#functionalism — Public Fediverse posts

📚 📈#Words continue to evolve: Why #language, #memes, and #brains follow the #logic of #evolution 🧬🧠

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#DanielDennett #PhilosophyOfMind #CognitiveScience #Memetics #CulturalEvolution #TheoryOfEvolution #Consciousness #ArtificialIntelligence #AGI #Neuroscience #ComputationalNeuroscience #Zoomposium #SelfAndIdentity #MindAndBrain #Naturalism #Functionalism #Embodiment #InformationTheory #ScienceCommunication

📚 📈#Words continue to evolve: Why #language, #memes, and #brains follow the #logic of #evolution 🧬🧠

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#DanielDennett #PhilosophyOfMind #CognitiveScience #Memetics #CulturalEvolution #TheoryOfEvolution #Consciousness #ArtificialIntelligence #AGI #Neuroscience #ComputationalNeuroscience #Zoomposium #SelfAndIdentity #MindAndBrain #Naturalism #Functionalism #Embodiment #InformationTheory #ScienceCommunication

📚 📈#Words continue to evolve: Why #language, #memes, and #brains follow the #logic of #evolution 🧬🧠

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#DanielDennett #PhilosophyOfMind #CognitiveScience #Memetics #CulturalEvolution #TheoryOfEvolution #Consciousness #ArtificialIntelligence #AGI #Neuroscience #ComputationalNeuroscience #Zoomposium #SelfAndIdentity #MindAndBrain #Naturalism #Functionalism #Embodiment #InformationTheory #ScienceCommunication

📚 📈#Words continue to evolve: Why #language, #memes, and #brains follow the #logic of #evolution 🧬🧠

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#DanielDennett #PhilosophyOfMind #CognitiveScience #Memetics #CulturalEvolution #TheoryOfEvolution #Consciousness #ArtificialIntelligence #AGI #Neuroscience #ComputationalNeuroscience #Zoomposium #SelfAndIdentity #MindAndBrain #Naturalism #Functionalism #Embodiment #InformationTheory #ScienceCommunication

📚 📈#Words continue to evolve: Why #language, #memes, and #brains follow the #logic of #evolution 🧬🧠

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#DanielDennett #PhilosophyOfMind #CognitiveScience #Memetics #CulturalEvolution #TheoryOfEvolution #Consciousness #ArtificialIntelligence #AGI #Neuroscience #ComputationalNeuroscience #Zoomposium #SelfAndIdentity #MindAndBrain #Naturalism #Functionalism #Embodiment #InformationTheory #ScienceCommunication

🔬Why #experiments aren't always necessary – ⚛️From #physics to #philosophyofmind🧠

In our #Zoomposium with #DanielDennett, one of the most influential thinkers in the philosophy of mind, we explore this very topic.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Consciousness #Qualia #InsightsIntoPhysics #TheoryVersusExperiment #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism #MindAndBrain

🔬Why #experiments aren't always necessary – ⚛️From #physics to #philosophyofmind🧠

In our #Zoomposium with #DanielDennett, one of the most influential thinkers in the philosophy of mind, we explore this very topic.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Consciousness #Qualia #InsightsIntoPhysics #TheoryVersusExperiment #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism #MindAndBrain

🔬Why #experiments aren't always necessary – ⚛️From #physics to #philosophyofmind🧠

In our #Zoomposium with #DanielDennett, one of the most influential thinkers in the philosophy of mind, we explore this very topic.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Consciousness #Qualia #InsightsIntoPhysics #TheoryVersusExperiment #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism #MindAndBrain

🔬Why #experiments aren't always necessary – ⚛️From #physics to #philosophyofmind🧠

In our #Zoomposium with #DanielDennett, one of the most influential thinkers in the philosophy of mind, we explore this very topic.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Consciousness #Qualia #InsightsIntoPhysics #TheoryVersusExperiment #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism #MindAndBrain

🔬Why #experiments aren't always necessary – ⚛️From #physics to #philosophyofmind🧠

In our #Zoomposium with #DanielDennett, one of the most influential thinkers in the philosophy of mind, we explore this very topic.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Consciousness #Qualia #InsightsIntoPhysics #TheoryVersusExperiment #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism #MindAndBrain

💻 #Functionalism – Why it doesn’t explain #subjectiveExperience 🤕

In the #Zoomposium with #ThomasFuchs, it becomes clear why alternative approaches such as the concept of #embodiedconsciousness are gaining increasing importance. Instead of reducing the #mind to mere #informationprocessing, the focus here shifts to the interplay between #body, #environment, and #experience.

🎥https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#Embodiment #Body #Consciousness #Phenomenology #PhilosophyOfMind

💻 #Functionalism – Why it doesn’t explain #subjectiveExperience 🤕

In the #Zoomposium with #ThomasFuchs, it becomes clear why alternative approaches such as the concept of #embodiedconsciousness are gaining increasing importance. Instead of reducing the #mind to mere #informationprocessing, the focus here shifts to the interplay between #body, #environment, and #experience.

🎥https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#Embodiment #Body #Consciousness #Phenomenology #PhilosophyOfMind

💻 #Functionalism – Why it doesn’t explain #subjectiveExperience 🤕

In the #Zoomposium with #ThomasFuchs, it becomes clear why alternative approaches such as the concept of #embodiedconsciousness are gaining increasing importance. Instead of reducing the #mind to mere #informationprocessing, the focus here shifts to the interplay between #body, #environment, and #experience.

🎥https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#Embodiment #Body #Consciousness #Phenomenology #PhilosophyOfMind

💻 #Functionalism – Why it doesn’t explain #subjectiveExperience 🤕

In the #Zoomposium with #ThomasFuchs, it becomes clear why alternative approaches such as the concept of #embodiedconsciousness are gaining increasing importance. Instead of reducing the #mind to mere #informationprocessing, the focus here shifts to the interplay between #body, #environment, and #experience.

🎥https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#Embodiment #Body #Consciousness #Phenomenology #PhilosophyOfMind

💻 #Functionalism – Why it doesn’t explain #subjectiveExperience 🤕

In the #Zoomposium with #ThomasFuchs, it becomes clear why alternative approaches such as the concept of #embodiedconsciousness are gaining increasing importance. Instead of reducing the #mind to mere #informationprocessing, the focus here shifts to the interplay between #body, #environment, and #experience.

🎥https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#Embodiment #Body #Consciousness #Phenomenology #PhilosophyOfMind

Biological computation and the nature of software

A new paper is been getting some attention. It makes the case for biological computation. (This is a link to a summary, but there’s a link to the actual paper at the bottom of that article.)

Characterizing the debate between computational functionalism and biological naturalism as camps that are hopelessly dug in, the authors propose that the brain does do computation, but that it’s a very different kind from the type done in the device you’re using to read this, which they call “biological computation.”

The differences are that biological computation is a hybrid between digital (discrete) and analog (continuous) computing, there is no clean division between software and hardware, between algorithms and implementation, and that metabolism and energy constraints shape the processing that happens. They sum it up as, in the brain, the algorithm is the substrate.

The authors argue that to build artificially conscious systems, it may be necessary to go with a different physical ontology, one that is closer to the way biology works.

Let me start by saying that this paper is a big improvement over the usual arguments about the distinctions between computers and biology. The authors are making a real effort to identify what supposedly makes biology unique. Most of what they’re saying already accords with my own understanding of how the brain works, and what’s different about its computation. There are a few points where they try to pass off speculation as established fact, but those are nits.

