Artificial Intelligence, or AI, is all the rage these days.  “It’s going to eliminate all of our jobs!!”  “It’s going to become more intelligent than humans!!!” “It’s going to become sentient and turn into Skynet!!” 

Pffffft.

It’s not going to do any of those things.  Not even close.

Now don’t get me wrong – AI (and note – only the ‘A’ part of that is accurate) is here to stay.  And it’s going to lead to some very powerful tools, some of which can be very useful.  Of course, it will also lead to some tools that are not so useful.  And it will be misused and abused, which might be its most frightening prospect.

But if you are worried about Skynet, I’m here to tell you, don’t – The Terminator is a great action movie but not much more.  Nor should you worry about AI eliminating all the jobs, a notion that can be dispensed with in multiple ways, including with simple arithmetic.  We should once and for all dispense with the idea that AI will become conscious. Similarly, the notion that AI exhibits true intelligence should also be tossed in the wastebasket.  To understand why, we’ll start with the point that the rubber meets the road (or where software meets hardware) in computers.

The 1’s and 0’s of Artificial “Intelligence”

When I observe certain people hyping AI, namely those with a technical background, I notice they are mostly software engineers or programmers.  Many of these software engineers are extremely intelligent, and can make a computer do things – through programming – that I (also a technical person, but with a hardware/circuit orientation) could never dream of doing.  Nevertheless many of these AI-hypesters have a huge gap in their understanding of how computers actually work.  Their interactions with computers are through high-level programming languages, several layers of abstraction away from what is happening at the hardware/software interface.  Because of that they are only vaguely aware, at best, of the hard physical limits of computing.

For the non-technical, a little explanation is warranted here.  Almost all software programming – and AI is software – is done using what are called high-level languages – Python, Perl, C, … and for those of you who are old geezers (as am I), Fortran, Basic, Pascal, etc.  High-level programming languages are essential, as the practically infinite variety of software we use today would not be possible without them.  But the processor in your computer system cannot understand these languages directly – it needs what is known as a compiler that translates (“compiles”) the high-level language program into machine language that the computer understands.  And ultimately that means, in the digital computer systems we use, it gets converted into 1’s and 0’s. 

But even the 1’s and 0’s are somewhat of an abstraction – the processors used in computer systems are electronic circuits, and as such work with voltages and currents that represent these 1’s and 0’s, rather than working with the digits themselves.  Thus, in the chips used to implement computer systems, these 1’s and 0’s are represented by corresponding voltages – e.g., a “high” voltage for a logic 1, and a “low” (or no) voltage for a logic 0.  I’m not going to delve into the actual circuits as to how this is achieved (although they are relatively simple), other than to say you can think of these circuits as 2-position switches.  A single switch in this analogy can generate a logic 1, or high voltage in one position, and a logic 0, or low voltage in another position.  These switches, constructed using transistors, can be combined to form logic gates, and logic gates can be combined to form even more complex structures.  But at the heart of it all, at the lowest level, all you have are a bunch of switches that produce the voltage levels and corresponding binary logic levels.

Just about every computer system you own – from your smartphone, to your tablet, your laptop, your desktop – has billions of transistors, and thus billions of switches.  And they are nothing even remotely like neurons in the human brain.  Putting more of them together doesn’t turn them into neurons either.

Hey, I Came Here to Read About AI, not this Switch Stuff!

Ok, so you ask now, “if this essay is about AI, then where is he going with all this switch stuff?”  Where I’m going with this is to show you what AI – indeed what any software does – at the fundamental circuit level.   At the circuit level, it is, depending on the input voltage, making the output voltage change between a high voltage and a low voltage – between a logic 1 and a logic 0.  On circuits used in the chips of a computer system, this switching behavior can occur billions of times per second.  Multiply that by billions of these switching circuits, and you’ve a whole lotta switching going on.  And in AI computing workloads?  You have orders of magnitude more switching than the most processor-taxing game your kid runs on his gaming PC. 

But can true intelligence (much less consciousness) arise from this mere switching behavior, having billions of circuits switch between a logic 1 and logic 0 (a high voltage and a low voltage) billions of times per second?  Digital computers have been operating this way for decades now.  There is nothing remotely intelligent about the way they function.  Simply and adding more of switches and making them do it faster and faster doesn’t move ball even a nanometer closer to intelligent behavior, because the transistors used to create these switches are not neurons, and never will be neurons.  They’re just switches.  On or off.  Logic 1 or logic 0.  Putting more of these switches together into a more complex structure does not suddenly make them into neurons.  And because of this, computers will continue to understand language and human thought in the same way a radio understands music, i.e., not at all because they have no such capability of “understanding.”

If someone disagrees with me, and truly believes that AI can be truly intelligent and can truly become conscious, I’d love to hear their explanation as to how we are going to get there based on making more of these switching circuits and making them switch faster.  I’m all ears.  All I’ve ever heard from those that believe AI will become some sort of machine messiah (nod and wink to my progrock friends) are pure underpants gnomes-level leaps of logic.  As AI gets “better,” real intelligence and consciousness will just magically occur, they believe.

What an absolute load of bull-shinola.

The only surefire way I know to make electronic computers truly intelligent is this: convince God to “miracle” intelligence into computers.  If God wants computers to by intelligent, then by God (sorry) they will be.  But absent that, there is no other way.  Not with the computing systems we have now, not with CMOS switching circuits even in the billions of trillions, not with simply manipulating voltages to make 1’s and 0’s.  Ever more complex software programs – even what is called AI – isn’t going to suddenly cause intelligence, much less consciousness, to spring forth from silicon or some other substrate that may be used in the future.  If that’s all it took, we’d be there by now.

If you want to explore the topic of intelligence in man-made machines (or our inability to accomplish that), you can also explore Kurt Gödel’s incompleteness theorems.  I’m not going to get into the discussion about that here, other than to note that when Gödel came up with these theorems, it freaked him out a little bit as he thought he might have proven the existence of God.  But that’s pushing the limits of this discussion, so you’re on your own here.

Intelligent, sentient computers of the electronic variety make for great science fiction.  HAL from Arthur C. Clarke’s 2001: A Space Odyssey is one of Sci-Fi’s most memorable characters.  My personal favorite – Mike, from Robert A. Heinlein’s The Moon is a Harsh Mistress – is another one that seeped into the consciousness of many Sci-Fi aficionados.  But those computers are fiction, and intelligent electronic computers like them will remain so, absent divine intervention.

Notice I said “electronic computers.”  Biological computers are also a thing, and they can be very intelligent.  And better yet, there is a way to make intelligent biological computers – it’s very old tech, a time-tested technique known as “having babies.”  But that’s also another discussion.

“But hey, you didn’t address it taking all our jobs and all the other things AI is going to do, good and bad!”  This piece is getting kind of longish, but I will return with more confessions of my AI skepticism, and soon.  Or, as another AI character once said, “I’ll be back.”