Giving Me & My Kids The Edge Over AI

I actually wrote a first draft of this post about six months ago. I didn’t publish it. Partly because I sometimes lack confidence in my writing, and partly because it’s about AI predictions, which can feel like a tired subject everyone is piling onto.

Then I read this great piece: ‘How To Not Be Replaced by AI’ by Max Berry and it nudged me to finish this and post it. You might want to read his post first.

I’m a dad. We have an 11yr old and a 13yr old. They are at an age where they are just beginning to enjoy school subjects and extracurricular interests on a level that might eventually shape a career.

If you’d asked me five years ago what I’d push my kids towards learning, I would’ve said “coding” or “design”. Now I’m not so sure.

Honestly, I don’t just worry about how AI might affect their choices. I worry about the immediate future of my own white-collar job too.

I don’t want to get into AI hype versus skepticism. But it seems to me that two things are profoundly true:

So if white-collar work is going to exist long term, and if my own career is going to keep making sense, I’ll need to keep generating things that AI doesn’t, or can’t.

What do I mean by “things”?

In software, we generate artefacts like code, designs, and slide decks. We also generate softer outputs like negotiation outcomes and strategic direction.

AI is going to keep getting better at generating all of these. It’s already surprisingly competent at the soft stuff.

You see the same pattern elsewhere. In pharmaceuticals or hardware, AI is catching up to, and sometimes exceeding, human ability to generate artefacts and even manage parts of their deployment.

Arguably, AI’s greatest potential isn’t just recreating human work, but generating genuinely novel artefacts. New medicines. New materials. New climate solutions humans might never have thought to try.

Sometimes it feels like there’s no limit to what AI can generate.

I think there is.

As yet, untrained

AI models are fed enormous amounts of data. The bigger and better the datasets, the better the outputs.

Those datasets come from public and proprietary sources, but they share something important: they’re available.

The subconscious mind is not.

Today, AI can use available data to approximate subconscious human skills. Facial recognition is a good example. AI can distinguish between identical twins faster than their family can. And that same family, over time, learned to do better than strangers through repeated subconscious exposure.

Many “soft skills” AI is improving at, like writing a strategy document, follow the same pattern. AI finds patterns in available data and uses them to achieve outcomes humans often rely on learned subconscious processes to produce.

But not everything in the subconscious is learned. There are many human processes we don’t fully understand, don’t know how to articulate, and sometimes don’t even know why they exist.

A skill we don’t understand can’t be documented.

Data that isn’t documented isn’t available.

There’s a large corpus of data locked inside us that AI simply isn’t close to training on yet. That gives humans, including white-collar workers, an edge.

What now?

To keep my own job relevant, I’m planning to keep training my brain. That means not just leaning into soft skills that are harder for AI to catch up on, but deliberately exploring creative edges of the world.

For my kids, I’m going to gently steer them away from anything that’s purely artefact-driven, and more towards:

So how do you exercise creative muscle?

This might sound a bit wacky, but these are approaches I’ve personally tried, found useful, and don’t think AI will meaningfully penetrate for a long time. This list is as much a note to myself as anything else. There are other ways to exercise creative muscle and your milage may vary.

Make lots of things, preferably with other people

Start with doing… and then repeat. The more you create things, the more you learn (consciously and subconsciously!) what appeals and what doesn’t.

And doing this with others is even better. Collaboration forces you to explain ideas, absorb different perspectives and move faster. Showing work to real people teaches you what resonates beyond your own personal taste.

Dreams

Yes. Dreams.

Dreaming is an incredible creative resource.

Easy = Keep a notepad by your bed, or duck into the bathroom and record a quick voice note when you wake from an interesting dream. Don’t overthink it. Go back to sleep. Revisit it in the morning and see where it leads. You’ll be surprised.

Harder = Combine note-taking with lucid dreaming. I’ve managed to train myself to do this. Being able to gently guide dreams into certain spaces has led me to some genuinely new threads of thought.

Studying great art and bad art

Go to galleries. Read great books. Listen to great records. Then deliberately compare them with bad examples in the same medium.

Make notes on what separates them. The more abstract the art form, the better. It forces you to analyse intent, not just technique.

Human communities

Find communities to learn from, especially ones that feel “other” to you. Observe what makes them interesting. Ask questions. Notice what doesn’t translate easily.

Giving yourself constraints on purpose

You’re probably used to constraints at work — budget, headcount, time, feasibility. But these are all put upon you by someone or something else.

When you give yourself a set of rules or ‘code’ to play by, this can be an awesome lever for pushing you to think of different solutions. Some of the best human endeavours ever created were not just because the author had external constraints but because they created their own constraints to work within.

In summary

My thesis looks like this:

  1. AI is trained on data
  2. That data must come from an available corpus
  3. AI uses that data to pattern-match and generate outputs
  4. Those outputs may be familiar or even novel to humans
  5. Humans also generate outputs using subconscious processes we don’t fully understand
  6. Those processes don’t enter available datasets
  7. Which means there are things humans can do that AI won’t, until the subconscious becomes conscious

That window may close one day. For now, it’s where I’m finding my professional edge, and where I hope my kids learn to find theirs too.