Author, The Physics Devotional: Celebrating the Wisdom and Beauty of Physics and The Mathematics Devotional: Celebrating the Wisdom and Beauty of Mathematics

If we believe that thinking and consciousness are the result of patterns of brain cells and their components, then our thoughts, emotions, and memories could be replicated in moving assemblies of bicycle parts. Of course, the bicycle brains would have to be very big to represent the complexity of our minds. In principle, our minds could be hypostatized in the patterns of slender tree limbs moving in the wind or in the movements of termites.

What would it mean for a “bicycle brain,” or any machine, to think and know something? There are many kinds of knowledge the machine-being could have. This makes discussions of thinking things a challenge. For example, knowledge may be factual, or propositional: A being may know that the First Franco-Dahomean War was a conflict between France and the African Kingdom of Dahomey under King Béhanzin.

Another category of knowledge is procedural: knowing how to accomplish a task such as playing the game of Go, cooking a soufflé, making love, performing a rotary throw in Aikido, shooting a fifteenth-century Wallarmbrust crossbow, or simulating the Miller–Urey experiment to explore the origins of life. However, for us at least, reading about accurately shooting a Wallarmbrust crossbow is not the same as actually being able to accurately shoot the crossbow. This second type of procedural knowing implies being able to perform the act.

Yet another kind of knowledge deals with direct experience. This is the kind of knowledge referred to when someone says, “I know love” or “I know fear.”

Also, consider that humanlike interaction is important for any machine that we would wish to say has humanlike intelligence and thinking. A smart machine is less interesting if its intelligence lies trapped in an unresponsive program, sequestered in a kind of isolated limbo. As we provide our computers with increasingly advanced sensory peripherals and larger databases, it’s likely we will gradually come to think of those entities as intelligent. Certainly within this century, some computers will respond in such a way that anyone interacting with them will consider them conscious and deeply thoughtful.

The entities will exhibit emotions. But more important, over time we’ll merge with these creatures. We’ll share our thoughts and memories with them. We will become one. Our organs may fail and turn to dust, but our Elysian essences will survive. Computers, or computer/human hybrids, will surpass humans in every area, from art to mathematics to music to sheer intellect.

In the future, when our minds merge with artificial agents and also integrate various electronic prostheses, for each of our own real lives we will create multiple simulated lives. Your day job is as a computer programmer for a big company. However, after work you’ll be a knight in shining armor attending lavish medieval banquets and smiling at wandering minstrels. The next night, you’ll be in the Renaissance, living in your home on the southern coast of the Sorrentine Peninsula, enjoying a dinner of plover and pigeon. Perhaps, when we become hybrid entities with our machines, we’ll simulate new realities to rerun historical events with slight changes to observe the results, produce great artworks akin to ballets or plays, solve the problem of the Riemann Hypothesis or baryon asymmetry, predict the future, and escape the present, so as to call all of space-time our home.

Of course, the ways a machine thinks could be quite different from the ways we think. After all, it’s well known that machines don’t see the same way we do, and image-recognition algorithms called deep neural networks sometimes declare, with near 100 percent certainty, that images of random static are depictions of various animals. If such neural networks can be fooled by static, what else will fool thinking machines of the future?