That said, I think they oversell some of their points. For example, the distinction between analog and digital is often less than it appears. We listen to music and watch movies all the time in digital formats that were originally recorded in analog. Yes, something can be lost in the translation from continuous to discrete signaling, but in an analog system there is always variance noise, variations between a system’s processing, both with other systems of the same type, and between runs in the same system. The trick is for the translation to reduce the quantization noise, the distortions from moving to a discrete format, so that they’re less than the variance noise in the original.

Another is the aspect they call scale inseparability, the idea that the brain doesn’t use the layers of abstraction that technology uses. These layers exist in technology to make the engineering easier to understand and maintain, for engineers. Evolution doesn’t care about understanding so it’s not a factor in how biological systems are organized. The authors use this to imply that the software / hardware divide may be something the technology side will have to give up. That the algorithm may need to be in the substrate as it is with biology.

I think this represents confusion about what software actually is. We usually talk about software as a set of instructions that a processor follows. In most cases, it’s convenient to think about it that way. But at a more physical level, it makes more sense to think of software as a configuration of hardware. So when software is running on hardware, the algorithm is always the substrate.

The real distinction here is that technological computers are designed to be reconfigured on the fly. This is actually an amazing achievement when you stop and think about it. I often see articles marveling at the brain’s plasticity, its ability to rewire itself. But your computer’s memory can undergo wholesale reconfiguration on demand by loading a new software package, something brain’s can’t do, at least not quickly.

Of course, this comes with vulnerabilities brains are far less susceptible to. One reason computers can be hacked is this ability to massively reconfigure. Not that brains are completely immune. Ant brains can be hacked by a fungal infection, and cat owners can be infected with a parasite that makes them like their cats more, and that’s aside from the ability of advertisers and propagandists to hijack our brain’s reasoning to introduce notions we might otherwise resist. But it’s a harder thing to do effectively in biological systems.

What’s important to realize is that anything that can be done in hardware can, in principle, be done in software, at least once a minimal general computing platform is in place. You can run software that emulates other hardware platforms so you can run their software. It is true that doing it in hardware is often far more efficient in terms of performance and energy, but that comes with reduced flexibility. It’s why we now run word processors on our general purpose computers instead of the old word processing machines that once existed.

So I don’t think the fact that current AI runs on software neural networks, in and of itself, is a showstopper. Another difference is that the brain operates with massive parallelization, far more than any current technological system. These systems can still perform something like the brain’s processing in software because they operate millions of times faster. Although the addition of GPUs, designed with parallelization in mind, help a great deal.

But that, I think, gets to a valid concern the authors make about energy constraints. Discrete processing, and doing things with software instead of hardware, come at a cost in terms of energy and performance. This is something I do think AI researchers should be paying more attention to. All we need to do to understand how far current AI is from animal intelligence, much less human level, is look at the vast amounts of data and energy it requires to do what it does. Datacenters are sucking the power grid dry to meet their energy demands. All of which speaks to how crude the technology remains in comparison to biological intelligence.

But this energy constraint issue is broader than just trying to reproduce biological processes. I think it’s a problem for all technological computing. And it will likely eventually result in architecture changes. Understanding how biology does it may be important, but I tend to doubt the solution will be doing it exactly like those systems.

And this gets to a sentiment that I detect in the paper and write ups about it. It’s the idea that consciousness is a ghost in the machine, one we need to find the magic ingredients for so we can generate it. I think this is fundamentally the wrong way to think about it. Neuroscientist Hawan Lau, I think, in a Bluesky post, sums up the issue. Why do we think this might be true for consciousness when it isn’t for so many other things the body does, like motor control?

All that said, I do like the term “biological computation.” It admits that the computation in brains is different while still acknowledging the important ways it’s the same. I suspect that won’t be enough for those strongly convinced computationalism is wrong, but it still feels like useful progress.

What do you think about the points the authors make? Or my take on them? Are they right that a new hardware architecture is required? Or would even that be enough? Does the “biological computation” term strike the right balance?

#AI #ArtificialIntelligence #BiologicalComputation #ComputationalFunctionalism #Consciousness #functionalism #Neuroscience #Philosophy #PhilosophyOfMind

Biological computation and the nature of software

A new paper is been getting some attention. It makes the case for biological computation. (This is a link to a summary, but there’s a link to the actual paper at the bottom of that article.)

Characterizing the debate between computational functionalism and biological naturalism as camps that are hopelessly dug in, the authors propose that the brain does do computation, but that it’s a very different kind from the type done in the device you’re using to read this, which they call “biological computation.”

The differences are that biological computation is a hybrid between digital (discrete) and analog (continuous) computing, there is no clean division between software and hardware, between algorithms and implementation, and that metabolism and energy constraints shape the processing that happens. They sum it up as, in the brain, the algorithm is the substrate.

The authors argue that to build artificially conscious systems, it may be necessary to go with a different physical ontology, one that is closer to the way biology works.

Let me start by saying that this paper is a big improvement over the usual arguments about the distinctions between computers and biology. The authors are making a real effort to identify what supposedly makes biology unique. Most of what they’re saying already accords with my own understanding of how the brain works, and what’s different about its computation. There are a few points where they try to pass off speculation as established fact, but those are nits.

That said, I think they oversell some of their points. For example, the distinction between analog and digital is often less than it appears. We listen to music and watch movies all the time in digital formats that were originally recorded in analog. Yes, something can be lost in the translation from continuous to discrete signaling, but in an analog system there is always variance noise, variations between a system’s processing, both with other systems of the same type, and between runs in the same system. The trick is for the translation to reduce the quantization noise, the distortions from moving to a discrete format, so that they’re less than the variance noise in the original.

Another is the aspect they call scale inseparability, the idea that the brain doesn’t use the layers of abstraction that technology uses. These layers exist in technology to make the engineering easier to understand and maintain, for engineers. Evolution doesn’t care about understanding so it’s not a factor in how biological systems are organized. The authors use this to imply that the software / hardware divide may be something the technology side will have to give up. That the algorithm may need to be in the substrate as it is with biology.

I think this represents confusion about what software actually is. We usually talk about software as a set of instructions that a processor follows. In most cases, it’s convenient to think about it that way. But at a more physical level, it makes more sense to think of software as a configuration of hardware. So when software is running on hardware, the algorithm is always the substrate.

The real distinction here is that technological computers are designed to be reconfigured on the fly. This is actually an amazing achievement when you stop and think about it. I often see articles marveling at the brain’s plasticity, its ability to rewire itself. But your computer’s memory can undergo wholesale reconfiguration on demand by loading a new software package, something brain’s can’t do, at least not quickly.

Of course, this comes with vulnerabilities brains are far less susceptible to. One reason computers can be hacked is this ability to massively reconfigure. Not that brains are completely immune. Ant brains can be hacked by a fungal infection, and cat owners can be infected with a parasite that makes them like their cats more, and that’s aside from the ability of advertisers and propagandists to hijack our brain’s reasoning to introduce notions we might otherwise resist. But it’s a harder thing to do effectively in biological systems.

What’s important to realize is that anything that can be done in hardware can, in principle, be done in software, at least once a minimal general computing platform is in place. You can run software that emulates other hardware platforms so you can run their software. It is true that doing it in hardware is often far more efficient in terms of performance and energy, but that comes with reduced flexibility. It’s why we now run word processors on our general purpose computers instead of the old word processing machines that once existed.

So I don’t think the fact that current AI runs on software neural networks, in and of itself, is a showstopper. Another difference is that the brain operates with massive parallelization, far more than any current technological system. These systems can still perform something like the brain’s processing in software because they operate millions of times faster. Although the addition of GPUs, designed with parallelization in mind, help a great deal.

