Change Kinda F#$king Sucks

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I recently gave a presentation to a room full of automotive leaders, dealers, and manufacturers in Quebec City that I called “Change Kinda F#$king Suck.”

I was talking about the changes happening in the car business.

But the car business isn’t alone.

We’re experiencing an amount and rate of change unlike anything we’ve ever seen in history.

One reason artificial intelligence could be such an important innovation is that intelligence is the primary driver of innovative change.

The current set of fast-paced technological changes we’re experiencing could accelerate even faster if driven not just by people’s intelligence but also by artificial intelligence.

The impact those changes could have on work and life is currently uncalculable.

There will be impacts.

We really don’t know what all those impacts will be.

Inevitably, those impacts will result in new ways of doing things.

And not everyone likes to change the way they do things.

The way people work, the work they do, the tools they use, and the jobs available appear to be things we expect will change forever.

That’s why I wrote about some of those work and job transition changes in my first Flip The Tortoise post.

Thankfully, the curve for change adoption is presumed to be pretty much the same across all types of change.

Many of us are predictably bad at dealing with change.

It doesn’t matter whether we’re talking about internet growth, smartphone usage, an office process, electric vehicle purchase patterns, or AI in the workplace; change adoption follows a similar pattern.

Some folks welcome change with open arms (innovators).

Some folk adopt change sooner than others (early adopters).

Some folks just aren’t ready for the change (the majority).

Other folks don’t change until they absolutely have to (laggards).

This past week, the godfather of AI, X-Googler, and Nobel laureate Geoffrey Hinton reupped his warnings about how artificial intelligence will impact the job market and the role that big tech companies leading that charge play in that potential job disruption.

In an interview with Bloomberg TV, he said the obvious way to make money off AI investments, aside from charging fees to use chatbots or selling trillions of dollars worth of GPUs, is to replace workers with something cheaper.

“I think the big companies are betting on it causing massive job replacement by AI, because that’s where the big money is going to be,” Hinton warned.

Geoff (I can call you Geoff, right?) added that while some economists point out previous disruptive technologies both created and destroyed jobs, it’s not clear to him that AI will do the same.

There’s early evidence that AI is affecting specific jobs, particularly for recent grads who are early in their careers.

Research from Stanford University found that since the adoption of generative AI, workers aged 22 to 25 in the most AI-exposed occupations experienced a 13% relative decline in employment.

“The discussion about AI taking jobs, or at least good jobs, is generally framed as tomorrow’s problem. However, there are some hints that AI may already be taking ‘knowledge worker’ jobs,” said Michael Feroli, chief U.S. economist at J.P. Morgan.

IMHO, no job is safe from AI disruption.

We’re all gonna have to change how we learn and work.

In the face of a radical and dramatic job disruption, it is difficult to understand why more people aren’t spending more time learning the ins and outs of AI tools.

Their jobs may literally depend on it.

But it turns out some of us have a profound case of what psychologists describe as algorithm aversion.

If we see an automated system or AI tool make a mistake, we internalize our understanding of that system as prone to errors and stop trusting it.

And AI tools get it wrong all the time.

Maybe we shouldn’t be so surprised that AI makes mistakes.

It is built on the bulk of human words and human knowledge.

And we make mistakes all the time.

So, yeah, maybe change kinda f#$king sucks.

But maybe we can weather change in an AI world by embracing AI's capabilities.

Find places where AI can help you in your daily life at home and at work. Know that it can make mistakes, but appreciate that you’re fallible too.

Maybe armed with superintelligence, we can together make fewer mistakes.

For that to happen, we collectively have to trust that it is possible before the majority of folks will embrace that kind of change.

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