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Is Consciousness Nothing More Than Organized Information? · The Last Observer: Science and Beyond

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  Speaker 1: I want you to take just a second, right now,
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  Speaker 1: wherever you are, and just notice the sheer feeling of
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  Speaker 1: being alive is completely Pause, yeah, pause, and really look
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  Speaker 1: at the colors in the room around you, like, really
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  Speaker 1: look at them.
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  Speaker 2: Pay attention to the light exactly.
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  Speaker 1: And listen to the specific timber of the audio playing
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  Speaker 1: in your.
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  Speaker 2: Ears right now, or even just the you know, the
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  Speaker 2: ambient hum of the space you're in.
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  Speaker 1: Right right, and maybe most incredibly, I want you to
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  Speaker 1: pay attention to the inner monologue happening inside your head
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  Speaker 1: at this exact second, that voice, that internal voice, that
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  Speaker 1: that localized sense of awareness looking out from behind your eyes.
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  Speaker 1: What exactly is that subjective experience?
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  Speaker 2: Honestly, it remains the ultimate mystery. I mean it really does.
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  Speaker 2: It's wild because science is well, we're phenomenally good at
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  Speaker 2: describing the physical properties of your environment, sure, like the
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  Speaker 2: physics of it exactly. We can measure the exact nanometer
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  Speaker 2: wavelengths of light bouncing off your.
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  Speaker 1: Walls, or like the decibel level you know, the frequent
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  Speaker 1: the sound waves that are hitting your ear drums right
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  Speaker 1: this second.
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  Speaker 2: Yeah, we can even map the electrical spikes traversing your optic.
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  Speaker 3: Nerve in real time, which is amazing.
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  Speaker 2: But none of those physical objective descriptions actually capture what
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  Speaker 2: it feels like to experience them. The visceral, undeniable redness
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  Speaker 2: of red, you know.
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  Speaker 1: Or the sharpness of a cold wind.
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  Speaker 2: On your face, exactly the feeling itself.
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  Speaker 1: Which is crazy when you think about it. Yeah, I mean,
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  Speaker 1: we can explain the birth of black.
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  Speaker 2: Holes, we can track subatomic particles.
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  Speaker 1: Yeah, But the one thing you are most intimately familiar with,
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  Speaker 1: like your own awareness, it completely defies basic physical description.
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  Speaker 2: It totally does. And you know, for centuries humanity has
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  Speaker 2: basically been stuck oscillating between two extreme and frankly, really
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  Speaker 2: frustrating explanations for this totally.
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  Speaker 1: So, on one hand, you had the classic the ghost
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  Speaker 1: in the.
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  Speaker 2: Machine theory, right, the dualist perspective. Renada cart famously championed
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  Speaker 2: this back in the seventeenth century.
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  Speaker 1: I remember this from Philosophy one on one.
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  Speaker 2: Yah, So Descartes basically argued that the universe is made
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  Speaker 2: of two. You have physical matter, which takes up space
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  Speaker 2: and obeys mechanical laws.
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  Speaker 3: And then you have this thinking substance like the mind.
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  Speaker 2: Exactly, the mind, which is completely immaterial and It's.
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  Speaker 1: An incredibly intuitive way to look at it too, Like
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  Speaker 1: when I imagine a purple elephant right now, that thought doesn't.
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  Speaker 2: Have mass, No, it doesn't.
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  Speaker 1: It doesn't have physical dimensions. It feels entirely separate from
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  Speaker 1: the heavy, physical meat and bone of my body.
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  Speaker 2: It feels like magic.
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  Speaker 1: Yeah, a spirit inhabiting a biological space suit.
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  Speaker 2: It feels that way, sure, But from a scientific and
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  Speaker 2: physical standpoint, it's a complete dead end.
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  Speaker 1: Why is it a dead end?
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  Speaker 2: Well, the fatal flaw of dualism, the whole ghost in
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  Speaker 2: the machine idea, is what we call the interaction problem.
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  Speaker 1: The interaction problem.
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  Speaker 2: Right, if the mind is entirely immaterial, like, if it
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  Speaker 2: lacks any physical properties or energy, how can it possibly
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  Speaker 2: cause a physical change in the universe?
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  Speaker 1: Oh? I see?
