Don’t Hold Your Breathe for AI


Are you a believer that someday soon artificial intelligence will be driving your kids to school, flying your family on vacation, and operating on your cancer?

As one who has seen the anticipation of AI rise and fall over several decades, I would like to warn you.  Artificial Intelligence has great limitations.  The greatest one of which is that we don’t know what it means.

Here’s the first piece of evidence for you.  A journalist has compiled a list of AI terms for the first AI glossary.  I don’t see the terms for Intelligence, nor AI.  It’s important to define EVERYTHING when you’re being a serious scientist.  Never assume anything.

Here’s the next piece of evidence.  Today’s most powerful AI vision systems can’t tell the difference between a stop sign and a speed limit sign.  Or a turtle versus a rifle.  How’s that for security?

Perhaps you say that this is only for vision systems, and doesn’t apply to other types of AI attempts.  Perhaps.  Then again, consider this article about how the Watson system of IBM has done as a doctor’s assistant.No single image summarizes our dread of Artificial Intelligence more than this.

Not well.  It’s been fired from several hospitals that were giving it a try.

Perhaps you know of a success story, or someplace that has a great AI dictionary and making great strides.  I’d love to hear from you.

My emotional and scientifically conservative side says “be skeptical” and “don’t hold your breath.”  We’ve been through this once, twice, maybe three times in the past 40 years.

Maybe that’s my “natural intelligence” talking.


Ivory Tower Easy Street

Why does anyone want to get a PhD?

It’s TONS of hard work.  Usually means NO social life until your mid 30s.  Your ONLY friends are similar masochists who are NOT competing with you in your field.

Finally, IF you manage to get through the feudal slave system called graduate work, and are “awarded” your higher degree of philosophy, are your dreams realized?


The nightmare begins.

No matter what the discipline, you must now scamper for funding, for post-doc work, for anything related to your dream, your passion.

Yes, it’s why you started this crazy process back when you were SO YOUNG.  You dreamed.  You had a passion.  A passion for learning.  A passion for a subject.


For a select few, the highest of the high, the luckiest of the luck, they land some form of academic job.  Not just any academic job, but a “tenured” job.  Of course, publishing and researching to the point of making tenure is yet another stressful round.  But once they make that benchmark, that holy grail, that nirvana, what does that academic do?

They can (mostly) relax.

And that’s the vision misleading our young, passionate, intensely curious dreamer who strives for the PhD.

And of all the PhD in academia, who has it the easiest?

Go ahead and guess.  I’ll wait.



You never would have guessed, would you?

Of all the academic professions, mathematicians are allowed to operate in the realm of pure creativity.  No, not the creativity of oil paints or clay.  Not even the creativity of “post-reconstructionist-logical-positivism” or “economic drivers in the mid-level artificial carbon credit markets.”  No, their creativity is pure, and focused.

For in math, there is no ambiguity, there are no loopholes in logic or proofs that are allowed, as in every other possible profession.  In this sense, it makes things harder because you can’t get by merely by the force of your personality.  Mostly.

Your papers might take years before they are approved.  Or rejected.  And the only thing worse than having your enemies find a flaw in your work (and they will) is having your FRIENDS find them first.

But the work you do, the progress you make, and how you contribute to the sum total of knowledge that is Science will be solid.  That is something very difficult to do in any of the hard sciences, much harder in the biological sciences, and virtually impossible in ANY of the social “sciences.”

In sum, if you’re a dreamer who loves learning and wants to make a difference, but also wants to live on easy street the rest of your life, then math is your path.  Yes, it’ll be hard, and you will leave many bodies behind as you prove yourself, but that’s life.

But in the end, isn’t that much better than getting a PhD in, well, ANYTHING else?

Good luck!


Hawking’s Intelligent T-Shirt


My brother-in-law got me a fun T-shirt displaying this text:

15 7H3
70 4D4P7 70

I’ll let you wrestle through it, as that’s part of the fun.

There’s a little problem, however.

It’s wrong. Now, I don’t know if the late great Hawking said this, I haven’t checked as yet.  However, the definition itself is wrong.

Fundamentally, there are many things that can’t adapt to change.  In fact, I know quite a few people, generally ex-employees, that do their best to resist change.  That’s partly why they are “ex” employees.

Despite their resistance to change, despite their inability to adapt to change, I wouldn’t call them unintelligent.

That’s part of the problem with not having a good definition.

So, with all due (possible) respect to Stephen H., here’s my hat in the ring.

Intelligence is the reflection of the environment within our defined life form.

Let me break this down.  It starts off with “Intelligence is…”  So that part is easy.  Since it doesn’t have to deal with change, it’s directly related to something else.  So measurement should be easier.  Not easy.  Easier.

Next, it’s a reflection.  This makes our job easier, because that means there is going to be a “source” and a “target.”  Every reflection requires some form of mirror, and the mirror reflects light from some object (the source) to a mind, making an impression (the target).

What’s the source?  It’s the environment.  Buckminster Fuller said it best: Environment is everything but me.