But that, I think, gets to a valid concern the authors make about energy constraints. Discrete processing, and doing things with software instead of hardware, come at a cost in terms of energy and performance. This is something I do think AI researchers should be paying more attention to. All we need to do to understand how far current AI is from animal intelligence, much less human level, is look at the vast amounts of data and energy it requires to do what it does. Datacenters are sucking the power grid dry to meet their energy demands. All of which speaks to how crude the technology remains in comparison to biological intelligence.

But this energy constraint issue is broader than just trying to reproduce biological processes. I think it’s a problem for all technological computing. And it will likely eventually result in architecture changes. Understanding how biology does it may be important, but I tend to doubt the solution will be doing it exactly like those systems.

And this gets to a sentiment that I detect in the paper and write ups about it. It’s the idea that consciousness is a ghost in the machine, one we need to find the magic ingredients for so we can generate it. I think this is fundamentally the wrong way to think about it. Neuroscientist Hawan Lau, I think, in a Bluesky post, sums up the issue. Why do we think this might be true for consciousness when it isn’t for so many other things the body does, like motor control?

All that said, I do like the term “biological computation.” It admits that the computation in brains is different while still acknowledging the important ways it’s the same. I suspect that won’t be enough for those strongly convinced computationalism is wrong, but it still feels like useful progress.

What do you think about the points the authors make? Or my take on them? Are they right that a new hardware architecture is required? Or would even that be enough? Does the “biological computation” term strike the right balance?

#AI #ArtificialIntelligence #BiologicalComputation #ComputationalFunctionalism #Consciousness #functionalism #Neuroscience #Philosophy #PhilosophyOfMind

Biological computation and the nature of software

A new paper is been getting some attention. It makes the case for biological computation. (This is a link to a summary, but there’s a link to the actual paper at the bottom of that article.)

Characterizing the debate between computational functionalism and biological naturalism as camps that are hopelessly dug in, the authors propose that the brain does do computation, but that it’s a very different kind from the type done in the device you’re using to read this, which they call “biological computation.”

The differences are that biological computation is a hybrid between digital (discrete) and analog (continuous) computing, there is no clean division between software and hardware, between algorithms and implementation, and that metabolism and energy constraints shape the processing that happens. They sum it up as, in the brain, the algorithm is the substrate.

The authors argue that to build artificially conscious systems, it may be necessary to go with a different physical ontology, one that is closer to the way biology works.

Let me start by saying that this paper is a big improvement over the usual arguments about the distinctions between computers and biology. The authors are making a real effort to identify what supposedly makes biology unique. Most of what they’re saying already accords with my own understanding of how the brain works, and what’s different about its computation. There are a few points where they try to pass off speculation as established fact, but those are nits.

That said, I think they oversell some of their points. For example, the distinction between analog and digital is often less than it appears. We listen to music and watch movies all the time in digital formats that were originally recorded in analog. Yes, something can be lost in the translation from continuous to discrete signaling, but in an analog system there is always variance noise, variations between a system’s processing, both with other systems of the same type, and between runs in the same system. The trick is for the translation to reduce the quantization noise, the distortions from moving to a discrete format, so that they’re less than the variance noise in the original.

Another is the aspect they call scale inseparability, the idea that the brain doesn’t use the layers of abstraction that technology uses. These layers exist in technology to make the engineering easier to understand and maintain, for engineers. Evolution doesn’t care about understanding so it’s not a factor in how biological systems are organized. The authors use this to imply that the software / hardware divide may be something the technology side will have to give up. That the algorithm may need to be in the substrate as it is with biology.

I think this represents confusion about what software actually is. We usually talk about software as a set of instructions that a processor follows. In most cases, it’s convenient to think about it that way. But at a more physical level, it makes more sense to think of software as a configuration of hardware. So when software is running on hardware, the algorithm is always the substrate.

The real distinction here is that technological computers are designed to be reconfigured on the fly. This is actually an amazing achievement when you stop and think about it. I often see articles marveling at the brain’s plasticity, its ability to rewire itself. But your computer’s memory can undergo wholesale reconfiguration on demand by loading a new software package, something brain’s can’t do, at least not quickly.

Of course, this comes with vulnerabilities brains are far less susceptible to. One reason computers can be hacked is this ability to massively reconfigure. Not that brains are completely immune. Ant brains can be hacked by a fungal infection, and cat owners can be infected with a parasite that makes them like their cats more, and that’s aside from the ability of advertisers and propagandists to hijack our brain’s reasoning to introduce notions we might otherwise resist. But it’s a harder thing to do effectively in biological systems.

What’s important to realize is that anything that can be done in hardware can, in principle, be done in software, at least once a minimal general computing platform is in place. You can run software that emulates other hardware platforms so you can run their software. It is true that doing it in hardware is often far more efficient in terms of performance and energy, but that comes with reduced flexibility. It’s why we now run word processors on our general purpose computers instead of the old word processing machines that once existed.

So I don’t think the fact that current AI runs on software neural networks, in and of itself, is a showstopper. Another difference is that the brain operates with massive parallelization, far more than any current technological system. These systems can still perform something like the brain’s processing in software because they operate millions of times faster. Although the addition of GPUs, designed with parallelization in mind, help a great deal.

But that, I think, gets to a valid concern the authors make about energy constraints. Discrete processing, and doing things with software instead of hardware, come at a cost in terms of energy and performance. This is something I do think AI researchers should be paying more attention to. All we need to do to understand how far current AI is from animal intelligence, much less human level, is look at the vast amounts of data and energy it requires to do what it does. Datacenters are sucking the power grid dry to meet their energy demands. All of which speaks to how crude the technology remains in comparison to biological intelligence.

But this energy constraint issue is broader than just trying to reproduce biological processes. I think it’s a problem for all technological computing. And it will likely eventually result in architecture changes. Understanding how biology does it may be important, but I tend to doubt the solution will be doing it exactly like those systems.

And this gets to a sentiment that I detect in the paper and write ups about it. It’s the idea that consciousness is a ghost in the machine, one we need to find the magic ingredients for so we can generate it. I think this is fundamentally the wrong way to think about it. Neuroscientist Hawan Lau, I think, in a Bluesky post, sums up the issue. Why do we think this might be true for consciousness when it isn’t for so many other things the body does, like motor control?

All that said, I do like the term “biological computation.” It admits that the computation in brains is different while still acknowledging the important ways it’s the same. I suspect that won’t be enough for those strongly convinced computationalism is wrong, but it still feels like useful progress.

What do you think about the points the authors make? Or my take on them? Are they right that a new hardware architecture is required? Or would even that be enough? Does the “biological computation” term strike the right balance?

#AI #ArtificialIntelligence #BiologicalComputation #ComputationalFunctionalism #Consciousness #functionalism #Neuroscience #Philosophy #PhilosophyOfMind

Biological computation and the nature of software

A new paper is been getting some attention. It makes the case for biological computation. (This is a link to a summary, but there’s a link to the actual paper at the bottom of that article.)

Characterizing the debate between computational functionalism and biological naturalism as camps that are hopelessly dug in, the authors propose that the brain does do computation, but that it’s a very different kind from the type done in the device you’re using to read this, which they call “biological computation.”

The differences are that biological computation is a hybrid between digital (discrete) and analog (continuous) computing, there is no clean division between software and hardware, between algorithms and implementation, and that metabolism and energy constraints shape the processing that happens. They sum it up as, in the brain, the algorithm is the substrate.

The authors argue that to build artificially conscious systems, it may be necessary to go with a different physical ontology, one that is closer to the way biology works.

