via NPR
Look around you. What do you see?
Other people going about their business? Rooms with tables and chairs? Nature with its sky, grass and trees?
All that stuff, it's really there, right? Even if you were to disappear right now — poof! — the rest of the world would still exist in all forms you're seeing now, right?
Or would it?
This kind of metaphysical question is something you'd expect in a good philosophy class — or maybe even a discussion of quantum physics. But most of us wouldn't expect an argument denying the reality of the objective world to come out of evolutionary biology. After all, doesn't evolution tell us we've been tuned to reality by billions of years of natural selection? It makes sense that creatures that can't tell a poisonous snake from a stick shouldn't last long and, therefore, shouldn't pass their genes on to the next generation.
That is certainly how the standard argument goes. But Donald Hoffman, a cognitive scientist, isn't buying it.
For decades, Hoffman, a professor at the University of California, Irvine, has been studying the links between evolution, perception and intelligence (both natural and machine). Based on that body of work, he thinks we've been missing something fundamental when it comes to fundamental reality.
Fundamentally, Hoffman argues, evolution and reality (the objective kind) have almost nothing to do with each other.
Hoffman's been making a lot of news in recent months with these claims. His March 2015 TED talk went viral, gaining more than 2 million views. After a friend sent me the video, I was keen to learn more. I called Dr. Hoffman, and he graciously set aside some time for us to talk. What followed was a delightful conversation with a guy who does, indeed, have a big radical idea. At the same time, Hoffman doesn't come off as someone with an ax to grind. He seems genuinely open and truly curious. At his core, Hoffman says, he's a scientist with a theory that must either live or die by data.
So, what exactly is Hoffman's big radical idea? He begins with a precisely formulated theorem:
"Given an arbitrary world and arbitrary fitness functions, an organism that sees reality as it is will never be more fit than an organism of equal complexity that sees none of reality but that is just tuned to fitness."
So let's unpack Hoffman's theorem for a moment. To paraphrase the website Understanding Evolution, "fitness" is used to describe how good a particular organism is at getting its offspring into the next generation relative to the other organisms around it. When people study evolution using mathematics or computers, they imagine there are compact ways of describing what makes an organism fit for a particular environment. That's what they mean by "fitness functions."
So imagine you have two kinds of creatures living in an environment. The first is tuned to respond directly to objective reality — the actual independent reality out there. The other creature has behavior only tuned to its, and the environment's, fitness function. The second creature couldn't care less about what's really going on in reality. What Hoffman's theorem says is the fitness-tuned critter will — almost always — win the evolution game.
To see how this works, consider an example Hoffman describes in an interview with Quanta Magazine. He begins by imagining a resource like water whose real-world quantity has been objectively ordered — very little water, medium amounts of water, lots of water. According to Hoffman, most fitness functions won't be direct responses to something like this ordering. Instead they will be like bell curves. Too little water is bad (death by desiccation), but so is too much water (death by drowning). That means evolution would tune the organism's behavior so that too little and too much water would both be bad and both generate the same kind of response (perception). Only the moderate amount of water would generate a different response. As Hoffman puts it:
" ... an organism tuned to fitness might see small and large quantities of some resource as, say, red, to indicate low fitness, whereas they might see intermediate quantities as green, to indicate high fitness. Its perceptions will be tuned to fitness, but not to truth. It won't see any distinction between small and large — it only sees red — even though such a distinction exists in reality."
To test this idea, Hoffman and collaborators have run evolutionary simulations with different kinds of fitness functions — some of those tuned to reality and some having nothing to do with reality. The non-reality functions almost always win. For Hoffman, the consequences of these studies are profound. As he told me:
"We assume the 'predicates' of perceptions — space, time, physical objects, shapes — are the right ones to describe physical reality. And this theorem says that [such] predicates are [the wrong ones] almost surely."
In other words, evolution couldn't care less if you perceive objective reality. It only wants you to have sex successfully. As a consequence, your apprehension of the world is tuned to whatever allows that to happen. Thus, your perceptions at the root level have nothing to do with some fundamental physics upon which the fundamental nature of objective independent reality is constructed.
Hoffman then builds something even more radical out of his broken link between objective reality and evolution. He calls it conscious realism, and it's based on the premise that "circuits of conscious agents" are what end up defining experienced reality. While there clearly is a world separate from us, Hoffman says, evolution does not give us access to that. Instead, he claims, it's our interactions as conscious agents that give shape to the reality we experience. "I can take separate observers," he told Quanta Magazine, "put them together and create new observers, and keep doing this ad infinitum. It's conscious agents all the way down."
This is a pretty head-spinning stuff. Our perceived reality has nothing to do with the world in and of itself? That's the kind of thing that's bound to piss off a whole lot of people in a whole lot of fields. I asked Hoffman about the reaction to his work. "All over the map," he replied. "I'm either a genius or an absolute stupid idiot. The emotions are pretty strong."
