Your alternative wording of practical CF is indeed basically what I’m arguing against (although, we could interpret different degrees of the simulation having the “exact” same experience, and I think the arguments here don’t only argue against the strongest versions but also weaker versions, depending on how strong those arguments are).
I’ll explain a bit more why I think practical CF is relevant to CF more generally.
Firstly, functionalist commonly say things like
Computational functionalism: the mind is the software of the brain. (Piccinini)
Which, when I take at face value, is saying that there is actually a program being implemented by the brain that is meaningful to point to (i.e. it’s not just a program in the sense that any physical process could be a program if you simulate it (assuming digital physics etc)). That program lives on a level of abstraction above biophysics.
Secondly, computational functionalism, taken at fact value again, says that all details of the conscious experience should be encoded in the program that creates it. If this isn’t true, then you can’t say that conscious experience is that program because the experience has properties that the program does not.
Putnam advances an opposing functionalist view, on which mental states are functional states. (SEP)
He proposes that mental activity implements a probabilistic automaton and that particular mental states are machine states of the automaton’s central processor. (SEP)
the mind is constituted by the programs stored and executed by the brain (Piccinini)
I can accept the charge that this still is a stronger version of CF that a number of functionalists subscribe to. Which is fine! My plan was to address quite narrow claims at the start of the sequence and move onto broader claims later on.
I’d be curious to hear which of the above steps you think miss the mark on capturing common CF views.
I guess I shouldn’t put words in other people’s mouths, but I think the fact that years-long trains-of-thought cannot be perfectly predicted in practice because of noise is obvious and uninteresting to everyone, I bet including to the computational functionalists you quoted, even if their wording on that was not crystal clear.
There are things that the brain does systematically and robustly by design, things which would be astronomically unlikely to happen by chance. E.g. the fact that I move my lips to emit grammatical English-language sentences rather than random gibberish. Or the fact that humans wanted to go to the moon, and actually did so. Or the fact that I systematically take actions that tend to lead to my children surviving and thriving, as opposed to suffering and dying.
That kind of stuff, which my brain does systematically and robustly, is what makes me me. My memories, goals, hopes and dreams, skills, etc. The fact that I happened to glance towards my scissors at time 582834.3 is not important, but the robust systematic patterns are.
And the reason that my brain does those things systematically and robustly is because the brain is designed to run an algorithm that does those things, for reasons that can be explained by a mathematical analysis of that algorithm. Just as a sorting algorithm systematically sorts numbers for reasons that can be explained by a mathematical analysis of that algorithm.
I don’t think “software versus hardware” is the right frame. I prefer “the brain is a machine that runs a certain algorithm”. Like, what is software-versus-hardware for a mechanical calculator? I dunno. But there are definitely algorithms that the mechanical calculator is implementing.
So we can talk about what is the algorithm that the brain is running, and why does it work? Well, it builds models, and stores them, and queries them, and combines them, and edits them, and there’s a reinforcement learning actor-critic thing, blah blah blah.
Those reasons can still be valid even if there’s some unpredictable noise in the system. Think of a grandfather clock—the second hand will robustly move 60× faster than the minute hand, by design, even if there’s some noise in the pendulum that effects the speed of both. Or think of an algorithm that involves randomness (e.g. MCMC), and hence any given output is unpredictable, but the algorithm still robustly and systematically does stuff that is a priori specifiable and be astronomically unlikely to happen by chance. Or think of the Super Mario 64 source code compiled to different chip architectures that use different size floats (for example). You can play both, and they will both be very recognizably Super Mario 64, but any given exact sequence of button presses will eventually lead to divergent trajectories on the two systems. (This kind of thing is known to happen in tool-assisted speedruns—they’ll get out of sync on different systems, even when it’s “the same game” to all appearances.)
But it’s still reasonable to say that the Super Mario 64 source code is specifying an algorithm, and all the important properties of Super Mario 64 are part of that algorithm, e.g. what does Mario look like, how does he move, what are the levels, etc. It’s just that the core algorithm is not specified at such a level of detail that we can pin down what any given infinite sequence of button presses will do. That depends on unimportant details like floating point rounding.
I think this is compatible with how people use the word “algorithm” in practice. Like, CS people will causally talk about “two different implementations of the MCMC algorithm”, and not just “two different algorithms in the MCMC family of algorithms”.