Here’s the fun part.  Where’s the target?  It’s going to be “inside” something.

What is that “something?”

That’s OUR defined life form.  This is the trickiest part, because most of the time no one takes the time to define who has the intelligence.  If we all agree we’re evaluating the intelligence of a mouse, then there it is.  If it’s the entire mouse species, that’s different.  If it’s going to be you, that’s one thing.  But if it’s going to be a whole bunch of us, that’s very different.

No single image summarizes our dread of Artificial Intelligence more than this.

Ever heard of group intelligence?  Some feel that groups are not quite as swift as individuals.  Now we can test for that.  What is the reflection of the environment within the group?  The group may have a great reflection, but if they can’t communicate it within themselves very well, then it doesn’t do them much good.  They would still be considered “intelligent” by my definition, but as many people have argued through the years, intelligence doesn’t always mean you’re smart.

There you have it.  This doesn’t quite answer a lot of the tough questions that are still out there.  Check out the post from 6 August 2018.  In the meantime, be careful out there.

Be intelligent.  Be smart!


Ptolemy Was Right

Did you hear about big broohaha back in 1540?  It was so big that people started using the word “revolution” to describe anything that upset everything.

Or some guy playing with his toys.  Either way, nice picture.

Yes, this guy named Copernicus turned the world inside out by telling everyone we weren’t the center of the universe.  It was a big deal.

Except it wasn’t.  A big deal, that is.  Not in real terms.

First off, it wasn’t the first time that someone else suggested the idea.

Secondly, nothing changed.  Sure, people thought they were going to fly off the surface of the Earth because it was moving so fast, but they didn’t.  Sometimes I wish those sorts of people would, but that’s another post.

Most importantly, as students of behavior, there is no “right” or “wrong.”  There is only behavior that can be measured with respect to a purpose.

Ptolemy’s ideas that the Earth was the center of the solar system was a perfectly good idea.  It sufficed for many things, in fact, most people don’t care, even today.  And he gave it to us around 150 AD.

But for those people who really want to understand the universe, it wasn’t good enough.  Models putting Earth in the middle were complex.  Way too complex.

So a better idea came along.  It wasn’t the first time people presented the idea, but now it made more sense, because the better theory explained nature more efficiently than before.  Clock makers, astronomers, and physicists were all much happier.

So what?

When someone has a crazy theory, we shouldn’t simply dismiss them as “wrong.”  If that theory works for them, if it makes them happy, then fine.

However, if we have a question that our theory addresses more efficiently, or if our theory satisfies our purpose better than theirs, then our theory is “better” for us.  It is not necessarily better for them.

So the next time you hear someone fighting it out over their different theories of nature, sit back and relax.  You’ll know that they are both right.  Try and enjoy the spectacle.

That is, unless they are politicians fiddling with your future.  In that case, you should worry.

And that’s always right.


Greatest Challenge For AI


A great book on the making of Stanley Kubrick’s and Arthur C Clarke’s 2001 A Space Odyssesy is fantastic.  I recommend seeing Stanley’s movie, getting Arthur’s book, and reading Bizony’s book as well.

Now, one prediction talked about in Bizony’s book was that we would have “Artificial Intelligence” by the year 2001.

It hasn’t happened.  Not in the way we want, anyway.

The reason is that the brilliant minds who are tackling the problem start from the basis of natural sciences.  They use math, engineering, biology, physics, all sorts of cool backgrounds.

It’s the wrong place to start.

Intelligence, whatever it may be, is a fundamental behavior.

Everything that it’s based upon, everything that we ask it to do for us, is also behavior.

In fact, the only thing “natural” about intelligence is the body we give it.

What our brightest minds must do is figure out what it is they want to achieve.  Here’s an example using today’s subject; intelligence.  However, as you’ll soon see, one small question quickly blossoms into lots of prickly questions, each of which must also be addressed.

Yes, they have to be answered.  If you don’t, then you’re in danger of falling into one of those loopy traps that never let you out.

Here’s simple question number one, Q1: Define Intelligence.

Go ahead.  Define it any way you want.  Now, for the prickly parts.

No single image summarizes our dread of Artificial Intelligence more than this.Q2:  You started as a baby, and before that you were less than a baby.  At what point in your lifetime did you become, “intelligent?”

Be careful with Q2, because if you’re defining something that is truly natural and scientifically rigorous, it shouldn’t change quickly, and should have specific characteristics that remain stable no matter what form YOU take.

Q3: You are related to other animals on this planet.  Are any of THEM “intelligent?”  This one is not only prickly, but also tricky, because it ties into the next question.

Q4: Even if your species is the only intelligence on the planet, it still came from the primordial swamp a few billion years ago.  Assuming the ooze was not intelligent, and that you are, at what point in the development of life did “intelligence” arise?

There you have it.  Only four (or so) questions to answer before anyone can truly create artificial intelligence.  Except that this is only for intelligence itself.  Of course, we still have to define all sorts of other things, but that’s for another day.

Knowing when to quit?

That’s intelligence.