Indeed, criticisms both closely reasoned and otherwise can be found from a variety of sources. For myself, I find the logic in Hoffman's ideas both exciting and potentially appealing because of other philosophical biases I carry around in my head. Also, it's clear from the body of his work that Hoffman has been seriously attacking the problem from a range of angles for a while.
But the ideas are also so radical that I'm inclined to think they're wrong (as most ideas this radical tend to be). It's gonna take a lot of proof to tip the scales in my (and most others') view.
But that's as it should be. And what I really like about Donald Hoffman is his cheerful willingness to let the fur fly.
Let the games (evolutionary and otherwise) go on!
Showing posts with label donald hoffman. Show all posts
Showing posts with label donald hoffman. Show all posts
Sunday, October 2, 2016
Tuesday, September 20, 2016
The Evolutionary Argument Against Reality
via Quanta:
As we go about our daily lives, we tend to assume that our perceptions — sights, sounds, textures, tastes — are an accurate portrayal of the real world. Sure, when we stop and think about it — or when we find ourselves fooled by a perceptual illusion — we realize with a jolt that what we perceive is never the world directly, but rather our brain’s best guess at what that world is like, a kind of internal simulation of an external reality. Still, we bank on the fact that our simulation is a reasonably decent one. If it wasn’t, wouldn’t evolution have weeded us out by now? The true reality might be forever beyond our reach, but surely our senses give us at least an inkling of what it’s really like.
Not so, says Donald D. Hoffman, a professor of cognitive science at the University of California, Irvine. Hoffman has spent the past three decades studying perception, artificial intelligence, evolutionary game theory and the brain, and his conclusion is a dramatic one: The world presented to us by our perceptions is nothing like reality. What’s more, he says, we have evolution itself to thank for this magnificent illusion, as it maximizes evolutionary fitness by driving truth to extinction.
Getting at questions about the nature of reality, and disentangling the observer from the observed, is an endeavor that straddles the boundaries of neuroscience and fundamental physics. On one side you’ll find researchers scratching their chins raw trying to understand how a three-pound lump of gray matter obeying nothing more than the ordinary laws of physics can give rise to first-person conscious experience. This is the aptly named “hard problem.”
On the other side are quantum physicists, marveling at the strange fact that quantum systems don’t seem to be definite objects localized in space until we come along to observe them — whether we are conscious humans or inanimate measuring devices. Experiment after experiment has shown — defying common sense — that if we assume that the particles that make up ordinary objects have an objective, observer-independent existence, we get the wrong answers. The central lesson of quantum physics is clear: There are no public objects sitting out there in some preexisting space. As the physicist John Wheeler put it, “Useful as it is under ordinary circumstances to say that the world exists ‘out there’ independent of us, that view can no longer be upheld.”
So while neuroscientists struggle to understand how there can be such a thing as a first-person reality, quantum physicists have to grapple with the mystery of how there can be anything but a first-person reality. In short, all roads lead back to the observer. And that’s where you can find Hoffman — straddling the boundaries, attempting a mathematical model of the observer, trying to get at the reality behind the illusion. Quanta Magazine caught up with him to find out more. An edited and condensed version of the conversation follows.
QUANTA MAGAZINE: People often use Darwinian evolution as an argument that our perceptions accurately reflect reality. They say, “Obviously we must be latching onto reality in some way because otherwise we would have been wiped out a long time ago. If I think I’m seeing a palm tree but it’s really a tiger, I’m in trouble.”
DONALD HOFFMAN: Right. The classic argument is that those of our ancestors who saw more accurately had a competitive advantage over those who saw less accurately and thus were more likely to pass on their genes that coded for those more accurate perceptions, so after thousands of generations we can be quite confident that we’re the offspring of those who saw accurately, and so we see accurately. That sounds very plausible. But I think it is utterly false. It misunderstands the fundamental fact about evolution, which is that it’s about fitness functions — mathematical functions that describe how well a given strategy achieves the goals of survival and reproduction. The mathematical physicist Chetan Prakash proved a theorem that I devised that says: According to evolution by natural selection, an organism that sees reality as it is will never be more fit than an organism of equal complexity that sees none of reality but is just tuned to fitness. Never.
You’ve done computer simulations to show this. Can you give an example?
Suppose in reality there’s a resource, like water, and you can quantify how much of it there is in an objective order — very little water, medium amount of water, a lot of water. Now suppose your fitness function is linear, so a little water gives you a little fitness, medium water gives you medium fitness, and lots of water gives you lots of fitness — in that case, the organism that sees the truth about the water in the world can win, but only because the fitness function happens to align with the true structure in reality. Generically, in the real world, that will never be the case. Something much more natural is a bell curve — say, too little water you die of thirst, but too much water you drown, and only somewhere in between is good for survival. Now the fitness function doesn’t match the structure in the real world. And that’s enough to send truth to extinction. For example, an organism tuned to fitness might see small and large quantities of some resource as, say, red, to indicate low fitness, whereas they might see intermediate quantities as green, to indicate high fitness. Its perceptions will be tuned to fitness, but not to truth. It won’t see any distinction between small and large — it only sees red — even though such a distinction exists in reality.
