WordMan, one way to approach the question is:
Do you think those people who think clearly and precisely and thoroughly about the definitions they use can consistently make better choices than they would otherwise? Do you think those people who take the time to learn how other people are defining the words that they use are going to benefit from this method of thought?
That’s one possible practical question that relates to this thread (although there are others).
And I can see people go either way on this. Pretty sure more than one poster has already posited that there is most likely no real practical benefit to working through this sort of philosophical issue. I understand that, and I can respect that. We have compartmentalized minds. We have walls between the things we believe that we know. Those walls are high, and studying one topic does not necessarily mean any beneficial spillovers into other areas.
But I personally can’t help but believe – not based on too terribly much evidence, but nevertheless – that people who can focus on the meat of the issue on this one topic are likely to be able to do the same on other, more practical topics. Now, it could be the case that certain people are just generally better at this skill at a fundamental level, which means they’re good at it regardless of the topic. They didn’t learn that practical skill from this one topic. Maybe they learned it elsewhere, and it just so happens to apply well in a highfalutin philosophical discussion.
But I personally believe it’s possible for a person who is sufficiently curious to make a sort of mental breakthrough about how words like “determinism” are actually defined. This has been a problem in this thread. It’s always a problem in these threads. As Mijin said in post 127:
And this is really the prime issue.
Unlike free will, which seems to have as many different definitions as there are posters who claim to believe in it, causal determinism is actually well defined. There is no room for fuzziness. It is absolutely clear what it is, and how it works, and how to identify a deterministic system from a non-deterministic system when looking at that system from the outside. (It is not possible to recognize a deterministic system from the inside, which is entirely the problem.)
Causal determinism is as well defined as any human concept can possibly get. And it’s a simple definition!
Yet people still get it wrong. More than one person in this thread has made what seem like basic mistakes.
Are there any practical benefit to working through these kinds of philosophical issues to dig through these kinds of errors? Well… maybe. It depends on whether you believe, first, whether people who have made basic mistakes about definitions can admit their obvious errors (and I can cite at least one person who has been dogmatically ignorant for literally years on a very simple question of fact); and second, whether you believe someone who successfully recognizes their basic definitional error in this particular topic will benefit from that revelation with the spillover effect, by making “better” decisions in other “more practical” topics. I would say that the chances of both of those events happening is very small. In all likelihood, there is most probably no benefit to the vast majority of people from these sort of highfalutin discussions.
But still. I think there can be exceptions.
The basic definition of determinism in the sciences is just the chain of “cause and effect”.
Okay, then, we can ask ourselves, what is “cause and effect”? That’s simple, too. It means that the physical system evolves in a fixed way according to basic rules. Think of it like a flow chart. Everyone has seen flow charts. All that determinism means is that there is one arrow that comes out of every box. If you’re in a box, there is only one way that the system can go to get out of that box. That is the essence of a cause and an effect system. At its core, it really is as simple as that.
If you’re in box 1, then the next box that you’re in is 2. And if you’re in box 2, then the next box you’re in is 3. That’s it. That’s determinism. There is a fixed rule about the one place where you can when you’re in each box. Every time you’re in box A, then the next box is B. Every time you’re in box F, then you’re next box is G.
In physics, this basic idea can be expressed mathematically with a continuous function, which is to say: an infinite number of boxes. That sounds complicated. Well hell, it is complicated. But we can still approach an infinite number of boxes from an easier perspective. Take a piece of paper, and draw a curve corresponding to y(t) = t^2. Or even simpler, draw a simple line where y = x.
There are an infinite number of points on that curve, right? Sure. But nevertheless, where the line is going to be in the future is still completely well defined. When the state of the line is at time t=0, there is no ambiguity about which “box” the line will be at two seconds later. If we know where we are at the bottom of the parabola, then we should know where the parabola is going in the “future”. We human beings can create a deterministic mathematical system, and if we’re asked, okay, this system is in Box B two seconds into the run-time, then where will the system be when it goes another six seconds? We look at the equations, we crunch the numbers, and – if the deterministic system is simple enough! – we can calculate the position where the system will be. It’s complicated, yes, but the reasoning with equations is still exactly the same sort of reasoning as from the flow chart. If you know that we’re starting with box D, then we just need to find out where the equations are telling us to go with box E and F and so on.
Follow the clearly defined rules to find the next box. That is determinism. That is all it is.
