Computer experts have long struggled to achieve artificial intelligence (AI), computers or robots with human-like intelligence. There have been many errors in predictions about when artificial intelligence would appear. Page 12 of the paper here gives a graph showing that 8 experts predicted that computers would have human level intelligence by about the year 2000, and that 8 other experts predicted that computers would have human level intelligence by the year 2020 (something incredibly unlikely to happen in the next few years).
Some experts continue to make dubious predictions about artificial intelligence. Some have become what we may call AI alarmists. An AI alarmist is someone who warns us that computers or robots are going to get so smart that a great disaster will occur. Some say that a large fraction of the population will become out of work, as computers or robots take the jobs of bankers, physicians, lawyers, and software developers. Other AI alarmists predict something worse: that machines will become so smart that they take over the planet.
Such alarmists often say, “Maybe if we're lucky they'll keep us as pets.” High-tech luminary Elon Musk has said, “A.I. is a fundamental risk to the existence of human civilization, and I don’t think people fully appreciate that.” Stephen Hawking has made similar comments.
According to the computationalism theory of the human mind, the mind is like a computer, so one day we will be able to develop computers that produce outputs just like human consciousness. Such a theory is assumed by most AI alarmists. Such theorists usually don't tell us that they are advancing the computationalism theory of the human mind. They usually just pronounce the dubious ideas of such a theory as if such ideas were self-evident.
But the computationalism theory of the human mind is not valid. The human mind is not like a computer, and the brain has nothing like these seven things that a computer uses to store and retrieve data. The human mind has facets such as conscious experience and understanding, which have never been produced to any degree by a computer.
Let us look into what happens when computers compute. The following equation covers most of the types of computation that occur.
digital inputs + processing = digital outputs or modification of digital data
There are various types of variations of this equation. One is simply:
no inputs + processing = digital outputs or modification of digital data
Another variation is the following:
digital inputs + processing + retrieval of other digital inputs = digital outputs or modification of digital data
By digital inputs or digital outputs I mean anything at all that can be represented digitally, by a sequence of binary numbers. Here are some of the things that we know can be represented digitally, and which modern computers do use as digital inputs or digital outputs:
Any set of characters or words
Any text can be digitally represented by means of things such as the ASCII system that allows you to represent particular characters as particular numbers. While we don't normally think of an image as digital, it can be represented digitally as a series of pixels or picture elements. For example, a photograph might consist of 1 million pixels, which each can be represented by a number representing a particular shade of color. So the image can be digitally represented by a million such numbers. A video can also be representing digitally, since the video can be represented as a series of images, each of which can be digitally represented.
But there are some things that we can never hope to produce as digital outputs. The first is real conceptual understanding. By understanding I don't mean “how-to” type understanding, but the high-level conscious understanding of some abstract truth or concept. We can imagine no possible way to produce a digital output that would equal a real conceptual understanding of something.
But, you may ask, doesn't that smart computer Watson already understand something – the game of chess? No, it doesn't. Watson merely can produce a digital output corresponding to a good move to make as the next move in a chess game. Watson has zero conceptual understanding of the game of chess itself, and has zero understanding of the abstract concept of a game. The only way you can understand the abstract concept of a game (or the abstract concept of leisure) is if you have been a human being (or something like a human), and played a game yourself.
A digital output must always boil down to a series of 1's and 0's. Can we imagine a series of 1's and 0's that would equal a real understanding of an abstract concept such as health, matter, life or world peace? No, we cannot.
AI alarmism is based on the idea that future computers will be able to produce conceptual understanding as an output. They won't, because real understanding of abstract concepts is not a possible digital output, and digital computers will only be able to produce digital outputs. Computers or robots lacking conceptual understanding will neither be able to take over the world nor even ably perform any of the more intellectually demanding jobs requiring the repeated application of general intelligence.
But why do computers sometimes seem smart? Because by programming software and putting that into a computer, a computer can act as a repository of human logic. But the logic used by the computer is not coming from the computer, but from some human who programmed the computer. The process of encoding human logic and transferring human logic to a computer is relatively slow and laborious, only allowing the simulation of very limited types of expertise. There seems to be no hope that clever humans will ever be able to create some kind of general intelligence program that thinks and analyzes in the general-purpose way that humans do.
Faced with such reasoning, an AI alarmist may reply with clever reasoning like this:
But we know that the brain produces understanding, and the brain is a material thing. Once we understand the exact material factors involved in how the brain produces understanding, we need merely ramp up such physical processes in a robot or a computer, multiplying such processes many-fold; and then you'll have something that greatly exceeds us in intelligence and understanding.
I deny that we know any such thing as what is stated in the first sentence of this argument. Nature never told us that our thoughts and ideas are coming from our brains. The idea that the understanding of the human mind is produced by the brain is an unproven dogma – something very often asserted, but never proven. Such a dogma is certainly not proven by brain imaging studies, which merely show very unimpressive differences in blood flow to different parts of the brain, typically only 1 or 2 percent (see here for the flaws of brain imaging studies).
Below are eight reasons for doubting that human understanding is merely a product of the brain.
- No one has any real understanding of how neurons or any other brain parts could produce consciousness, ideas or understanding.
- The mammal dissection experiments carried out over many years by Karl Lashley showed surprisingly high mental functionality when large portions of animal brains were removed, including large fractions of the cortex.
- As argued here, the human mind has quite a few fundamental traits that we cannot explain as being caused by natural selection, because they don't provide survival value; and this undermines the prospects of explaining our minds as some material effect.
- Claims that understanding comes from the brain (or more specifically the brain cortex) are in conflict with tests showing very high mental functioning and apparent high understanding in animals such as crows, who have no cortex and tiny brains.
- Human memory is still supremely mysterious, and we have no understanding of how brains could be achieving the 50-year memories that humans demonstrate, or the instantaneous recall of memories that humans have. Despite the dogma that memories are stored in brains, there is no plausible neural explanation as to how an organic system like the brain could be the source of memory storage as long-lasting as humans have, or the source of memory recall as instantaneous as humans have.
All of these things suggest an idea much more logical than the “we are thinking meat” dogma of materialists: the idea that we are thinking souls who happen to be hanging around in bodies. Because this idea is highly viable, we do not at all know that understanding is something that is materially produced by human brains. Not knowing such a thing, we can have no confidence that some “trick of matter producing mind” will ever be uncovered by future scientists.
If you are “thinking meat,” then you might have a grave fear that maybe the secret of a “meat-to-mind” trick might be learned by computer makers, who might be able to amp up such a trick a thousand-fold, to produce robots and computers so smart that they take over all jobs such as yours, or take over the world. But in light of the eight things discussed above, a more logical idea is: there is no such “meat-to-mind” trick for us to ever discover, because the meat in our brains is not producing our minds. In that case, we need not fear very much robots or computers, because they simply will never be able to have any bit of the understanding we have. Computers or robots lacking any real understanding will not be able to perform any of the more intellectually demanding jobs, those that require real conceptual understanding. And such robots and computers will not be able to take over the world, having no actual understanding of our planet or even a thousand simpler things.