But how can seeing a false reality be beneficial to an organism’s survival?
There’s a metaphor that’s only been available to us in the past 30 or 40 years, and that’s the desktop interface. Suppose there’s a blue rectangular icon on the lower right corner of your computer’s desktop — does that mean that the file itself is blue and rectangular and lives in the lower right corner of your computer? Of course not. But those are the only things that can be asserted about anything on the desktop — it has color, position and shape. Those are the only categories available to you, and yet none of them are true about the file itself or anything in the computer. They couldn’t possibly be true. That’s an interesting thing. You could not form a true description of the innards of the computer if your entire view of reality was confined to the desktop. And yet the desktop is useful. That blue rectangular icon guides my behavior, and it hides a complex reality that I don’t need to know. That’s the key idea. Evolution has shaped us with perceptions that allow us to survive. They guide adaptive behaviors. But part of that involves hiding from us the stuff we don’t need to know. And that’s pretty much all of reality, whatever reality might be. If you had to spend all that time figuring it out, the tiger would eat you.
So everything we see is one big illusion?
We’ve been shaped to have perceptions that keep us alive, so we have to take them seriously. If I see something that I think of as a snake, I don’t pick it up. If I see a train, I don’t step in front of it. I’ve evolved these symbols to keep me alive, so I have to take them seriously. But it’s a logical flaw to think that if we have to take it seriously, we also have to take it literally.
If snakes aren’t snakes and trains aren’t trains, what are they?
Snakes and trains, like the particles of physics, have no objective, observer-independent features. The snake I see is a description created by my sensory system to inform me of the fitness consequences of my actions. Evolution shapes acceptable solutions, not optimal ones. A snake is an acceptable solution to the problem of telling me how to act in a situation. My snakes and trains are my mental representations; your snakes and trains are your mental representations.
How did you first become interested in these ideas?
As a teenager, I was very interested in the question “Are we machines?” My reading of the science suggested that we are. But my dad was a minister, and at church they were saying we’re not. So I decided I needed to figure it out for myself. It’s sort of an important personal question — if I’m a machine, I would like to find that out! And if I’m not, I’d like to know, what is that special magic beyond the machine? So eventually in the 1980s I went to the artificial intelligence lab at MIT and worked on machine perception. The field of vision research was enjoying a newfound success in developing mathematical models for specific visual abilities. I noticed that they seemed to share a common mathematical structure, so I thought it might be possible to write down a formal structure for observation that encompassed all of them, perhaps all possible modes of observation. I was inspired in part by Alan Turing. When he invented the Turing machine, he was trying to come up with a notion of computation, and instead of putting bells and whistles on it, he said, Let’s get the simplest, most pared down mathematical description that could possibly work. And that simple formalism is the foundation for the science of computation. So I wondered, could I provide a similarly simple formal foundation for the science of observation?
A mathematical model of consciousness.
That’s right. My intuition was, there are conscious experiences. I have pains, tastes, smells, all my sensory experiences, moods, emotions and so forth. So I’m just going to say: One part of this consciousness structure is a set of all possible experiences. When I’m having an experience, based on that experience I may want to change what I’m doing. So I need to have a collection of possible actions I can take and a decision strategy that, given my experiences, allows me to change how I’m acting. That’s the basic idea of the whole thing. I have a space X of experiences, a space G of actions, and an algorithm D that lets me choose a new action given my experiences. Then I posited a W for a world, which is also a probability space. Somehow the world affects my perceptions, so there’s a perception map P from the world to my experiences, and when I act, I change the world, so there’s a map A from the space of actions to the world. That’s the entire structure. Six elements. The claim is: This is the structure of consciousness. I put that out there so people have something to shoot at.
But if there’s a W, are you saying there is an external world?
Here’s the striking thing about that. I can pull the W out of the model and stick a conscious agent in its place and get a circuit of conscious agents. In fact, you can have whole networks of arbitrary complexity. And that’s the world.
The world is just other conscious agents?
I call it conscious realism: Objective reality is just conscious agents, just points of view. Interestingly, I can take two conscious agents and have them interact, and the mathematical structure of that interaction also satisfies the definition of a conscious agent. This mathematics is telling me something. I can take two minds, and they can generate a new, unified single mind. Here’s a concrete example. We have two hemispheres in our brain. But when you do a split-brain operation, a complete transection of the corpus callosum, you get clear evidence of two separate consciousnesses. Before that slicing happened, it seemed there was a single unified consciousness. So it’s not implausible that there is a single conscious agent. And yet it’s also the case that there are two conscious agents there, and you can see that when they’re split. I didn’t expect that, the mathematics forced me to recognize this. It suggests that I can take separate observers, put them together and create new observers, and keep doing this ad infinitum. It’s conscious agents all the way down.
If it’s conscious agents all the way down, all first-person points of view, what happens to science? Science has always been a third-person description of the world.
