How do computers compare to Humans? – like Chalk and Cheese?
Computers calculate algorithms and formulae to their logical or rational limits. They can compute until the end of time. A computer is limited only by its microchips, the size of its memory and power source.
Humans are not good at computations. A few can, but they are definitely a bit weird. Computers just carry on, like Ravel’s Bolero or a Duracel battery.
When a computer beat World Champions at chess, Jeopardy or any other board game, the race was on. Computers do not have any great insights into how to play these games, rather they compute every possibility that exists for the game, and see which one works out best. The ability of a computer to play a game by the rules (and that is the only way they can play) depends on their bits, chips and algorithms. This is not how Fischer won the World Chess Championship.
Nor is this how the human mind works. Human minds are not good at repetition, and are nowhere near as a persistent as a computer. Like DNA replication, over time we make errors. For the most part these errors are almost always disastrous, but very occasionally, those errors can be heroic.
That computers “Think Rationally” has led to unwarranted superstitions about computers,
That computers will replace humans
That computers are “intelligent” hence the phrase AI – Artificial Intelligence
That computers are a substitute for humans
That humans can be programmed like a computer
That humans are interchangeable as computer chips
That they can be wired together
AI and philosophy have grown together in some very unfortunate ways.
This has led many scientists down many blind alleys, for example David Gelenter in his book The Tides of Mind, writes “with a little imagination the brain becomes a kind of organic computer”. This is a fundamental assumption of computational neuroscience, and it is WRONG.
The brain is not an organic computer. Very few brains are capable even of keeping up with a pocket calculator, let alone an iPad. The vast majority of brains struggle working out who pays for what after a meal that four of them have eaten together in a restaurant. At the very least they need an app on their phone. Yet those very brains, even after a bottle of wine can successfully navigate their way home across London and the suburbs, with no outside assistance. Something which is beyond even the most advanced AI K9 and may be decades before it can. Even driverless cars have to stick to the roads. Faced with an apparently impossible task, biological humans are always going to come out on top.
Humans are not good at any of the things that computers are good at, we are distinctly mediocre at those things computers excel at, like infinite 100% accurate computations, remembering pi to a 1000 digits. And that is why we invented computers, as tools to do the things we can’t.
Those humans who can do a little of what computers can do are for the most part distinctly odd. Autistic is a nice way to describe some of them, but in the case of Bill Gates, “Just Plain Evil” might be more appropriate.
Technology depends upon material objects that behave with 100% predictability. Even though the outcome looks unpredictable, and we presently have no way of predicting the outcome, (see Chaos Theory), and regardless of whether or not you believe “Quantum Computing” is Science Fiction (see Arthur C. Clarke’s 3rd Law : Any sufficiently advanced technology is indistinguishable from magic).
By contrast, there is nothing predictable about the behaviour of biological systems, They too are governed by Chaos Theory, but in addition they can generate new information, that is they are creative and that is well beyond the ability of any inorganic system.
Biology is constantly on the move, and constantly adapting to its environment, constantly expressing itself in different and entirely unpredictable forms. As much as any law the Law of Unintended Consequences governs biology, and no attempt to constrain it within rational physics has yet or will ever succeed. Or as my Grandmother used to say ‘There’s nowt as queer as folk”.
There are good reasons for this, not least described by the Science of Information – yes nowadays we have a Science of Everything.
Could anything but biology behave in a biological manner? No, because it would then be biology. Carbon based life-forms have a flexibility, dependent on the Carbon atom that is not available elsewhere in the periodic table, silicon based life forms might theoretically be possible, but remain the province of Star Trek and Science Fiction.
The Computational View of Human Nature, depends upon neurones acting like binary switches. Neurones do not behave like binary switches, they have a subtly and modulation that an “On/Off” switch, cannot have. Yes both are like fireworks, once fired they have done their thing and the information leading to their firing has now been lost, possibly, maybe – but that is an assumption as far as the neurone at least is concerned.
Neurones are far more than binary switches – they are part of a complex communication system, formed of extremely sophisticated wires, they do far more than switch on and off. They modulate, inhibit, enhance, carry forward, carry round and convey all the subtleties and nuances of the most sophisticated conversations on the planet as well as the brute force of a West India fast bowler. They one way switches, at varying states of readiness, requiring only a light touch to make them fire, or a massive stimulus, depending on the charge on their membrane, increasing and decreasing their sensitivity to any given stimulus that depends upon their surrounding inputs. By contrast, a poverty ridden computer switch is either on or off -either a 0 or a +1
Nagel, Searle and Gelenter dissent from the computational view of the mind, and so they should. The computational view of mind, is fixed in an understanding of the brain that places the neurone centre stage. The neurone is a wire, albeit a highly sophisticated set of wires, but it is fundamentally a wiring network.
The twenty first century question that challenges neuroscience and neuroscientists is – where is information generated that leads to consciousness, leads to creativity to real intelligence (as opposed to the computational ability associated with computers – anything but an intelligence, unless you think working through an algorithm is “Thinking” as opposed to “Working through an algorithm” or several algorithms, or algorithms containing feedback loops, all clever stuff but it doesn’t take a genius to do it.
Gelernter suggests that we may not have the brains that make us capable of understanding consciousness any more than a parrot can understand how to play chess. My personal belief is that in order to understand consciousness, or at least before we stop trying to understand it, we need a more accurate model of the brain. And that is “Neuroscience behind MoodMapping”, an alternative view of the brain, that is consistent with what we know and equally provides us with an alternative framework based on the facts as were familiar with, understood within a different framework.