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Again Garbage In, Garbage Out

I feel like Marty McFly in Back to the Future when I see this stuff. Wait, Ive seen this one! This is a classic!

Just like every other whizbang computer science invention, it suffers from the same weakness that weve seen every other AI thing do. If you put bad data into it, youll get bad data back out. Only this time, its worse, because the computer is deciding what bits of the data are important, and you cant always know what its looking at and why its getting things right. Something that works 99% of the time can fail spectacularly or in comical ways when the neural net is found to be looking at the wrong stuff.

These problems can probably be solved, though, but lets explore this a little further.

By now, I hope readers know three things:

But, artificial neural networks are still amazing. One super cool thing they do is help computers chew on qualitative information (uncountable things something theyve always struggled with). Traditional programs can readily deal with hard facts like an objects size, position, and velocity (these are all expressible as numbers), but they couldnt tell us what the thing was. Autonomous vehicles will be impossible if a vehicles computer cant identify objects, so this is vitally important to that mission.

They dont identify things the way we do, though. Artificial neural networks exist to convert qualitative judgments (what is that thing?) into quantitative ones for a program to deal with (this is Thing #3481, so now these mathematical rules will apply to the program). This enables a computer to do things that were previously not well suited to it, and thats amazing.

But, the ability to make limited qualitative judgments (categorizing objects) doesnt mean a computer system is good at making all such judgments like we are. Once they get to the end of their training, they have no ability to improvise or adapt and go on.

It is the pinnacle of bad AI thinking to compare the human mind to a computer. We have popularly done this for decades, but its fundamentally wrong.

Now, notice I didnt say brain. I said mind. We often use those terms interchangeably, but when we do that, we ignore the fact that we dont know how the human mind and the human brain relate to each other. The mind may be in the brain and due to a physical process we dont yet understand, or it could be something else. We dont know that much yet.

We do know a lot about the brain, including how its wired up to our nerves, how different parts of the brain connect to different senses, and how diseases or problems in the brain lead to problems a person subjectively experiences. We know that when a person is happy, certain parts of the brain light up with activity in scans. We know that when a person smells pheromones, different parts of the brain light up depending on the persons gender identity and/or sexual orientation (and not necessarily their sex).

We also know that we can get the brain to affect peoples consciousness through manipulation. Chemicals can make a person enter altered states of consciousness, lose consciousness, or see things that arent there. Electromagnetic stimulation, ultrasound, and even direct electrical stimulation can all have predictable effects. Neuralink isnt lying to us when they say they could eventually do things like pipe audio or even image overlays into the brain that our consciousness would perceive.

Using the human brain for inspiration has led to the development of artificial neural networks, and those are doing amazing things, but they cant reproduce the mind at this point, and may never be able to do so.

The biggest roadblock is that we havent solved the Hard Problem of Consciousness. Despite the many things we do know about the brain, we dont know what mechanism drives a human beings experience of consciousness. Somehow, the human brain is doing something thats beyond the sum of its parts, and a mind somehow exists that the brain or body interacts with. How do we know that a mind and consciousness is happening? Only because the person tells us that they experience consciousness.

This idea of believing people without evidence may seem to fly in the face of science, but science was never meant to be a faith, nor was it meant to explain stuff like this. Again, see Goffs book on the topic for a lot more details (or a video here where he goes over it).

As stated earlier, this goes all the way back to Galileo. We dont know what consciousness is, or how it happens, because Galileo deliberately set that very issue aside for later so scientists could focus on that which could be measured and computed. Now, were trying to take a philosophical approach to inquiry that was specifically designed to exclude consciousness and use it to explain something we cant even prove exists beyond taking each others words for it (our experience of consciousness). Will that approach work? We simply dont know.

While physical science as started by Galileo has been hugely successful, theres simply no guarantee that it will lead to an understanding of consciousness, and if it does, it might not be something we can reproduce with computers.

In the last part, Ill finish explaining how these artificial neural networks arent alive or conscious, but that it really doesnt keep companies like Tesla from doing what it aims to do (build self-driving cars).

For ease of navigation for this long series of articles, links to all of them will be here once they are published:

Part 1: Why Computers Only Crunch Numbers

Part 2:Miscalibrated Trust In Mathematics

Part 3: Computers Only Run Programs

Part 4: How Neural Networks Really Work

Part 5 (you are here): What Artificial Neural Networks Cant Do

Part 6: Self Driving Cars Are Still Very Much Possible, Despite Not Being Alive

Featured image: Screenshot from Teslas AI Day

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Demystifying Neural Networks: Teslas Are (Probably) Not Alive, But Thats OK! (Part 5) - CleanTechnica