Let me start by saying that this paper is a big improvement over the usual arguments about the distinctions between computers and biology. The authors are making a real effort to identify what supposedly makes biology unique. Most of what they’re saying already accords with my own understanding of how the brain works, and what’s different about its computation. There are a few points where they try to pass off speculation as established fact, but those are nits.

That said, I think they oversell some of their points. For example, the distinction between analog and digital is often less than it appears. We listen to music and watch movies all the time in digital formats that were originally recorded in analog. Yes, something can be lost in the translation from continuous to discrete signaling, but in an analog system there is always variance noise, variations between a system’s processing, both with other systems of the same type, and between runs in the same system. The trick is for the translation to reduce the quantization noise, the distortions from moving to a discrete format, so that they’re less than the variance noise in the original.

Another is the aspect they call scale inseparability, the idea that the brain doesn’t use the layers of abstraction that technology uses. These layers exist in technology to make the engineering easier to understand and maintain, for engineers. Evolution doesn’t care about understanding so it’s not a factor in how biological systems are organized. The authors use this to imply that the software / hardware divide may be something the technology side will have to give up. That the algorithm may need to be in the substrate as it is with biology.

I think this represents confusion about what software actually is. We usually talk about software as a set of instructions that a processor follows. In most cases, it’s convenient to think about it that way. But at a more physical level, it makes more sense to think of software as a configuration of hardware. So when software is running on hardware, the algorithm is always the substrate.

The real distinction here is that technological computers are designed to be reconfigured on the fly. This is actually an amazing achievement when you stop and think about it. I often see articles marveling at the brain’s plasticity, its ability to rewire itself. But your computer’s memory can undergo wholesale reconfiguration on demand by loading a new software package, something brain’s can’t do, at least not quickly.

Of course, this comes with vulnerabilities brains are far less susceptible to. One reason computers can be hacked is this ability to massively reconfigure. Not that brains are completely immune. Ant brains can be hacked by a fungal infection, and cat owners can be infected with a parasite that makes them like their cats more, and that’s aside from the ability of advertisers and propagandists to hijack our brain’s reasoning to introduce notions we might otherwise resist. But it’s a harder thing to do effectively in biological systems.

What’s important to realize is that anything that can be done in hardware can, in principle, be done in software, at least once a minimal general computing platform is in place. You can run software that emulates other hardware platforms so you can run their software. It is true that doing it in hardware is often far more efficient in terms of performance and energy, but that comes with reduced flexibility. It’s why we now run word processors on our general purpose computers instead of the old word processing machines that once existed.

So I don’t think the fact that current AI runs on software neural networks, in and of itself, is a showstopper. Another difference is that the brain operates with massive parallelization, far more than any current technological system. These systems can still perform something like the brain’s processing in software because they operate millions of times faster. Although the addition of GPUs, designed with parallelization in mind, help a great deal.

But that, I think, gets to a valid concern the authors make about energy constraints. Discrete processing, and doing things with software instead of hardware, come at a cost in terms of energy and performance. This is something I do think AI researchers should be paying more attention to. All we need to do to understand how far current AI is from animal intelligence, much less human level, is look at the vast amounts of data and energy it requires to do what it does. Datacenters are sucking the power grid dry to meet their energy demands. All of which speaks to how crude the technology remains in comparison to biological intelligence.

But this energy constraint issue is broader than just trying to reproduce biological processes. I think it’s a problem for all technological computing. And it will likely eventually result in architecture changes. Understanding how biology does it may be important, but I tend to doubt the solution will be doing it exactly like those systems.

And this gets to a sentiment that I detect in the paper and write ups about it. It’s the idea that consciousness is a ghost in the machine, one we need to find the magic ingredients for so we can generate it. I think this is fundamentally the wrong way to think about it. Neuroscientist Hawan Lau, I think, in a Bluesky post, sums up the issue. Why do we think this might be true for consciousness when it isn’t for so many other things the body does, like motor control?

All that said, I do like the term “biological computation.” It admits that the computation in brains is different while still acknowledging the important ways it’s the same. I suspect that won’t be enough for those strongly convinced computationalism is wrong, but it still feels like useful progress.

What do you think about the points the authors make? Or my take on them? Are they right that a new hardware architecture is required? Or would even that be enough? Does the “biological computation” term strike the right balance?

#AI #ArtificialIntelligence #BiologicalComputation #ComputationalFunctionalism #Consciousness #functionalism #Neuroscience #Philosophy #PhilosophyOfMind

Biological computation and the nature of software

A new paper is been getting some attention. It makes the case for biological computation. (This is a link to a summary, but there’s a link to the actual paper at the bottom of that article.)

Characterizing the debate between computational functionalism and biological naturalism as camps that are hopelessly dug in, the authors propose that the brain does do computation, but that it’s a very different kind from the type done in the device you’re using to read this, which they call “biological computation.”

The differences are that biological computation is a hybrid between digital (discrete) and analog (continuous) computing, there is no clean division between software and hardware, between algorithms and implementation, and that metabolism and energy constraints shape the processing that happens. They sum it up as, in the brain, the algorithm is the substrate.

The authors argue that to build artificially conscious systems, it may be necessary to go with a different physical ontology, one that is closer to the way biology works.

Let me start by saying that this paper is a big improvement over the usual arguments about the distinctions between computers and biology. The authors are making a real effort to identify what supposedly makes biology unique. Most of what they’re saying already accords with my own understanding of how the brain works, and what’s different about its computation. There are a few points where they try to pass off speculation as established fact, but those are nits.

That said, I think they oversell some of their points. For example, the distinction between analog and digital is often less than it appears. We listen to music and watch movies all the time in digital formats that were originally recorded in analog. Yes, something can be lost in the translation from continuous to discrete signaling, but in an analog system there is always variance noise, variations between a system’s processing, both with other systems of the same type, and between runs in the same system. The trick is for the translation to reduce the quantization noise, the distortions from moving to a discrete format, so that they’re less than the variance noise in the original.

Another is the aspect they call scale inseparability, the idea that the brain doesn’t use the layers of abstraction that technology uses. These layers exist in technology to make the engineering easier to understand and maintain, for engineers. Evolution doesn’t care about understanding so it’s not a factor in how biological systems are organized. The authors use this to imply that the software / hardware divide may be something the technology side will have to give up. That the algorithm may need to be in the substrate as it is with biology.

I think this represents confusion about what software actually is. We usually talk about software as a set of instructions that a processor follows. In most cases, it’s convenient to think about it that way. But at a more physical level, it makes more sense to think of software as a configuration of hardware. So when software is running on hardware, the algorithm is always the substrate.

The real distinction here is that technological computers are designed to be reconfigured on the fly. This is actually an amazing achievement when you stop and think about it. I often see articles marveling at the brain’s plasticity, its ability to rewire itself. But your computer’s memory can undergo wholesale reconfiguration on demand by loading a new software package, something brain’s can’t do, at least not quickly.

Of course, this comes with vulnerabilities brains are far less susceptible to. One reason computers can be hacked is this ability to massively reconfigure. Not that brains are completely immune. Ant brains can be hacked by a fungal infection, and cat owners can be infected with a parasite that makes them like their cats more, and that’s aside from the ability of advertisers and propagandists to hijack our brain’s reasoning to introduce notions we might otherwise resist. But it’s a harder thing to do effectively in biological systems.

What’s important to realize is that anything that can be done in hardware can, in principle, be done in software, at least once a minimal general computing platform is in place. You can run software that emulates other hardware platforms so you can run their software. It is true that doing it in hardware is often far more efficient in terms of performance and energy, but that comes with reduced flexibility. It’s why we now run word processors on our general purpose computers instead of the old word processing machines that once existed.

