I’ve been on a post-a-day marathon for two weeks now, and I’m seeing this as the penultimate post (for now). Over the course of these, I’ve written a lot about various low-level aspects of computing, truth tables and system state, for instance. And I’ve weighed in on what I think consciousness amounts to.
How we view, interpret, or define, consciousness aside, a major point of debate involves whether machines can have the same “consciousness” properties we do. In particular, what is the role of subjective experience when it comes to us and to machines?
For me it boils down to a couple of key points.
Moving on from system states (and states of the system), today I’d like to fly over the landscape of different systems. In particular, systems that are — or are not — viewed as conscious.
Two views make this especially interesting. The first holds that everything is computing everything and — under computationalism — this includes conscious computations. The second (if I understand it) holds that anything that processes input data into some kind of output is conscious. (I’m not clear if the view also sees an input-output system as a computer.)
So I want to explore what I see as major landmarks in the landscape of systems that… well, about the only thing we can probably all agree on is that they do something.
Over the last three posts I’ve been exploring the idea of system states and how they might connect with computational theories of mind. I’ve used a full-adder logic circuit as a simple stand-in for the brain — the analog flow and logical gating characteristics of the two are very similar.
In particular I’ve explored the idea that the output state of the system doesn’t reflect its inner working, especially with regard to intermediate states of the system as it generates the desired output (and that output can fluctuate until it “settles” to a valid correct value).
Here I plan to wrap up and summarize the system states exploration.
I left off last time talking about intermediate, or transitory, states of a system. The question is, if we only look at the system at certain key points that we think matter, do any intermediate states make a difference?
In a standard digital computer, the answer is a definite no. Even in many kinds of analog computers, transitory states exist for the same reason they do in digital computers (signals flowing through different paths and arriving at the key points at different times). In both cases they are ignored. Only the stable final state matters.
So in the brain, what are the key points? What states matter?
In the last post I talked about software models for a full-adder logic circuit. I broke them into two broad categories: models of an abstraction, and models of a physical instance. Because the post was long, I was able to mention the code implementations only in passing (but there are links).
I want to talk a little more about those two categories, especially the latter, and in particular an implementation that bridges between the categories. It’s here that ideas about simulating the brain or mind become important. Most approaches involve some kind of simulation.
One type of simulation involves the states of a system.
Imagine the watershed for a river. Every drop of water that falls in that area, if it doesn’t evaporate or sink into the ground, eventually makes its way, through creeks, streams, and rivers, to the lake or ocean that is the shed’s final destination. The visual image is somewhat like the veins in a leaf. Or the branches of the leaf’s tree.
In all cases, there is a natural flow through channels sculpted over time by physical forces. Water always flows downhill, and it erodes what it flows past, so gravity, time, and the resistance of rock and dirt, sculpt the watershed.
The question is whether the water “computes.”
Previously, I wrote that I’m skeptical of interpretation as an analytic tool. In physical reality, generally speaking, I think there is a single correct interpretation (more of a true account than an interpretation). Every other interpretation is a fiction, usually made obvious by complexity and entropy.
I recently encountered an argument for interpretation that involved the truth table for the boolean logical AND being seen — if one inverts the interpretation of all the values — as the truth table for the logical OR.
It turns out to be a tautology. A logical AND mirrors a logical OR.
My illusion of free will decided the month of May must be made for Mind (and maybe a dash of Mandelbrot). Lately, online discussions about consciousness have me pondering it again. I never posted on topics such as Chinese Rooms or Philosophical Zombies, largely because sensible arguments exist both ways, and I never decided exactly where I fell in the argument space.
It’s not that I’ve decided on the topics so much as I’ve decided to write about them (and other topics). I’ve found that writing about a topic does a lot to clarify my mind about it. (Trying to teach a topic does that even more.)
I’ll start today with some personal observations and points of view.