A central aspect of the transhumanist project should be to imagine what we are trying to become or create. What kind of minds can there be? It may be that there is an abundance of possible minds we cannot even imagine from our current frame of reference, but on the flipside, some of the minds that we can imagine may in fact turn out to be forbidden by the laws of nature. We have only one true data point on the graph of mindspace – humankind. The psychological differences we observe between humans may be a useful guide in imagining other kinds of minds. Philosophy of mind, cognitive science, and computational complexity theory may help too. On a past post that went over some basics of the nascent field of Friendly AI – building positive AIs – a commenter, Raphael, said this:

I agree that most people anthropomorphize and that the Asimov’s Laws are risible (if they worked, then Asimov wouldn’t have had any drama to write about). It also seems highly plausible that the space of possible intelligences is much larger than the space of human intelligences (e.g. from low-IQ to Newton).

However, I’m not sure how much we can say beyond that. For instance, given that we don’t know what intelligence is (in any detailed way), it is hard to say exactly how diverse the space of intelligent minds is. I will substantiate this point by analogy. Without knowledge of computational complexity theory, it is easy to assume that the space of conceivable algorithms is the same as the space of physically realizable algorithms. In other words, that all algorithms we can devise are such that we could (with huge amounts of computing power) actually implement those algorithms. However, we now know that this is completely wrong. There are simple problems which can only be solved via algorithms that cannot be implemented in our universe.

The question is interesting. I have strong intuitions that a very large diversity of minds is possible, and can name specific qualities of different possible types of minds, but I lack the empirically verified theory that would be necessary to say that such minds are possible with certainty. As an effort to explore this space, I’m going to list some different types of minds I can imagine and invite people to criticize the plausibility of their existence. Are some mind variants more plausible than others? Is there a criteria for determining this other than their foreignness from a human-centered psychological perspective? That’s what we should try to find out.

Some relevant dimensions along which we can imagine minds that vary widely are:

1) Clock speed. Functionalism tells us that minds are defined as the interactions of the hardware on which they are instantiated. When the hardware is slow, the mind is slow. When the hardware is fast, the mind is fast. Humans have about 10^11 neurons firing at about 200 times per second (200 Hz). It should then follow that arbitrary changes to hardware performance in any given brain results in a corresponding change in speed of thinking, perceiving, experiencing, planning, creativity, and communication. In this model, minds with 10^11 neurons that run at 0.2 Hz could be expected to think a thousand times slower than human beings, whereas minds with the same number of neurons running at 200 KHz could be expected to think a thousand times faster. Invalidating this proposal would require that minds with slower hardware, do not, in fact, operate slower than human brains, or that minds with faster hardware do not, in fact, operate faster than human brains.

2) Distribution. Human minds are contained up in a 3-pound hunk of meat shielded by a calcite cranium. If functionalism – that is, the idea that minds are defined as the physical activity in the brain – holds, then a variety of distributed or condensed mind-forms should be possible, as long as there is low latency and sufficient bandwidth between cognitive nodes. Electronic signals travel at the speed of light, meaning that an artificial intelligence should be able to exist as a program distributed across computers on opposite sides of the planet and still function effectively. At the same time, highly miniaturized computing machinery, such as nanocomputers, should, in theory, be able to hold human-equivalent minds with a volume and weight much smaller than our current 1450cc brains. For size scalability among brains to be impossible would require that functionalism is false, which, according to anyone that studies the brain, looks quite unlikely.

3) Communication. Imagine the evolution of homonid communication from the standpoint of natural selection if it were a intelligent actor: “If I lower the larynx a bit here, give better control of chest muscles to the neocortex there, and expand the auditory cortex like so, then we might have something.” Language: complex information transfer accompanied by high-fidelity memory storage of the data, is not something that comes naturally to evolution-designed biological life. Electronic systems offer the appeal of the discrete state and the regularity of distinct file types. They can transfer images, text, sound, CAD files, even virtual landscapes at speeds limited mainly by the bandwidth of the data pipe. We can imagine minds that store complex skills, observations, and analyses as independent data files – kungfu.mi, for instance. For nonbiological minds, we should expect the possibilities of communication to be much greater than among biological humans. This dimension of variation falls out automatically when you go outside the default human I/O.

4) Reprogrammability. Clearly the human mind is trainable to a certain extent and even partially deliberately reprogrammable. However, we have very limited control over the overall anatomical structure or chemical makeup of our brains. Our limbic system places games with our “higher faculties”. We have little control over the structure of neurons, the way our brains process visual or auditory data, or our fundamental instincts. A mind with access to its own source code could modify any aspect of itself it thought fit. It could observe the fine-grained structure of other such minds and take inspiration from their cognitive structures in the way that a modern painter might take inspiration from Renaissance artists. It could even build new sensory modalities designed for specialized purposes, like simultaneously visualizing the dynamics of thousands of moving parts in a complex engine, being able to tell one from another in the same way we can tell two faces apart.

5) Intelligence. The vast intelligence difference between primitive microbes and today’s humans give us a kind of clue at the type of variation that is possible. Rather than assume that human beings are around the limits of intelligent thought, or can “visualize anything if we put our minds to it”, we should assume we are typical – somewhere in the middle between microbes and the ultimate limits of intelligence – if not on the far low end of the spectrum. The actual quantity of processing power we have at our disposal is certainly one limiting factor on our intelligence, but perhaps even more important is the particular arrangement of our brains. Intelligence is a relatively recent evolutionary innovation, and our brains as a whole, most of which is based off of preexisting morphological complexity, is not specifically designed to accommodate or nurture general intelligence. We should expect that a mind designed deliberately to implement intelligence could go far beyond our ability to reason, imagine, plan, create, and experience reality.

6) “Morality”. The baggage-free version: “goal orientation”. An AI could begin with whatever goal orientation we give it. There are practically no limits. We could make AIs that are our obedient slaves and love it. Humans dislike being enslaved because being so tends to result in fewer reproductive opportunities, thus evolution selected against it. This evolutionary design would not be built into AIs. Synthetic minds start off with nothing: a blank slate. You could make a humanoid robot whose goal is to eternally hop in a circle while rubbing its stomach and patting its head, and it could achieve that goal, as long as it had a reliable power supply and spare parts. The concept of “self” in the sense of “I exist” is not the same thing as the concept of self as humans know it: i.e., “I’m a self-interested moral agent with certain inalienable rights which I continuously have to reemphasize because my evolutionary and cultural history consists of others constantly challenging those rights, and I am programmed by evolution to be concerned about them”. In an AI, all that self-centered goal complexity is simply not there. A certain degree of goal complexity is necessary to produce intelligence at all, but it’s quite minimal, and the room for variation in the ‘footnotes’ is immense. If we want AIs to do things we consider “normal”, like caring about others, we’ll have to program it in, and instill a desire to build upon those goals in ways that keep the spirit of the original intentions. Otherwise, there’s no telling what we’ll end up with.

Can you imagine other dimensions of variation? Can you think of any regions of the above possibilities which might be ruled out by physical law? If the potential space of possible moralities in particular is so large, do we have an ethical obligation to craft synthetic minds with human-empathic goal orientations?