So I don’t think the fact that current AI runs on software neural networks, in and of itself, is a showstopper. Another difference is that the brain operates with massive parallelization, far more than any current technological system. These systems can still perform something like the brain’s processing in software because they operate millions of times faster. Although the addition of GPUs, designed with parallelization in mind, help a great deal.

But that, I think, gets to a valid concern the authors make about energy constraints. Discrete processing, and doing things with software instead of hardware, come at a cost in terms of energy and performance. This is something I do think AI researchers should be paying more attention to. All we need to do to understand how far current AI is from animal intelligence, much less human level, is look at the vast amounts of data and energy it requires to do what it does. Datacenters are sucking the power grid dry to meet their energy demands. All of which speaks to how crude the technology remains in comparison to biological intelligence.

But this energy constraint issue is broader than just trying to reproduce biological processes. I think it’s a problem for all technological computing. And it will likely eventually result in architecture changes. Understanding how biology does it may be important, but I tend to doubt the solution will be doing it exactly like those systems.

And this gets to a sentiment that I detect in the paper and write ups about it. It’s the idea that consciousness is a ghost in the machine, one we need to find the magic ingredients for so we can generate it. I think this is fundamentally the wrong way to think about it. Neuroscientist Hawan Lau, I think, in a Bluesky post, sums up the issue. Why do we think this might be true for consciousness when it isn’t for so many other things the body does, like motor control?

All that said, I do like the term “biological computation.” It admits that the computation in brains is different while still acknowledging the important ways it’s the same. I suspect that won’t be enough for those strongly convinced computationalism is wrong, but it still feels like useful progress.

What do you think about the points the authors make? Or my take on them? Are they right that a new hardware architecture is required? Or would even that be enough? Does the “biological computation” term strike the right balance?

#AI #ArtificialIntelligence #BiologicalComputation #ComputationalFunctionalism #Consciousness #functionalism #Neuroscience #Philosophy #PhilosophyOfMind

🆓 Free Will – Why I Said Yes To This Interview🎙️

“I acted on my own free will. Nobody forced me.”

With these words, #DanielDennett opens our #Zoomposium on the question of free will – and sets the tone for a conversation that is as pointed as it is profound.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#FreeWill #PhilosophyOfMind #Consciousness #FreeWillDebate #SelfAndIdentity #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism

🆓 Free Will – Why I Said Yes To This Interview🎙️

“I acted on my own free will. Nobody forced me.”

With these words, #DanielDennett opens our #Zoomposium on the question of free will – and sets the tone for a conversation that is as pointed as it is profound.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#FreeWill #PhilosophyOfMind #Consciousness #FreeWillDebate #SelfAndIdentity #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism

🆓 Free Will – Why I Said Yes To This Interview🎙️

“I acted on my own free will. Nobody forced me.”

With these words, #DanielDennett opens our #Zoomposium on the question of free will – and sets the tone for a conversation that is as pointed as it is profound.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#FreeWill #PhilosophyOfMind #Consciousness #FreeWillDebate #SelfAndIdentity #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism

🆓 Free Will – Why I Said Yes To This Interview🎙️

“I acted on my own free will. Nobody forced me.”

With these words, #DanielDennett opens our #Zoomposium on the question of free will – and sets the tone for a conversation that is as pointed as it is profound.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#FreeWill #PhilosophyOfMind #Consciousness #FreeWillDebate #SelfAndIdentity #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism

🆓 Free Will – Why I Said Yes To This Interview🎙️

“I acted on my own free will. Nobody forced me.”

With these words, #DanielDennett opens our #Zoomposium on the question of free will – and sets the tone for a conversation that is as pointed as it is profound.

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#FreeWill #PhilosophyOfMind #Consciousness #FreeWillDebate #SelfAndIdentity #CognitiveScience #Neuroscience #MultipleDraftsModel #Functionalism #Naturalism #Materialism

🧠🔧 Functionalism—the key to understanding the mind? Or a modern misconception?

#Functionalism and our understanding of the #mind: the #brain as software, #humans as #programs, #consciousness as a kind of #code.

A #Zoomposium with #ThomasFuchs on #embodiment, #AI, #neuroconstructivism, and the #future of our #view of humanity.

🎥 https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#EmbodiedConsciousness #PhilosophyOfMind #CognitiveNeuroscience

🧠🔧 Functionalism—the key to understanding the mind? Or a modern misconception?

#Functionalism and our understanding of the #mind: the #brain as software, #humans as #programs, #consciousness as a kind of #code.

A #Zoomposium with #ThomasFuchs on #embodiment, #AI, #neuroconstructivism, and the #future of our #view of humanity.

🎥 https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#EmbodiedConsciousness #PhilosophyOfMind #CognitiveNeuroscience

🧠🔧 Functionalism—the key to understanding the mind? Or a modern misconception?

#Functionalism and our understanding of the #mind: the #brain as software, #humans as #programs, #consciousness as a kind of #code.

A #Zoomposium with #ThomasFuchs on #embodiment, #AI, #neuroconstructivism, and the #future of our #view of humanity.

🎥 https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#EmbodiedConsciousness #PhilosophyOfMind #CognitiveNeuroscience

🧠🔧 Functionalism—the key to understanding the mind? Or a modern misconception?

#Functionalism and our understanding of the #mind: the #brain as software, #humans as #programs, #consciousness as a kind of #code.

A #Zoomposium with #ThomasFuchs on #embodiment, #AI, #neuroconstructivism, and the #future of our #view of humanity.

🎥 https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#EmbodiedConsciousness #PhilosophyOfMind #CognitiveNeuroscience

🧠🔧 Functionalism—the key to understanding the mind? Or a modern misconception?

#Functionalism and our understanding of the #mind: the #brain as software, #humans as #programs, #consciousness as a kind of #code.

A #Zoomposium with #ThomasFuchs on #embodiment, #AI, #neuroconstructivism, and the #future of our #view of humanity.

🎥 https://youtu.be/1ouxs6P3Enc

📎https://philosophies.de/index.php/2022/11/20/das-verkoerperte-bewusstsein/

#EmbodiedConsciousness #PhilosophyOfMind #CognitiveNeuroscience

#Consciousness – The Brain’s #UserIllusion, Explained!🧠✨

What if consciousness isn’t the “captain” of our #thoughts — but just the dashboard we use to navigate them?

📽 Interview: https://youtu.be/M2qiVz95ZYk

📎 Information: https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Zoomposium #DanielDennett #Consciousness #UserIllusion #PhilosophyOfMind #CognitiveScience #Neuroscience #Qualia #FreeWill #ArtificialIntelligence #AGI #Embodiment #Functionalism #Materialism #Naturalism #MindAndMachine #Cognition #IllusionOfSelf

#Consciousness – The Brain’s #UserIllusion, Explained!🧠✨

What if consciousness isn’t the “captain” of our #thoughts — but just the dashboard we use to navigate them?

📽 Interview: https://youtu.be/M2qiVz95ZYk

📎 Information: https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Zoomposium #DanielDennett #Consciousness #UserIllusion #PhilosophyOfMind #CognitiveScience #Neuroscience #Qualia #FreeWill #ArtificialIntelligence #AGI #Embodiment #Functionalism #Materialism #Naturalism #MindAndMachine #Cognition #IllusionOfSelf

#Consciousness – The Brain’s #UserIllusion, Explained!🧠✨

What if consciousness isn’t the “captain” of our #thoughts — but just the dashboard we use to navigate them?

