Something Important Just Happened

What the release of Fable means for the future of work

The Patrick Dempsey: #0116

I write weekly articles for educators who are ready to get unstuck from outdated curriculum, resistant institutions, and a career that was built for a world that no longer exists.

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An AI Story

I hardly dabbled with Fable.

I was still amazed with Opus 4.8 and was busy working on other things, so I never really got to press its potential.

But seeing the capabilities of it from what others created—not that we’re necessarily at AGI or anything, but seeing how quickly things are changing, improving, increasing in ability to handle complex tasks and produce these just incredible outputs—it’s clear that even if the valuations of AI are crazy now, AI is reshaping work and society with it.

And we’re just getting started.

Which made me realize something that I don’t think most people have fully appreciated and many won’t until it’s too late.

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Recognition

Recognition is one of my favorite words.

We often use it to mean something like, “I know that, because it’s familiar.”

So, I can recognize my wife in a crowd of hundreds, because I know her features and her face so well.

But recognition actually means to re-cognize, to know again differently.

In its original Latin, to re-cognize was an active process of bringing something back into your mental workspace in order to examine it closely and critically, and then acknowledge it with a completely updated meaning.

And this is the moment of AI.

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AI’s Dual Role

Most of the hype around AI is about its potential impact—increased productivity and efficiency. That is definitely the banner story.

But I would say the more important function, which indeed underlies its technical impact, is AI simply as a forcing function.

By this I mean, when we can see AI executing tasks—from the mundane to the creative—we almost necessarily have to ask: what role do I play in this process? What is my real value when AI increasingly completes the tasks that have been, for all intents and purposes, the foundation of my livelihood? Perhaps even my identity?

We can think of it this way.

Let’s say I use AI to summarize a transcript and create a one-pager or a full slide presentation from it. Perhaps it used to take me a week to do it, and that with much less context than AI incorporates. And now AI can do it in minutes, context specific, and all aligned with our branding guidelines.

I don’t necessarily think that the slide presentation gains or loses value because of AI’s capabilities to create it. But I do think we have to start to wonder what the point of any of it was? Was any real value ever created by that presentation? Could the same information have been communicated differently? Did it really require that medium? Was it even necessary to share it at all?

If all I did was hit a button to produce that presentation, why do I need to hit that button at all?

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Focusing on What Actually Matters

I keep hearing this line from both the marketers of AI and those worried about its impact: AI will help organizations and individuals focus on the work that matters.

Which is, I guess, just one way of saying what I just said—that presentation wasn’t important. It was just something we did. It never had any real value.

Because, now that AI can do it, we’re told we can focus on what actually matters.

And if I press this further and ask, “Well what is the work that actually matters?” . . . it’s hard to find any stable answer or really any answer at all.

And of course it would be hard to find some definition, because the work was always about doing the work.

In our example, what mattered was putting the presentation together. That was literally the job!

But, now we’ve agreed that, at least temporarily, judgment is perhaps the only and most important thing left for humans to do. That is the work that actually matters—having AI produce everything and people giving it a once over to determine if it is good enough.

We really have no idea what we’re talking about. Even less about what we’re doing.

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AI As Additive

To this point, the overwhelming majority of conversations about AI and the use cases we are seeing for it are based on what I see is a fundamentally flawed assumption—AI as additive.

Here’s what we do. Here’s how AI can help. We’re up to date. Everything will be fine.

Well before AI, I used to question higher education’s model simply by asking:

“If we had to start again today, how likely is it that what we create would look like what we have?”

I had very specific targets in mind with this sort of question, of course. For example:

I figured no new institution would purposely create a decision-making structure that existed with a primary purpose of blocking progress.

I found it hard to believe that a new institution would think that their first priority should be to hire 27 VP roles and to bloat admin in every way possible.

I thought it unlikely that they would build a financial model that depended on 18-year-olds taking out massive loans that in themselves still didn’t cover the cost of enrolling that student and would then create entire arms of the operation to extract revenue from sources that really had nothing to do with the organization operating as a going concern.

And on and on.

But in this current line of thinking about AI as additive, we look at the organization, perhaps acknowledge that it could be run more efficiently, and then decide to implement AI into, let’s say, Advancement so we can extract even more endowment income from the few whales we have left.

We use AI. We source leads. We target our messaging. We get more value from donors. AI gives us a positive ROI. So we think it’s a win. We assume AI is working for us.

This is the illusion. This is a trap. Because AI isn’t additive.

And organizations and individuals that don’t completely change the foundation from which they operate will be completely irrelevant in the next 3 years.

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From 1 to 0

This article is the debut of a renewed focus for my work and a larger future project.

I’m calling it From 1 to 0: The Mindsets, Habits, and Skills You Need to Start Over (before AI takes over)

I see this as a natural extension of the themes and passions of everything I’ve written to this point.

It is surely the logical next step of why I started posting in the first place along with my original Substack article: I Need a New Job.

The driving question is simple: if you had to start your organization or your career from scratch today, knowing what AI can do already, would you build anything that looks like what you have? That is rhetorical—of course you wouldn’t! No one would start a business today and pretend the Internet didn’t exist. So why are we pretending AI is just a better tool for the business or career we already have? Starting over is the only option.

In this next article, I’ll break down why I think every organization and individual is about to go from 1 to 0, and why the only way to make it is to do it on purpose.