The idea that what we’re doing is measuring publicly accessible objects, the idea that objectivity results from the fact that you and I can measure the same object in the exact same situation and get the same results — it’s very clear from quantum mechanics that that idea has to go. Physics tells us that there are no public physical objects. So what’s going on? Here’s how I think about it. I can talk to you about my headache and believe that I am communicating effectively with you, because you’ve had your own headaches. The same thing is true as apples and the moon and the sun and the universe. Just like you have your own headache, you have your own moon. But I assume it’s relevantly similar to mine. That’s an assumption that could be false, but that’s the source of my communication, and that’s the best we can do in terms of public physical objects and objective science.
It doesn’t seem like many people in neuroscience or philosophy of mind are thinking about fundamental physics. Do you think that’s been a stumbling block for those trying to understand consciousness?
I think it has been. Not only are they ignoring the progress in fundamental physics, they are often explicit about it. They’ll say openly that quantum physics is not relevant to the aspects of brain function that are causally involved in consciousness. They are certain that it’s got to be classical properties of neural activity, which exist independent of any observers — spiking rates, connection strengths at synapses, perhaps dynamical properties as well. These are all very classical notions under Newtonian physics, where time is absolute and objects exist absolutely. And then [neuroscientists] are mystified as to why they don’t make progress. They don’t avail themselves of the incredible insights and breakthroughs that physics has made. Those insights are out there for us to use, and yet my field says, “We’ll stick with Newton, thank you. We’ll stay 300 years behind in our physics.”
I suspect they’re reacting to things like Roger Penrose and Stuart Hameroff’s model, where you still have a physical brain, it’s still sitting in space, but supposedly it’s performing some quantum feat. In contrast, you’re saying, “Look, quantum mechanics is telling us that we have to question the very notions of ‘physical things’ sitting in ‘space.’”
I think that’s absolutely true. The neuroscientists are saying, “We don’t need to invoke those kind of quantum processes, we don’t need quantum wave functions collapsing inside neurons, we can just use classical physics to describe processes in the brain.” I’m emphasizing the larger lesson of quantum mechanics: Neurons, brains, space … these are just symbols we use, they’re not real. It’s not that there’s a classical brain that does some quantum magic. It’s that there’s no brain! Quantum mechanics says that classical objects — including brains — don’t exist. So this is a far more radical claim about the nature of reality and does not involve the brain pulling off some tricky quantum computation. So even Penrose hasn’t taken it far enough. But most of us, you know, we’re born realists. We’re born physicalists. This is a really, really hard one to let go of.
To return to the question you started with as a teenager, are we machines?
The formal theory of conscious agents I’ve been developing is computationally universal — in that sense, it’s a machine theory. And it’s because the theory is computationally universal that I can get all of cognitive science and neural networks back out of it. Nevertheless, for now I don’t think we are machines — in part because I distinguish between the mathematical representation and the thing being represented. As a conscious realist, I am postulating conscious experiences as ontological primitives, the most basic ingredients of the world. I’m claiming that experiences are the real coin of the realm. The experiences of everyday life — my real feeling of a headache, my real taste of chocolate — that really is the ultimate nature of reality.
As we go about our daily lives, we tend to assume that our perceptions — sights, sounds, textures, tastes — are an accurate portrayal of the real world. Sure, when we stop and think about it — or when we find ourselves fooled by a perceptual illusion — we realize with a jolt that what we perceive is never the world directly, but rather our brain’s best guess at what that world is like, a kind of internal simulation of an external reality. Still, we bank on the fact that our simulation is a reasonably decent one. If it wasn’t, wouldn’t evolution have weeded us out by now? The true reality might be forever beyond our reach, but surely our senses give us at least an inkling of what it’s really like.
Not so, says Donald D. Hoffman, a professor of cognitive science at the University of California, Irvine. Hoffman has spent the past three decades studying perception, artificial intelligence, evolutionary game theory and the brain, and his conclusion is a dramatic one: The world presented to us by our perceptions is nothing like reality. What’s more, he says, we have evolution itself to thank for this magnificent illusion, as it maximizes evolutionary fitness by driving truth to extinction.
Getting at questions about the nature of reality, and disentangling the observer from the observed, is an endeavor that straddles the boundaries of neuroscience and fundamental physics. On one side you’ll find researchers scratching their chins raw trying to understand how a three-pound lump of gray matter obeying nothing more than the ordinary laws of physics can give rise to first-person conscious experience. This is the aptly named “hard problem.”
On the other side are quantum physicists, marveling at the strange fact that quantum systems don’t seem to be definite objects localized in space until we come along to observe them — whether we are conscious humans or inanimate measuring devices. Experiment after experiment has shown — defying common sense — that if we assume that the particles that make up ordinary objects have an objective, observer-independent existence, we get the wrong answers. The central lesson of quantum physics is clear: There are no public objects sitting out there in some preexisting space. As the physicist John Wheeler put it, “Useful as it is under ordinary circumstances to say that the world exists ‘out there’ independent of us, that view can no longer be upheld.”