📽 Interview: https://youtu.be/M2qiVz95ZYk

📎 Information: https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Zoomposium #DanielDennett #Consciousness #UserIllusion #PhilosophyOfMind #CognitiveScience #Neuroscience #Qualia #FreeWill #ArtificialIntelligence #AGI #Embodiment #Functionalism #Materialism #Naturalism #MindAndMachine #Cognition #IllusionOfSelf

#Consciousness – The Brain’s #UserIllusion, Explained!🧠✨

What if consciousness isn’t the “captain” of our #thoughts — but just the dashboard we use to navigate them?

📽 Interview: https://youtu.be/M2qiVz95ZYk

📎 Information: https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Zoomposium #DanielDennett #Consciousness #UserIllusion #PhilosophyOfMind #CognitiveScience #Neuroscience #Qualia #FreeWill #ArtificialIntelligence #AGI #Embodiment #Functionalism #Materialism #Naturalism #MindAndMachine #Cognition #IllusionOfSelf

#Consciousness – The Brain’s #UserIllusion, Explained!🧠✨

What if consciousness isn’t the “captain” of our #thoughts — but just the dashboard we use to navigate them?

📽 Interview: https://youtu.be/M2qiVz95ZYk

📎 Information: https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#Zoomposium #DanielDennett #Consciousness #UserIllusion #PhilosophyOfMind #CognitiveScience #Neuroscience #Qualia #FreeWill #ArtificialIntelligence #AGI #Embodiment #Functionalism #Materialism #Naturalism #MindAndMachine #Cognition #IllusionOfSelf

Modular NAS system by Gridstack

https://www.grid-stack.com/

#design #industrialdesign #technology #nas #minimalism #functionalism #modular #aesthetics

Modular NAS system by Gridstack

https://www.grid-stack.com/

#design #industrialdesign #technology #nas #minimalism #functionalism #modular #aesthetics

Modular NAS system by Gridstack

https://www.grid-stack.com/

#design #industrialdesign #technology #nas #minimalism #functionalism #modular #aesthetics

Modular NAS system by Gridstack

https://www.grid-stack.com/

#design #industrialdesign #technology #nas #minimalism #functionalism #modular #aesthetics

Modular NAS system by Gridstack

https://www.grid-stack.com/

#design #industrialdesign #technology #nas #minimalism #functionalism #modular #aesthetics

What is a non-functional account of consciousness supposed to be?

I’m a functionalist. I think the mind and consciousness is about what the brain does, rather than its particular composition, or some other attribute. Which means that if another system did the same or similar things, it would make sense to say it was conscious. Consciousness is as consciousness does.

Functionalism has some advantages over other meta-theories of consciousness. One is that since we’re talking about functionality, of capabilities, establishing consciousness in other species and systems is a matter of establishing what they can do. But it does require accepting that consciousness can come in gradations. And that “consciousness” is not a precise designation of which collection of functionality is required. So it means giving up primitivism about consciousness, accepting that rather than a single natural kind, it’s a hazy collection of many different kinds.

It’s worth pausing to be clear on what functionalism is. It’s about cause-effect relationships. These relationships can, in principle, be modeled by Ramsey sentences, a technique David Lewis adapted from Frank Ramsey, which models a causal sequence, or entire structures of those sequences. (Suzi Travis has an excellent post which includes an introduction to them.) At the heart of the entire enterprise are these cause-effect relations.

Of course, cause-effect relations are themselves emergent from the symmetrical (reversible) structural relations of more fundamental physics. Causes and effects attain their asymmetry due to the Second Law of Thermodynamics, the one that says entropy always increases. So another way to talk about functionalism is in terms of structural realism. Ultimately functionalism is about structural relations. (Something it took me a while to appreciate after discovering structural realism.)

Over the years, I’ve received a lot of different reactions to this position. Not a few aren’t sure what functionalism is. Some are outraged by the idea. Others equate it with behaviorism. (Unlike behaviorism, functionalism accepts the existence of intermediate states between stimuli and response.)

But occasionally someone responds that the idea is obvious and trivial. I think this response is interesting, because I basically agree. It is trivial, or it should be. I only started calling myself a functionalist because so many people insist that the real problem of consciousness isn’t about functionality.

Philosophers have long argued for a version of consciousness that is beyond functionality. Ned Block, when making his distinction between phenomenal and access consciousness, while admitting there were functional notions of phenomenal consciousness, argued for a version that was something other than functionality (or intentionality, which is also relational). And David Chalmers argues that solving the hard problem of consciousness isn’t about solving the structure and relations that science can usually get a handle on.

Anyone who’s known me for a while will be aware that I think these views are mistaken. But I have to admit something. Part of the reason I’m not enthusiastic about them is I don’t even know what a non-functional view of consciousness is supposed to be.

I understand old school interactionist dualism well enough. But in that case there are still causes and effects. It’s just that most of them are hidden from us in some kind of non-physical substrate. But the interaction in interactionist dualism should be detectable by science, and hasn’t been, which I think is why many contemporary non-physicalists gravitate to other options.

It’s when we get to views like property dualism and panpsychism that I start to lose understanding. We’re supposed to be talking about something beyond the functionality, beyond structure and relations, something that could be absent without making any difference in functionality (philosophical zombies), that could change without change in functionality (inverted qualia), or is in principle impossible to observe from any perspective other than the subject’s (Mary’s room). It’s not clear to me what exactly it is we’re talking about here.

This view has epiphenomenal implications, that consciousness is causally impotent, making no difference in the world. It’s interesting that the arguments to avoid this implication inevitably sneak functionality back into the picture. One option, explored by David Chalmers in his book: The Conscious Mind, is that consciousness is causality, which strikes me as a very minimal form of functionalism. Another, one Chalmers favors, is the Russellian monist notion that consciousness, or proto-consciousness, sits in the intrinsic properties of matter, and is basically the causes behind the causes, which again, seem to amount to a form of hidden functionalism.

But these arguments aside, it’s still unclear what exactly it is we’re talking about. It’s frequently admitted that no one can really say what it is. However, it’s typically argued that we can point to various examples to make it clear, such as the redness of an apple, the painfulness of a toothache, seeing black letters on a white page, the taste of a fruit juice, imagining the Eiffel tower, etc.

The thing is, all of these examples strike me as examples of functionality. Redness is a distinction our visual system makes, making something distinct and of high salience, among other likely functions. A toothache obviously is a signal of a problem that needs to be dealt with. Black letters on a white page is pattern recognition to parse symbolic communication. The taste of a drink conveys information about that drink (good=keep drinking, bad=stop and maybe spit out). And remembering past experiences or simulating possible new ones, like imagining the Eiffel tower, has obvious adaptive benefits.

I’ve read enough philosophy to know the usual response. That’s I’m identifying the functional aspects of these experiences, but that the functional description leaves out something crucial. My question is, what? Of course, I know the typical response here too. It’s ineffable. It can’t be described or analyzed. Ok, how do we know it’s there? Each of us supposedly has first person access to it. But I just indicated that my own first person access seems to indicate only functionality. Impasse.

So I’m a functionalist, not just because I think it’s a promising approach, but because I really don’t understand the alternatives. Could I be missing something? If so, what?

#conscioiusness #functionalism #phenomenalConsciousness #Philosophy #PhilosophyOfMind

What is a non-functional account of consciousness supposed to be?

I’m a functionalist. I think the mind and consciousness is about what the brain does, rather than its particular composition, or some other attribute. Which means that if another system did the same or similar things, it would make sense to say it was conscious. Consciousness is as consciousness does.

