We are all accustomed to using machines that are stronger and faster than people are. But before the first computers appeared, no one could see how any machine could do more than a very few different things. This must be why Descartes insisted that no machine could be as resourceful as any person can be.
“For while reason is a universal instrument which can apply to every situation, a machine’s parts need a particular arrangement for each particular action; therefore it is impossible for a single machine to have enough diversity to enable it to act in all the events of life in the same way as our reason causes us to act.”[149]
Similarly in earlier times there appeared to be an unbridgeable gap between the capacities of humans and other animals. Thus, in The Descent of Man, Darwin observes that,” Many authors have insisted that man is divided by an insuperable barrier from all the lower animals in his mental faculties.” However, he then contends that this difference may be just “one of degree and not of kind.”
Charles Darwin: “It has, I think, now been shewn that man and the higher animals, especially the primates … all have the same senses, intuitions, and sensations, — similar passions, affections, and emotions, even the more complex ones, such as jealousy, suspicion, emulation, gratitude, and magnanimity; … they possess the same faculties of imitation, attention, deliberation, choice, memory, imagination, the association of ideas, and reason, though in very different degrees.”[150]
Then Darwin observes that “the individuals of each species may graduate in intellect from absolute imbecility to high excellence,” and argues that even the highest forms of human thought could have developed from such variations—because he sees no particular point at which that would meet an intractable obstacle.
“That such evolution is at least possible, ought not to be denied, for we daily see these faculties developing in every infant; and we may trace a perfect gradation from the mind of an utter idiot ... to the mind of a Newton.”
Many people still find it hard to envision how there could have been transitional steps from animal to human minds. In the past, that view was excusable—because few thinkers had ever suspected that only a few small structural changes could vastly increase what machines can achieve. However, in 1936, the mathematician Alan Turing showed how to make a “universal” machine that can read the descriptions of other machines—and then, by switching among those descriptions, it can do all the things that those machines can do.[151]
All modern computers use this trick, so today we can use the same machine to arrange our appointments, edit our texts, or help us send messages to our friends. Furthermore, once we store those descriptions inside the machine, then those programs can change themselves—so that the machine can keep extending its own abilities. This showed that the limits which Descartes observed were not inherent in machines, but resulted from our old-fashioned ways to build or to program them. For each machine that we built in the past had only way to accomplish each particular task—whereas each person, when stuck, has alternatives.
Nevertheless, many thinkers still maintain that machines can never achieve such feats as composing great theories or symphonies. Instead, they prefer to attribute such feats to inexplicable ‘talents’ or ‘gifts.’ However, those abilities will seem less mysterious, once we see how our resourcefulness could result from having such diverse ways to think. Indeed, each previous chapter of this book discussed some way in which our minds provide such alternatives:
§1. We are born with many kinds of resources.
§2. We learn from our Imprimers and friends.
§3. We also learn what we ought not to do.
§4. We can reflect upon what we are thinking about.
§5. We can predict the effects of imagined actions.
§6. We use huge stores of commonsense knowledge.
§7. We can switch among different Ways to Think.
This chapter discusses yet additional features that make human minds so versatile.
§82. We can see things from many points of view.
§83. We have special ways to rapidly switch among these.
§84. We have developed special ways to learn very quickly. Move the
§85. We have efficient ways to recognize which knowledge is relevant.
§86. We can keep extending the range of our ways to think.
§87. We have many different ways to represent things.
At the start of this book, we noted that it is hard to conceive of ourselves as machines, because no machine that we’ve seen in the past seemed to understand the meanings of things, but could only react to the simple commands that we designed them to execute. Some philosophers argue that this must be because machines are merely material things, whereas meanings exist in the world of ideas, which lies outside the realm of physical things. However, Chapter §1 suggested that we, ourselves have constrained our machines by defining those meanings so narrowly that we fail to express their diversity:
If you ‘understand’ something in only one way then you scarcely understand it at all—because when something goes wrong, you’ll have no place to go. But if you represent something in several ways, then when one method fails, you can switch to another. That way, you can turn things around in your mind to see them from different points of view —until you find one that works for you!
To show how this kind of diversity makes human thinking so versatile, we’ll start with examples of the multiple ways we use to estimate our distance from things.
§8-2. Estimating Distances
When you’re thirsty, you look for something to drink—and if you notice a nearby cup, you can simply reach out to pick it up—but if that cup lies further away, then you will have to move over to it. But how do you know which things you can reach? A naïve person sees this as no problem at all because, “You just look at a thing and you see where it is.” But when Joan detected that oncoming car in §4-2 or grasped that book in §6-1, how did she know its distance from her?
In primeval times we had to guess how near our predators were to us; today we only need to judge if we have enough time to cross the street—but, still, our lives depend on this. Fortunately, we each have many different ways to estimate the distance to things.
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Turing described these “universal” machines before any modern computers were built. For more details about how these work, see http://mathworld.wolfram.com/UniversalTuringMachine.html.