That said, I guess it’s possible that Putnam and/or Piccinini were describing things in a careless or confused way viz. the role of noise impinging upon the brain. I am not them, and it’s probably not a good use of time to litigate their exact beliefs and wording. ¯\_(ツ)_/¯
Thanks for the comment Steven.
Your alternative wording of practical CF is indeed basically what I’m arguing against (although, we could interpret different degrees of the simulation having the “exact” same experience, and I think the arguments here don’t only argue against the strongest versions but also weaker versions, depending on how strong those arguments are).
I’ll explain a bit more why I think practical CF is relevant to CF more generally.
Firstly, functionalist commonly say things like
Which, when I take at face value, is saying that there is actually a program being implemented by the brain that is meaningful to point to (i.e. it’s not just a program in the sense that any physical process could be a program if you simulate it (assuming digital physics etc)). That program lives on a level of abstraction above biophysics.
Secondly, computational functionalism, taken at fact value again, says that all details of the conscious experience should be encoded in the program that creates it. If this isn’t true, then you can’t say that conscious experience is that program because the experience has properties that the program does not.
I can accept the charge that this still is a stronger version of CF that a number of functionalists subscribe to. Which is fine! My plan was to address quite narrow claims at the start of the sequence and move onto broader claims later on.
I’d be curious to hear which of the above steps you think miss the mark on capturing common CF views.
I guess I shouldn’t put words in other people’s mouths, but I think the fact that years-long trains-of-thought cannot be perfectly predicted in practice because of noise is obvious and uninteresting to everyone, I bet including to the computational functionalists you quoted, even if their wording on that was not crystal clear.
There are things that the brain does systematically and robustly by design, things which would be astronomically unlikely to happen by chance. E.g. the fact that I move my lips to emit grammatical English-language sentences rather than random gibberish. Or the fact that humans wanted to go to the moon, and actually did so. Or the fact that I systematically take actions that tend to lead to my children surviving and thriving, as opposed to suffering and dying.
That kind of stuff, which my brain does systematically and robustly, is what makes me me. My memories, goals, hopes and dreams, skills, etc. The fact that I happened to glance towards my scissors at time 582834.3 is not important, but the robust systematic patterns are.
And the reason that my brain does those things systematically and robustly is because the brain is designed to run an algorithm that does those things, for reasons that can be explained by a mathematical analysis of that algorithm. Just as a sorting algorithm systematically sorts numbers for reasons that can be explained by a mathematical analysis of that algorithm.
I don’t think “software versus hardware” is the right frame. I prefer “the brain is a machine that runs a certain algorithm”. Like, what is software-versus-hardware for a mechanical calculator? I dunno. But there are definitely algorithms that the mechanical calculator is implementing.
So we can talk about what is the algorithm that the brain is running, and why does it work? Well, it builds models, and stores them, and queries them, and combines them, and edits them, and there’s a reinforcement learning actor-critic thing, blah blah blah.
Those reasons can still be valid even if there’s some unpredictable noise in the system. Think of a grandfather clock—the second hand will robustly move 60× faster than the minute hand, by design, even if there’s some noise in the pendulum that effects the speed of both. Or think of an algorithm that involves randomness (e.g. MCMC), and hence any given output is unpredictable, but the algorithm still robustly and systematically does stuff that is a priori specifiable and be astronomically unlikely to happen by chance. Or think of the Super Mario 64 source code compiled to different chip architectures that use different size floats (for example). You can play both, and they will both be very recognizably Super Mario 64, but any given exact sequence of button presses will eventually lead to divergent trajectories on the two systems. (This kind of thing is known to happen in tool-assisted speedruns—they’ll get out of sync on different systems, even when it’s “the same game” to all appearances.)
But it’s still reasonable to say that the Super Mario 64 source code is specifying an algorithm, and all the important properties of Super Mario 64 are part of that algorithm, e.g. what does Mario look like, how does he move, what are the levels, etc. It’s just that the core algorithm is not specified at such a level of detail that we can pin down what any given infinite sequence of button presses will do. That depends on unimportant details like floating point rounding.
I think this is compatible with how people use the word “algorithm” in practice. Like, CS people will causally talk about “two different implementations of the MCMC algorithm”, and not just “two different algorithms in the MCMC family of algorithms”.
That said, I guess it’s possible that Putnam and/or Piccinini were describing things in a careless or confused way viz. the role of noise impinging upon the brain. I am not them, and it’s probably not a good use of time to litigate their exact beliefs and wording. ¯\_(ツ)_/¯