Functionalism has some advantages over other meta-theories of consciousness. One is that since we’re talking about functionality, of capabilities, establishing consciousness in other species and systems is a matter of establishing what they can do. But it does require accepting that consciousness can come in gradations. And that “consciousness” is not a precise designation of which collection of functionality is required. So it means giving up primitivism about consciousness, accepting that rather than a single natural kind, it’s a hazy collection of many different kinds.

It’s worth pausing to be clear on what functionalism is. It’s about cause-effect relationships. These relationships can, in principle, be modeled by Ramsey sentences, a technique David Lewis adapted from Frank Ramsey, which models a causal sequence, or entire structures of those sequences. (Suzi Travis has an excellent post which includes an introduction to them.) At the heart of the entire enterprise are these cause-effect relations.

Of course, cause-effect relations are themselves emergent from the symmetrical (reversible) structural relations of more fundamental physics. Causes and effects attain their asymmetry due to the Second Law of Thermodynamics, the one that says entropy always increases. So another way to talk about functionalism is in terms of structural realism. Ultimately functionalism is about structural relations. (Something it took me a while to appreciate after discovering structural realism.)

Over the years, I’ve received a lot of different reactions to this position. Not a few aren’t sure what functionalism is. Some are outraged by the idea. Others equate it with behaviorism. (Unlike behaviorism, functionalism accepts the existence of intermediate states between stimuli and response.)

But occasionally someone responds that the idea is obvious and trivial. I think this response is interesting, because I basically agree. It is trivial, or it should be. I only started calling myself a functionalist because so many people insist that the real problem of consciousness isn’t about functionality.

Philosophers have long argued for a version of consciousness that is beyond functionality. Ned Block, when making his distinction between phenomenal and access consciousness, while admitting there were functional notions of phenomenal consciousness, argued for a version that was something other than functionality (or intentionality, which is also relational). And David Chalmers argues that solving the hard problem of consciousness isn’t about solving the structure and relations that science can usually get a handle on.

Anyone who’s known me for a while will be aware that I think these views are mistaken. But I have to admit something. Part of the reason I’m not enthusiastic about them is I don’t even know what a non-functional view of consciousness is supposed to be.

I understand old school interactionist dualism well enough. But in that case there are still causes and effects. It’s just that most of them are hidden from us in some kind of non-physical substrate. But the interaction in interactionist dualism should be detectable by science, and hasn’t been, which I think is why many contemporary non-physicalists gravitate to other options.

It’s when we get to views like property dualism and panpsychism that I start to lose understanding. We’re supposed to be talking about something beyond the functionality, beyond structure and relations, something that could be absent without making any difference in functionality (philosophical zombies), that could change without change in functionality (inverted qualia), or is in principle impossible to observe from any perspective other than the subject’s (Mary’s room). It’s not clear to me what exactly it is we’re talking about here.

This view has epiphenomenal implications, that consciousness is causally impotent, making no difference in the world. It’s interesting that the arguments to avoid this implication inevitably sneak functionality back into the picture. One option, explored by David Chalmers in his book: The Conscious Mind, is that consciousness is causality, which strikes me as a very minimal form of functionalism. Another, one Chalmers favors, is the Russellian monist notion that consciousness, or proto-consciousness, sits in the intrinsic properties of matter, and is basically the causes behind the causes, which again, seem to amount to a form of hidden functionalism.

But these arguments aside, it’s still unclear what exactly it is we’re talking about. It’s frequently admitted that no one can really say what it is. However, it’s typically argued that we can point to various examples to make it clear, such as the redness of an apple, the painfulness of a toothache, seeing black letters on a white page, the taste of a fruit juice, imagining the Eiffel tower, etc.

The thing is, all of these examples strike me as examples of functionality. Redness is a distinction our visual system makes, making something distinct and of high salience, among other likely functions. A toothache obviously is a signal of a problem that needs to be dealt with. Black letters on a white page is pattern recognition to parse symbolic communication. The taste of a drink conveys information about that drink (good=keep drinking, bad=stop and maybe spit out). And remembering past experiences or simulating possible new ones, like imagining the Eiffel tower, has obvious adaptive benefits.

I’ve read enough philosophy to know the usual response. That’s I’m identifying the functional aspects of these experiences, but that the functional description leaves out something crucial. My question is, what? Of course, I know the typical response here too. It’s ineffable. It can’t be described or analyzed. Ok, how do we know it’s there? Each of us supposedly has first person access to it. But I just indicated that my own first person access seems to indicate only functionality. Impasse.

So I’m a functionalist, not just because I think it’s a promising approach, but because I really don’t understand the alternatives. Could I be missing something? If so, what?

#conscioiusness #functionalism #phenomenalConsciousness #Philosophy #PhilosophyOfMind

What is a non-functional account of consciousness supposed to be?

I’m a functionalist. I think the mind and consciousness is about what the brain does, rather than its particular composition, or some other attribute. Which means that if another system did the same or similar things, it would make sense to say it was conscious. Consciousness is as consciousness does.

Functionalism has some advantages over other meta-theories of consciousness. One is that since we’re talking about functionality, of capabilities, establishing consciousness in other species and systems is a matter of establishing what they can do. But it does require accepting that consciousness can come in gradations. And that “consciousness” is not a precise designation of which collection of functionality is required. So it means giving up primitivism about consciousness, accepting that rather than a single natural kind, it’s a hazy collection of many different kinds.

It’s worth pausing to be clear on what functionalism is. It’s about cause-effect relationships. These relationships can, in principle, be modeled by Ramsey sentences, a technique David Lewis adapted from Frank Ramsey, which models a causal sequence, or entire structures of those sequences. (Suzi Travis has an excellent post which includes an introduction to them.) At the heart of the entire enterprise are these cause-effect relations.

Of course, cause-effect relations are themselves emergent from the symmetrical (reversible) structural relations of more fundamental physics. Causes and effects attain their asymmetry due to the Second Law of Thermodynamics, the one that says entropy always increases. So another way to talk about functionalism is in terms of structural realism. Ultimately functionalism is about structural relations. (Something it took me a while to appreciate after discovering structural realism.)

Over the years, I’ve received a lot of different reactions to this position. Not a few aren’t sure what functionalism is. Some are outraged by the idea. Others equate it with behaviorism. (Unlike behaviorism, functionalism accepts the existence of intermediate states between stimuli and response.)

But occasionally someone responds that the idea is obvious and trivial. I think this response is interesting, because I basically agree. It is trivial, or it should be. I only started calling myself a functionalist because so many people insist that the real problem of consciousness isn’t about functionality.

Philosophers have long argued for a version of consciousness that is beyond functionality. Ned Block, when making his distinction between phenomenal and access consciousness, while admitting there were functional notions of phenomenal consciousness, argued for a version that was something other than functionality (or intentionality, which is also relational). And David Chalmers argues that solving the hard problem of consciousness isn’t about solving the structure and relations that science can usually get a handle on.

Anyone who’s known me for a while will be aware that I think these views are mistaken. But I have to admit something. Part of the reason I’m not enthusiastic about them is I don’t even know what a non-functional view of consciousness is supposed to be.

I understand old school interactionist dualism well enough. But in that case there are still causes and effects. It’s just that most of them are hidden from us in some kind of non-physical substrate. But the interaction in interactionist dualism should be detectable by science, and hasn’t been, which I think is why many contemporary non-physicalists gravitate to other options.

It’s when we get to views like property dualism and panpsychism that I start to lose understanding. We’re supposed to be talking about something beyond the functionality, beyond structure and relations, something that could be absent without making any difference in functionality (philosophical zombies), that could change without change in functionality (inverted qualia), or is in principle impossible to observe from any perspective other than the subject’s (Mary’s room). It’s not clear to me what exactly it is we’re talking about here.