So while neuroscientists struggle to understand how there can be such a thing as a first-person reality, quantum physicists have to grapple with the mystery of how there can be anything but a first-person reality. In short, all roads lead back to the observer. And that’s where you can find Hoffman — straddling the boundaries, attempting a mathematical model of the observer, trying to get at the reality behind the illusion. Quanta Magazine caught up with him to find out more. An edited and condensed version of the conversation follows.
QUANTA MAGAZINE: People often use Darwinian evolution as an argument that our perceptions accurately reflect reality. They say, “Obviously we must be latching onto reality in some way because otherwise we would have been wiped out a long time ago. If I think I’m seeing a palm tree but it’s really a tiger, I’m in trouble.”
DONALD HOFFMAN: Right. The classic argument is that those of our ancestors who saw more accurately had a competitive advantage over those who saw less accurately and thus were more likely to pass on their genes that coded for those more accurate perceptions, so after thousands of generations we can be quite confident that we’re the offspring of those who saw accurately, and so we see accurately. That sounds very plausible. But I think it is utterly false. It misunderstands the fundamental fact about evolution, which is that it’s about fitness functions — mathematical functions that describe how well a given strategy achieves the goals of survival and reproduction. The mathematical physicist Chetan Prakash proved a theorem that I devised that says: According to evolution by natural selection, an organism that sees reality as it is will never be more fit than an organism of equal complexity that sees none of reality but is just tuned to fitness. Never.
You’ve done computer simulations to show this. Can you give an example?
Suppose in reality there’s a resource, like water, and you can quantify how much of it there is in an objective order — very little water, medium amount of water, a lot of water. Now suppose your fitness function is linear, so a little water gives you a little fitness, medium water gives you medium fitness, and lots of water gives you lots of fitness — in that case, the organism that sees the truth about the water in the world can win, but only because the fitness function happens to align with the true structure in reality. Generically, in the real world, that will never be the case. Something much more natural is a bell curve — say, too little water you die of thirst, but too much water you drown, and only somewhere in between is good for survival. Now the fitness function doesn’t match the structure in the real world. And that’s enough to send truth to extinction. For example, an organism tuned to fitness might see small and large quantities of some resource as, say, red, to indicate low fitness, whereas they might see intermediate quantities as green, to indicate high fitness. Its perceptions will be tuned to fitness, but not to truth. It won’t see any distinction between small and large — it only sees red — even though such a distinction exists in reality.
But how can seeing a false reality be beneficial to an organism’s survival?
There’s a metaphor that’s only been available to us in the past 30 or 40 years, and that’s the desktop interface. Suppose there’s a blue rectangular icon on the lower right corner of your computer’s desktop — does that mean that the file itself is blue and rectangular and lives in the lower right corner of your computer? Of course not. But those are the only things that can be asserted about anything on the desktop — it has color, position and shape. Those are the only categories available to you, and yet none of them are true about the file itself or anything in the computer. They couldn’t possibly be true. That’s an interesting thing. You could not form a true description of the innards of the computer if your entire view of reality was confined to the desktop. And yet the desktop is useful. That blue rectangular icon guides my behavior, and it hides a complex reality that I don’t need to know. That’s the key idea. Evolution has shaped us with perceptions that allow us to survive. They guide adaptive behaviors. But part of that involves hiding from us the stuff we don’t need to know. And that’s pretty much all of reality, whatever reality might be. If you had to spend all that time figuring it out, the tiger would eat you.
So everything we see is one big illusion?
We’ve been shaped to have perceptions that keep us alive, so we have to take them seriously. If I see something that I think of as a snake, I don’t pick it up. If I see a train, I don’t step in front of it. I’ve evolved these symbols to keep me alive, so I have to take them seriously. But it’s a logical flaw to think that if we have to take it seriously, we also have to take it literally.
If snakes aren’t snakes and trains aren’t trains, what are they?
Snakes and trains, like the particles of physics, have no objective, observer-independent features. The snake I see is a description created by my sensory system to inform me of the fitness consequences of my actions. Evolution shapes acceptable solutions, not optimal ones. A snake is an acceptable solution to the problem of telling me how to act in a situation. My snakes and trains are my mental representations; your snakes and trains are your mental representations.
How did you first become interested in these ideas?
As a teenager, I was very interested in the question “Are we machines?” My reading of the science suggested that we are. But my dad was a minister, and at church they were saying we’re not. So I decided I needed to figure it out for myself. It’s sort of an important personal question — if I’m a machine, I would like to find that out! And if I’m not, I’d like to know, what is that special magic beyond the machine? So eventually in the 1980s I went to the artificial intelligence lab at MIT and worked on machine perception. The field of vision research was enjoying a newfound success in developing mathematical models for specific visual abilities. I noticed that they seemed to share a common mathematical structure, so I thought it might be possible to write down a formal structure for observation that encompassed all of them, perhaps all possible modes of observation. I was inspired in part by Alan Turing. When he invented the Turing machine, he was trying to come up with a notion of computation, and instead of putting bells and whistles on it, he said, Let’s get the simplest, most pared down mathematical description that could possibly work. And that simple formalism is the foundation for the science of computation. So I wondered, could I provide a similarly simple formal foundation for the science of observation?