Now notice what we are not saying here. We are not saying that all deterministic systems are fully predictable. The vast majority of them are not. Let me repeat that, in case it wasn’t clear: we cannot predict the future values for the vast majority of deterministic systems that we could create. Why? Well, just think about a VERY BIG flow chart. We might know that we’re in box C, and we might be looking for box D on this chart, but the chart is so big that box D is somewhere near the center of the Milky Way galaxy. We cannot yet get to that box to read what will happen in box D.
We can tell that this is a deterministic system. We can see box C, and we can see the clear deterministic rule from saying that the next box is thattaway, in that direction. But the flow chart is so big that we simply can’t follow where that line goes. In computational terms, what this means is that if we set up a computer to approximate this deterministic system, our beautiful sun will burn out before the computer could finish its calculations. We wrote a computer program to run this deterministic system. Sure. We can do that. And we know it’s deterministic, because the system is well defined as it’s being programmed into the computer. Determinism is about well defined causal chains. Everything in the system runs according to fixed rules. Nevertheless! We still cannot predict where this system will go because we simply don’t have the computational power to “follow the flow chart”. The math problem is too hard for the computer to run it in less than 10 billion years. The flow chart is, so to speak, too large for us to read the entire thing.
This is why computer metaphors are so common in these discussions. It’s the power of computation that, finally, gave us the key to unlock our understanding of the limits of predicting deterministic systems. Physicists used to believe that if they had the equations to describe the world, then they’d be able to predict… well, pretty much anything.
It was only after the computer era that it fully sank in, on a gut level for the people who work with these kinds of deterministic systems, that the vast majority of these systems are not computable within the human lifetime. Or even within the earth’s lifetime. If we had the processing power, we could predict the future. But we don’t. And then the even more staggering realization: our processing power comes from computers that exist inside this universe. They are, thus, necessarily smaller than the universe as a whole. It’s a necessary result, that even if our universe happens to be deterministic, that any computer inside of the universe cannot run a simulation of the universe that it is in. A computer that is smaller than the world cannot simulate the entire world. Can’t be done. Agents within a deterministic universe must necessarily remain mired in ignorance of what will happen next.
The question is, then, what kinds of deterministic systems can we simulate? Well, only very simple ones right now. But nevertheless, we can learn quite a bit from those simple deterministic systems if we try.
One thing we can do is, for example, create miniature civilizations. Like computer games, but without any player input. It’s a simulation that repeats the same outcome over and over again, every time it’s played. That is a deterministic system.
And an interesting thought experiment is to have multiple programmers. There might be World-Programmers who create the simulated game world, and Agent-Programmers who create the best little robot they can to navigate the game world. The Agent-Programmers might not even know the full details of the world that their poor little agent will be dropped into. So they have to create an agent which has some small chance of survival in a variety of different worlds. They have to create an agent that will react to what it sees in different kinds of worlds.
World+Agent is a deterministic system. Every time the system is run, the same outcome will happen. The agent will make the same choices every time. But nevertheless, we are free to call the agent’s “decisions” by that very name. No other word is appropriate. We know that if the agent were dropped in World2, after all, their decisions would be different.
World+Agent is a deterministic system. It plays out the same way every time it is run. World2+Agent is also a deterministic system. It plays out the same way every time the simulation is run. Yet the agent makes different choices in the different worlds, as a result of experiencing different input. The deterministic system is not the World by itself, and not the Agent by itself, but the combination of the two together. The chain of cause-and-effect can work out very differently, even with an identical “person”.
Yet in this thread, we’ve had the claim that in a deterministic world, there are no “actual” decisions. That just makes no sense. Of course there are decisions. How could there not be decisions? As said earlier in this thread:
There can be a (deterministic agent) trying to to optimize their experience based on limited information, embedded inside a (deterministic) world that follows a strict chain of cause and effect based on fixed rules, but that agent will be clearly making decisions. Given a slightly different (deterministic) world, the agent will make different decisions.
That fits any definition of decision I’ve ever seen… at least when “decision” is also defined in a clear way, as determinism is so defined.
It’s my belief that working through these sorts of hypotheticals can clear up a lot of previously fuzzy thinking about the nature of our definitions. We seem to have as many definitions of free will as we do posters. We seem, also, to have plenty of misconceptions about extremely well defined concepts like causal determinism.
If just one person reads through these sorts of ideas – except written better than in my post here – and has that light-bulb moment, then yeah. I think that person has a chance to reflect more carefully on definitions in other topics, and maybe – on rare occasions – to make better choices based on a clearer understanding of what a choice actually represents in a deterministic world. Our choices matter because our choices are part of the causal chain. We know that we would make very different choices if suddenly embedded in a different causal chain, because we can see the same thing happening on a much smaller scale.