johnmaconline

I loved the TV show The Six Million Dollar Man. 1974 – 1978. I was 5-9. 

I had the toys. Waited impatiently for each episode. Pretended I was Steve Austin and ran in slow motion while making the noise (IFYKYK).

Steve Austin was a cyborg. Here’s the definition from the opening credits of the show:

“A human being whose original parts have had to be replaced to one extent or another by machines that perform the same functions.”

The opening theme moves on. Steve crashes the space plane (real footage from NASA M2-F2), and then…

“Gentlemen, we can rebuild him. We have the technology. We have the capability to make the world’s first bionic man. Better than he was before. Better. Stronger. Faster.”

And they replaced his legs, one arm, and an eye. 

Now, he was bionic. A cyborg. Better. Stronger. Faster. At least physically. 

We’re already there. AI — the standard $20 / month AI — can make you better, stronger, faster. Maybe not enhanced physical performance (that’s coming, though), but certainly enhanced mental performance.

AI is leveling the playing field. Studies show that when embraced, current AI enhances productivity, efficiency, and innovation, with the most junior and least skilled workers receiving the most benefits. 

You don’t have to crash a test vehicle. It doesn’t cost you or the government $6 million. You don’t need surgery. The government doesn’t own you. 

You just need a credit card.

We’re all already Six Million Dollar Men and Women. 

Some very smart people (Tyler Cowen, Francois Chollet, Arc Prize Foundation, etc) are very high (or low, depending on one’s view of AGI) on o3. If not yet technically AGI, it’s definitely a breakthrough that gets close in practice.

I’ve started using it myself. I’m currently working on a technical blog article, eBook on hiring, documenting code, writing a little code, customer proposals, a corporate merger proposal, sales and marketing channels and content, and generating and exploring ideas to make 4TLAS work. 

I don’t yet have my own opinion, but I wrote this a couple months ago:

How will we know?

First, we had the Turing Test. Now we have others that test specifically for consciousness and cognition along particular axes — Perturbational Complexity Index (PCI), Unlimited Associative Learning (UAL), AI Consciousness Test (ACT), False Belief Task, Mirror Test, Deception Test, and Pain Response Test. 

I think we’re missing the point here. Any objective test we devise comes with a set of rules. Rules, once they are known, can be gamed. Especially by an AI.

Here’s how I’ll know that an AI has become sentient:

When it walks, figuratively or concretely, up to the table, sits down, and says, “Here’s what I wanna do…”

AGI and AI sentience aren’t exactly the same thing, although they’re close.

But I still stand by that. 

The best leaders know how to get the most out of their team.

They have vision, can transfer that vision to the team members, ask the right questions, know who’s best at what, know how to make the whole greater than the sum, can motivate each member, will remove the roadblocks, and can build the right feedback loops to move it all forward.

Today’s leadership with AI is no different. The team just happens to be ChatGPT (or Claude, Grok, etc).

One of the hopes for AI is that it can help us do more of the work we want to do and less of the work we don’t want to do.

The question is: What kind of work do we want to do?

It’s easy to answer with clichés. Work that’s creative. Work that’s meaningful. Work that’s fun.

What’s meaningful? Fun for who?

AI doesn’t care. AI will take on whatever we give it. Boring? Repetitive? Beneath us?

Sure, but if we’re not careful, we’ll discover that sometimes the boring parts are the parts that keep us engaged in life. The routine that shaped us. The repetition that made us better.

The work we say we want is often messier than we remember.

So, what kind of work do we want to do?

Here’s a cool little experiment that the people at The Hustle did: they used AI to replace the CEOs at several companies and compared what AI would do to what they actually did.

Same company. Same data. Same market conditions.

It’s a fun read. Spoiler alert: some of the decisions are the same, some are different.

AI is really good at patterns. It’s good at bounded problems. It’s good at history. 

Part of being a CEO is all those things.

However, part of being a CEO is also leadership. Leadership isn’t just making decisions given all the facts. Leadership is about having a vision for the future.

AI has no vision for the future. Just incentives.

If you’re a CEO, you should be using AI.

But also, you should be asking, “What kind of company do we want to be?”

I’m wordy. Especially when I’m thinking and talking at the same time. That’s a recipe for disaster.

So I ramble. And I can see the eyes glazing over.

I’m much better when I can dump it all out of my head, roll it around, experiment, and edit the snot out of it. It’s one of the reasons — actually the main reason — why I keep these posts to less than 250 words. 

Less is more.

But in software development, my tendency towards verbosity pays dividends.  

The more explicit, the better. Dump a million messages to the console so that if you have to analyze what happened after the failure, you’ll have a complete step-by-step map — the core dump. Future me (or future someone else) will thank you. 

And AI loves verbosity.

It doesn’t care if I’m rambling. It doesn’t care if I repeat myself three different ways. It doesn’t care if I’m even coherent.

AI just eats it up. The more I feed it, the more it gives me back. Round and round. AI doesn’t know what to leave out. It doesn’t know what’s important. It doesn’t know when to stop.

That’s still my job. Cut. Tighten. Refine.

Say less.

Make it mean more.