’re moving faster and creating more.

AI may be an advantage early. But, very quickly, it’s going to be a requirement just to keep up.