The Three I’s of AI – One More Time, With Gusto!

I wrote before this: AI will never match human intelligence because it lacks the three I’s:




These things can be programmed, of course – everything can, but even if programmed are not going to “continue to grow on their own” as human’s do.

The lack of any of the three, or the three, is what distinguishes humans from machines today (among many, many, many other things) and somewhat the final frontier in AI becoming a more powerful entity.  Computers do what they are told, they learn as they are told, and they fill-in gaps IF and WHEN they are told.  This is nothing new, been the same from the beginning of times.  Actually, was one of the reasons I was attracted to computing.

Let me explain a little more.

If you ever watch TV, and I don’t blame you if you don’t, you likely seen NCIS in one of the many rerun stations (I think USA Network has the medal for most reruns of any show you can run using NCIS).  If you watched it, the original – not the spinoffs for different cities, you likely heard Special Agent Jethro Gibbs talk about solving cases based on his “gut feeling” when evidence is not plentiful (although, the gut feeling is about going to get the right evidence).  That’s not because he ate the sandwich that Alexander did not want to eat, but because he used intuition – what we usually call “gut feeling” is our natural ability to fill-in for missing data with our subconscious knowledge and similar skills.

When Alexander Fleming discovered penicillin, or so the story goes – I wasn’t there, he was looking for ways to fight bacteria.  He forgot his sandwich in the office one weekend, and when he came back on Monday, it was covered in fuzzy green stuff.  Of course, we don’t have that problem any longer since our bread can last for centuries and still be soft and spongy… but I digress.  Instead of tossing the sandwich aside, as most would’ve done, he had the crazy idea of trying that — stuff in the bacteria he was trying to combat.  Lo and behold, it paid off and today – we live way longer because of that.  That crazy idea? that was imagination – that is when we overcome core instinct to follow pre-established patterns to try something crazy.

I can easily define those two, and by themselves, they are enough to justify the fact that computers don’t have the ability to do what we do – even if we program them to do so.  We are constantly evolving our intuition and our imagination with everything new we learn or notice or affects us.  It’s how our intelligence works, and it is not a programmatic approach that can be replicated in code.  It’s part of how our brains operate, and how our intelligence grows.  It’s how we learn, at the basis, and best we can do is create a few rules for computers to follow to mimic, but never accomplish the same: intuition can be overcome by relaxing compliance and rules, imagination can be overcome by allowing for imperfect logic to be used (tested).  You can start down that path, maybe even mimic some of it – but computers don’t have the same “circuitry” we do and thus won’t end up being the same.  Alas, given sufficient time and power – sure, you can accomplish something (in theory).

But what about innovation?  What is it? How do you explain it? and more importantly, can you replicate it by computers?

I was chatting about this with Dr. Michael Wu a few weeks ago when he gave me the beginning of an answer (no answer is even final with Dr. Wu :), trust me — love chatting with him).

He said “Intuition + Imagination = Innovation”

Boom goes the dynamite.

Been thinking about that for a couple of weeks, and by golly, that’s it!

If the third one is the result of combining the first two, then we are even further away from being able to replicate it by computers.  If you can only imperfect mimics of the first two, the last one is far, far, behind.

Computers cannot innovate because they lack innovation and imagination.  Even if you were to relax the rules and let them use imperfect logic and fill-in missing variables – they still lack the ability to combine to the right amount of intuition with the right amount of imagination to innovate.  Do you want an example? How long have we had to suffer the scourge — er, modern benefits — of using taxis? How come computers never came up with the idea of – I don’t know, letting private drivers aggregate under one application and lease their services + vehicles for a discounted price? As Imagination took over the problem, we had private car services – but their prices were insufferable.  As intuition took over the problem, we ended up with professional taxi drivers (thanks Transports of London) – but again, pricing.  Innovation took over and looked for a different model, something that delivered the same outcome – but filled in missing data elements (will riders use it? will there be enough demand? can we get sufficient people? how do we pay them?) with intuition and innovation.

It needed a human to see a different model emerge, not a computer to figure out how to optimize the outcome.

Therefore, once again – singularity and computers taking over cannot and will not happen because – without us, they still don’t know what to do after all variables and knowns are exhausted.


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