This view has epiphenomenal implications, that consciousness is causally impotent, making no difference in the world. It’s interesting that the arguments to avoid this implication inevitably sneak functionality back into the picture. One option, explored by David Chalmers in his book: The Conscious Mind, is that consciousness is causality, which strikes me as a very minimal form of functionalism. Another, one Chalmers favors, is the Russellian monist notion that consciousness, or proto-consciousness, sits in the intrinsic properties of matter, and is basically the causes behind the causes, which again, seem to amount to a form of hidden functionalism.

But these arguments aside, it’s still unclear what exactly it is we’re talking about. It’s frequently admitted that no one can really say what it is. However, it’s typically argued that we can point to various examples to make it clear, such as the redness of an apple, the painfulness of a toothache, seeing black letters on a white page, the taste of a fruit juice, imagining the Eiffel tower, etc.

The thing is, all of these examples strike me as examples of functionality. Redness is a distinction our visual system makes, making something distinct and of high salience, among other likely functions. A toothache obviously is a signal of a problem that needs to be dealt with. Black letters on a white page is pattern recognition to parse symbolic communication. The taste of a drink conveys information about that drink (good=keep drinking, bad=stop and maybe spit out). And remembering past experiences or simulating possible new ones, like imagining the Eiffel tower, has obvious adaptive benefits.

I’ve read enough philosophy to know the usual response. That’s I’m identifying the functional aspects of these experiences, but that the functional description leaves out something crucial. My question is, what? Of course, I know the typical response here too. It’s ineffable. It can’t be described or analyzed. Ok, how do we know it’s there? Each of us supposedly has first person access to it. But I just indicated that my own first person access seems to indicate only functionality. Impasse.

So I’m a functionalist, not just because I think it’s a promising approach, but because I really don’t understand the alternatives. Could I be missing something? If so, what?

#conscioiusness #functionalism #phenomenalConsciousness #Philosophy #PhilosophyOfMind

What is a non-functional account of consciousness supposed to be?

I’m a functionalist. I think the mind and consciousness is about what the brain does, rather than its particular composition, or some other attribute. Which means that if another system did the same or similar things, it would make sense to say it was conscious. Consciousness is as consciousness does.

Functionalism has some advantages over other meta-theories of consciousness. One is that since we’re talking about functionality, of capabilities, establishing consciousness in other species and systems is a matter of establishing what they can do. But it does require accepting that consciousness can come in gradations. And that “consciousness” is not a precise designation of which collection of functionality is required. So it means giving up primitivism about consciousness, accepting that rather than a single natural kind, it’s a hazy collection of many different kinds.

It’s worth pausing to be clear on what functionalism is. It’s about cause-effect relationships. These relationships can, in principle, be modeled by Ramsey sentences, a technique David Lewis adapted from Frank Ramsey, which models a causal sequence, or entire structures of those sequences. (Suzi Travis has an excellent post which includes an introduction to them.) At the heart of the entire enterprise are these cause-effect relations.

Of course, cause-effect relations are themselves emergent from the symmetrical (reversible) structural relations of more fundamental physics. Causes and effects attain their asymmetry due to the Second Law of Thermodynamics, the one that says entropy always increases. So another way to talk about functionalism is in terms of structural realism. Ultimately functionalism is about structural relations. (Something it took me a while to appreciate after discovering structural realism.)

Over the years, I’ve received a lot of different reactions to this position. Not a few aren’t sure what functionalism is. Some are outraged by the idea. Others equate it with behaviorism. (Unlike behaviorism, functionalism accepts the existence of intermediate states between stimuli and response.)

But occasionally someone responds that the idea is obvious and trivial. I think this response is interesting, because I basically agree. It is trivial, or it should be. I only started calling myself a functionalist because so many people insist that the real problem of consciousness isn’t about functionality.

Philosophers have long argued for a version of consciousness that is beyond functionality. Ned Block, when making his distinction between phenomenal and access consciousness, while admitting there were functional notions of phenomenal consciousness, argued for a version that was something other than functionality (or intentionality, which is also relational). And David Chalmers argues that solving the hard problem of consciousness isn’t about solving the structure and relations that science can usually get a handle on.

Anyone who’s known me for a while will be aware that I think these views are mistaken. But I have to admit something. Part of the reason I’m not enthusiastic about them is I don’t even know what a non-functional view of consciousness is supposed to be.

I understand old school interactionist dualism well enough. But in that case there are still causes and effects. It’s just that most of them are hidden from us in some kind of non-physical substrate. But the interaction in interactionist dualism should be detectable by science, and hasn’t been, which I think is why many contemporary non-physicalists gravitate to other options.

It’s when we get to views like property dualism and panpsychism that I start to lose understanding. We’re supposed to be talking about something beyond the functionality, beyond structure and relations, something that could be absent without making any difference in functionality (philosophical zombies), that could change without change in functionality (inverted qualia), or is in principle impossible to observe from any perspective other than the subject’s (Mary’s room). It’s not clear to me what exactly it is we’re talking about here.

This view has epiphenomenal implications, that consciousness is causally impotent, making no difference in the world. It’s interesting that the arguments to avoid this implication inevitably sneak functionality back into the picture. One option, explored by David Chalmers in his book: The Conscious Mind, is that consciousness is causality, which strikes me as a very minimal form of functionalism. Another, one Chalmers favors, is the Russellian monist notion that consciousness, or proto-consciousness, sits in the intrinsic properties of matter, and is basically the causes behind the causes, which again, seem to amount to a form of hidden functionalism.

But these arguments aside, it’s still unclear what exactly it is we’re talking about. It’s frequently admitted that no one can really say what it is. However, it’s typically argued that we can point to various examples to make it clear, such as the redness of an apple, the painfulness of a toothache, seeing black letters on a white page, the taste of a fruit juice, imagining the Eiffel tower, etc.

The thing is, all of these examples strike me as examples of functionality. Redness is a distinction our visual system makes, making something distinct and of high salience, among other likely functions. A toothache obviously is a signal of a problem that needs to be dealt with. Black letters on a white page is pattern recognition to parse symbolic communication. The taste of a drink conveys information about that drink (good=keep drinking, bad=stop and maybe spit out). And remembering past experiences or simulating possible new ones, like imagining the Eiffel tower, has obvious adaptive benefits.

I’ve read enough philosophy to know the usual response. That’s I’m identifying the functional aspects of these experiences, but that the functional description leaves out something crucial. My question is, what? Of course, I know the typical response here too. It’s ineffable. It can’t be described or analyzed. Ok, how do we know it’s there? Each of us supposedly has first person access to it. But I just indicated that my own first person access seems to indicate only functionality. Impasse.

So I’m a functionalist, not just because I think it’s a promising approach, but because I really don’t understand the alternatives. Could I be missing something? If so, what?

#conscioiusness #functionalism #phenomenalConsciousness #Philosophy #PhilosophyOfMind

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#zeppelin #romanianarchitecture #modernism #film #documentary #architecturefilm #architectureinromania #socmod #socialistmodernism #postwararchitecture #functionalism #modernclassic #citeradieuse #commercialcomplex #zeppelinmagazine #zeppelinoverbucharest #zeppelincities #zeppelin❤️this
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Swedish #functionalism This was the first functionalist house to be built in Örebro in an area otherwise filled with Jugend houses. #photography #silentsunday #architecture

Swedish #functionalism This was the first functionalist house to be built in Örebro in an area otherwise filled with Jugend houses. #photography #silentsunday #architecture