A mathematical model of consciousness.
That’s right. My intuition was, there are conscious experiences. I have pains, tastes, smells, all my sensory experiences, moods, emotions and so forth. So I’m just going to say: One part of this consciousness structure is a set of all possible experiences. When I’m having an experience, based on that experience I may want to change what I’m doing. So I need to have a collection of possible actions I can take and a decision strategy that, given my experiences, allows me to change how I’m acting. That’s the basic idea of the whole thing. I have a space X of experiences, a space G of actions, and an algorithm D that lets me choose a new action given my experiences. Then I posited a W for a world, which is also a probability space. Somehow the world affects my perceptions, so there’s a perception map P from the world to my experiences, and when I act, I change the world, so there’s a map A from the space of actions to the world. That’s the entire structure. Six elements. The claim is: This is the structure of consciousness. I put that out there so people have something to shoot at.
But if there’s a W, are you saying there is an external world?
Here’s the striking thing about that. I can pull the W out of the model and stick a conscious agent in its place and get a circuit of conscious agents. In fact, you can have whole networks of arbitrary complexity. And that’s the world.
The world is just other conscious agents?
I call it conscious realism: Objective reality is just conscious agents, just points of view. Interestingly, I can take two conscious agents and have them interact, and the mathematical structure of that interaction also satisfies the definition of a conscious agent. This mathematics is telling me something. I can take two minds, and they can generate a new, unified single mind. Here’s a concrete example. We have two hemispheres in our brain. But when you do a split-brain operation, a complete transection of the corpus callosum, you get clear evidence of two separate consciousnesses. Before that slicing happened, it seemed there was a single unified consciousness. So it’s not implausible that there is a single conscious agent. And yet it’s also the case that there are two conscious agents there, and you can see that when they’re split. I didn’t expect that, the mathematics forced me to recognize this. It suggests that I can take separate observers, put them together and create new observers, and keep doing this ad infinitum. It’s conscious agents all the way down.
If it’s conscious agents all the way down, all first-person points of view, what happens to science? Science has always been a third-person description of the world.
The idea that what we’re doing is measuring publicly accessible objects, the idea that objectivity results from the fact that you and I can measure the same object in the exact same situation and get the same results — it’s very clear from quantum mechanics that that idea has to go. Physics tells us that there are no public physical objects. So what’s going on? Here’s how I think about it. I can talk to you about my headache and believe that I am communicating effectively with you, because you’ve had your own headaches. The same thing is true as apples and the moon and the sun and the universe. Just like you have your own headache, you have your own moon. But I assume it’s relevantly similar to mine. That’s an assumption that could be false, but that’s the source of my communication, and that’s the best we can do in terms of public physical objects and objective science.
It doesn’t seem like many people in neuroscience or philosophy of mind are thinking about fundamental physics. Do you think that’s been a stumbling block for those trying to understand consciousness?
I think it has been. Not only are they ignoring the progress in fundamental physics, they are often explicit about it. They’ll say openly that quantum physics is not relevant to the aspects of brain function that are causally involved in consciousness. They are certain that it’s got to be classical properties of neural activity, which exist independent of any observers — spiking rates, connection strengths at synapses, perhaps dynamical properties as well. These are all very classical notions under Newtonian physics, where time is absolute and objects exist absolutely. And then [neuroscientists] are mystified as to why they don’t make progress. They don’t avail themselves of the incredible insights and breakthroughs that physics has made. Those insights are out there for us to use, and yet my field says, “We’ll stick with Newton, thank you. We’ll stay 300 years behind in our physics.”
I suspect they’re reacting to things like Roger Penrose and Stuart Hameroff’s model, where you still have a physical brain, it’s still sitting in space, but supposedly it’s performing some quantum feat. In contrast, you’re saying, “Look, quantum mechanics is telling us that we have to question the very notions of ‘physical things’ sitting in ‘space.’”
I think that’s absolutely true. The neuroscientists are saying, “We don’t need to invoke those kind of quantum processes, we don’t need quantum wave functions collapsing inside neurons, we can just use classical physics to describe processes in the brain.” I’m emphasizing the larger lesson of quantum mechanics: Neurons, brains, space … these are just symbols we use, they’re not real. It’s not that there’s a classical brain that does some quantum magic. It’s that there’s no brain! Quantum mechanics says that classical objects — including brains — don’t exist. So this is a far more radical claim about the nature of reality and does not involve the brain pulling off some tricky quantum computation. So even Penrose hasn’t taken it far enough. But most of us, you know, we’re born realists. We’re born physicalists. This is a really, really hard one to let go of.
To return to the question you started with as a teenager, are we machines?
The formal theory of conscious agents I’ve been developing is computationally universal — in that sense, it’s a machine theory. And it’s because the theory is computationally universal that I can get all of cognitive science and neural networks back out of it. Nevertheless, for now I don’t think we are machines — in part because I distinguish between the mathematical representation and the thing being represented. As a conscious realist, I am postulating conscious experiences as ontological primitives, the most basic ingredients of the world. I’m claiming that experiences are the real coin of the realm. The experiences of everyday life — my real feeling of a headache, my real taste of chocolate — that really is the ultimate nature of reality.
Tuesday, October 27, 2015
Did Humans Evolve to See Things as They Really Are?
via Scientific American
One of the deepest problems in epistemology is how we know the nature of reality. Over the millennia philosophers have offered many theories, from solipsism (only one's mind is known to exist) to the theory that natural selection shaped our senses to give us an accurate, or verdical, model of the world. Now a new theory by University of California, Irvine, cognitive scientist Donald Hoffman is garnering attention. (Google his scholarly papers and TED talk with more than 1.4 million views.) Grounded in evolutionary psychology, it is called the interface theory of perception (ITP) and argues that percepts act as a species-specific user interface that directs behavior toward survival and reproduction, not truth.
Hoffman's computer analogy is that physical space is like the desktop and that objects in it are like desktop icons, which are produced by the graphical user interface (GUI). Our senses, he says, form a biological user interface—a gooey GUI—between our brain and the outside world, transducing physical stimuli such as photons of light into neural impulses processed by the visual cortex as things in the environment. GUIs are useful because you don't need to know what is inside computers and brains. You just need to know how to interact with the interface well enough to accomplish your task. Adaptive function, not veridical perception, is what is important.
Hoffman's holotype is the Australian jewel beetle Julodimorpha bakewelli. Females are large, shiny, brown and dimpled. So, too, are discarded beer bottles dubbed “stubbies,” and males will mount them until they die by heat, starvation or ants. The species was on the brink of extinction because its senses and brain were designed by natural selection not to perceive reality (it's a beer bottle, you idiot!) but to mate with anything big, brown, shiny and dimply.
To test his theory, Hoffman ran thousands of evolutionary computer simulations in which digital organisms whose perceptual systems are tuned exclusively for truth are outcompeted by those tuned solely for fitness. Because natural selection depends only on expected fitness, evolution shaped our sensory systems toward fitter behavior, not truthful representation.
ITP is well worth serious consideration and testing, but I have my doubts. First, how could a more accurate perception of reality not be adaptive? Hoffman's answer is that evolution gave us an interface to hide the underlying reality because, for example, you don't need to know how neurons create images of snakes; you just need to jump out of the way of the snake icon. But how did the icon come to look like a snake in the first place? Natural selection. And why did some nonpoisonous snakes evolve to mimic poisonous species? Because predators avoid real poisonous snakes. Mimicry works only if there is an objective reality to mimic.
Hoffman has claimed that “a rock is an interface icon, not a constituent of objective reality.” But a real rock chipped into an arrow point and thrown at a four-legged meal works even if you don't know physics and calculus. Is that not veridical perception with adaptive significance?
see also:
Health: General Anesthesia Causes No Cognitive Deficit in Infants | Mind: Scientists Study Nomophobia — Fear of Being without a Mobile Phone | Sustainability: Exxon Knew about Climate Change Almost 40 Years Ago | Tech: Back to the Future, Part II Predicted Techno-Marvels of October 21, 2015
As for jewel beetles, stubbies are what ethologists call supernormal stimuli, which mimic objects that organisms evolved to respond to and elicit a stronger response in doing so, such as (for some people) silicone breast implants in women and testosterone-enhanced bodybuilding in men. Supernormal stimuli operate only because evolution designed us to respond to normal stimuli, which must be accurately portrayed by our senses to our brain to work.
Hoffman says that perception is species-specific and that we should take predators seriously but not literally. Yes, a dolphin's icon for “shark” no doubt looks different than a human's, but there really are sharks, and they really do have powerful tails on one end and a mouthful of teeth on the other end, and that is true no matter how your sensory system works.
Also, computer simulations are useful for modeling how evolution might have happened, but a real-world test of ITP would be to determine if most biological sensory interfaces create icons that resemble reality or distort it. I'm betting on reality. Data will tell.
Finally, why present this problem as an either-or choice between fitness and truth? Adaptations depend in large part on a relatively accurate model of reality. The fact that science progresses toward, say, eradicating diseases and landing spacecraft on Mars must mean that our perceptions of reality are growing ever closer to the truth, even if it is with a small “t.”
One of the deepest problems in epistemology is how we know the nature of reality. Over the millennia philosophers have offered many theories, from solipsism (only one's mind is known to exist) to the theory that natural selection shaped our senses to give us an accurate, or verdical, model of the world. Now a new theory by University of California, Irvine, cognitive scientist Donald Hoffman is garnering attention. (Google his scholarly papers and TED talk with more than 1.4 million views.) Grounded in evolutionary psychology, it is called the interface theory of perception (ITP) and argues that percepts act as a species-specific user interface that directs behavior toward survival and reproduction, not truth.
Hoffman's computer analogy is that physical space is like the desktop and that objects in it are like desktop icons, which are produced by the graphical user interface (GUI). Our senses, he says, form a biological user interface—a gooey GUI—between our brain and the outside world, transducing physical stimuli such as photons of light into neural impulses processed by the visual cortex as things in the environment. GUIs are useful because you don't need to know what is inside computers and brains. You just need to know how to interact with the interface well enough to accomplish your task. Adaptive function, not veridical perception, is what is important.
Hoffman's holotype is the Australian jewel beetle Julodimorpha bakewelli. Females are large, shiny, brown and dimpled. So, too, are discarded beer bottles dubbed “stubbies,” and males will mount them until they die by heat, starvation or ants. The species was on the brink of extinction because its senses and brain were designed by natural selection not to perceive reality (it's a beer bottle, you idiot!) but to mate with anything big, brown, shiny and dimply.
To test his theory, Hoffman ran thousands of evolutionary computer simulations in which digital organisms whose perceptual systems are tuned exclusively for truth are outcompeted by those tuned solely for fitness. Because natural selection depends only on expected fitness, evolution shaped our sensory systems toward fitter behavior, not truthful representation.
ITP is well worth serious consideration and testing, but I have my doubts. First, how could a more accurate perception of reality not be adaptive? Hoffman's answer is that evolution gave us an interface to hide the underlying reality because, for example, you don't need to know how neurons create images of snakes; you just need to jump out of the way of the snake icon. But how did the icon come to look like a snake in the first place? Natural selection. And why did some nonpoisonous snakes evolve to mimic poisonous species? Because predators avoid real poisonous snakes. Mimicry works only if there is an objective reality to mimic.
Hoffman has claimed that “a rock is an interface icon, not a constituent of objective reality.” But a real rock chipped into an arrow point and thrown at a four-legged meal works even if you don't know physics and calculus. Is that not veridical perception with adaptive significance?
see also:
Health: General Anesthesia Causes No Cognitive Deficit in Infants | Mind: Scientists Study Nomophobia — Fear of Being without a Mobile Phone | Sustainability: Exxon Knew about Climate Change Almost 40 Years Ago | Tech: Back to the Future, Part II Predicted Techno-Marvels of October 21, 2015
As for jewel beetles, stubbies are what ethologists call supernormal stimuli, which mimic objects that organisms evolved to respond to and elicit a stronger response in doing so, such as (for some people) silicone breast implants in women and testosterone-enhanced bodybuilding in men. Supernormal stimuli operate only because evolution designed us to respond to normal stimuli, which must be accurately portrayed by our senses to our brain to work.
Hoffman says that perception is species-specific and that we should take predators seriously but not literally. Yes, a dolphin's icon for “shark” no doubt looks different than a human's, but there really are sharks, and they really do have powerful tails on one end and a mouthful of teeth on the other end, and that is true no matter how your sensory system works.
Also, computer simulations are useful for modeling how evolution might have happened, but a real-world test of ITP would be to determine if most biological sensory interfaces create icons that resemble reality or distort it. I'm betting on reality. Data will tell.
Finally, why present this problem as an either-or choice between fitness and truth? Adaptations depend in large part on a relatively accurate model of reality. The fact that science progresses toward, say, eradicating diseases and landing spacecraft on Mars must mean that our perceptions of reality are growing ever closer to the truth, even if it is with a small “t.”
Thursday, June 11, 2015
Conscious realism
"To a physicalist, the conscious-realist mind-body problem might appear to be a bait and switch that dodges hard and interesting questions: What is consciousness for ? When and how did it arise in evolution ? How does it now arise from brain activity ? Now, the switch from the ontology of physicalism to the ontology of conscious realism changes the relevant questions. Consciousness is fundamental. So to ask what consciousness is for is to ask why something exists rather than nothing. To ask how consciousness arose in a physicalist evolution is mistaken. Instead we ask how the dynamics of conscious agents, when projected onto appropriate MUIs, yields current evolutionary theory as a special case. To ask how consciousness arises from brain activity is also mistaken. Brains are complex icons representing heterarchies of interacting conscious agents. So instead we ask how neurobiology serves as a user interface to such heterarchies. Conscious realism, it is true, dodges some tough mysteries posed by physicalism, but it replaces them with new, and equally engaging,
scientific problems.
Nobody explains everything. If you want to solve the mind-body problem you can take the physical as given and explain the genesis of conscious experience, or take conscious experience as given and explain the genesis of the physical. Explaining the genesis of conscious experience from the physical has proved, so far, intractable. Explaining the genesis of the physical from conscious experience has proved quite feasible. This is good news: We do not need a mutation that endows a new conceptual apparatus to transform the mind-body problem from a mystery to a routine scientific subject, we just need a change in the direction in which we seek an explanation. We can start with a mathematically precise theory of conscious agents and their interactions. We can, according to the norms of methodological naturalism, devise and test theories of how conscious agents construct physical objects and their properties, even space and time themselves. In the process we need relinquish no method or result of physicalist science, but instead we aim to exhibit each such result as a special case in a more comprehensive, conscious realist, framework."
http://www.cogsci.uci.edu/~ddhoff/ConsciousRealism2.pdf
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