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  Speaker 2: How does an a ethereal weightless ghost tell physical neurons to.
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  Speaker 1: Fire, which then contract physical muscle fibers to like raise
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  Speaker 1: your arm?
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  Speaker 2: Exactly? The laws of physics, specifically the conservation of energy,
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  Speaker 2: they just don't allow for magical, uncaused physical actions.
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  Speaker 1: So, frustrated by that massive logical pothole, modern science just
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  Speaker 1: kind of swung wildly in the completely opposite direction.
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  Speaker 2: Almost violently in the opposite direction.
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  Speaker 1: Right, as we map the brain and realized how mechanistic
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  Speaker 1: it all is, we got this new perspective that consciousness
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  Speaker 1: is just well, it's an inert, accidental byproduct of brain activity.
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  Speaker 2: Epiphenomenalism, ephenomenalism.
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  Speaker 3: Right.
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  Speaker 2: The nineteenth century biologist Thomas Huxley gave us a really
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  Speaker 2: rather bleak analogy for this.
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  Speaker 1: Oh yeah, the train one.
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  Speaker 2: Yeah. He compared consciousness to the steam whistle on a
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  Speaker 2: locomotive engine.
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  Speaker 1: Okay, so how does that work?
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  Speaker 2: Well, the whistle is allowed, it makes a lot of noise,
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  Speaker 2: but it has absolutely no part in the machinery that
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  Speaker 2: actually drives the tree forward.
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  Speaker 1: It's just exhaust.
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  Speaker 2: It's literally just exhaust.
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  Speaker 1: Meaning your inner life, like your feelings, your deep sense
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  Speaker 1: of self. You're agonizing over decisions. It doesn't actually do anything,
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  Speaker 1: nothing at all. Your brain makes the decision mechanically, and
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  Speaker 1: then your consciousness just sort of, I don't know, watches
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  Speaker 1: it happen and tricks itself into thinking you as in charge.
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  Speaker 2: You're essentially a meat robot heat robot. Wow, and your
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  Speaker 2: awareness is just a meaningless accident of biology.
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  Speaker 1: Which is profoundly depressing.
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  Speaker 2: Way look, at it at highly counterintuitive to view human
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  Speaker 2: existence that way.
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  Speaker 1: Yeah, because it demands that you believe the one and
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  Speaker 1: only thing you could be absolutely certain of in this universe,
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  Speaker 1: your own subjective felt experience is practically irrelevant. Right.
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  Speaker 2: But the good news is we do not have to
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  Speaker 2: accept either of those extremes.
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  Speaker 1: We don't have to choose between literal magic and meaningless
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  Speaker 1: exhaust thankfully.
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  Speaker 2: No, there is a really compelling third paradigm, okay, one
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  Speaker 2: that bridges theoretical neuroscience, information theory, and cognitive science.
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  Speaker 1: And so that's our mission today. We are going to
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  Speaker 1: explore how subjective awareness is an emergent property of self
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  Speaker 1: referential information processing.
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  Speaker 2: It requires a fundamental shift in how we define what
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  Speaker 2: a mind is. We have to move away from what
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  Speaker 2: a system is made of to how it shares and
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  Speaker 2: integrates information with itself.
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  Speaker 1: And the core concept we're going to unravel today is recursion.
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  Speaker 3: Recursion.
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  Speaker 1: Yes, we're looking at what happens when a highly complex
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  Speaker 1: computational system stops just receiving external inputs like you know,
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  Speaker 1: a camera passively taking a picture, and starts feeding its
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  Speaker 1: own internal representations back into itself.
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  Speaker 2: It creates a recursive loop, a hall of mirrors exactly,
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  Speaker 2: and when that loop reaches a specific threshold of density
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  Speaker 2: and complexity, the system wakes up. It wakes up. Today,
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  Speaker 2: we are going to unpack the biological and mathematical architecture
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  Speaker 2: of what it actually feels like when an information system
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  Speaker 2: looks in the mirror.
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  Speaker 1: So to even begin to understand how mirror information processing
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  Speaker 1: can crystallize into a self, we first need a way
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  Speaker 1: to measure and define this integration. Right.
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  Speaker 2: Yes, we have to make a very difficult leap from
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  Speaker 2: abstract philosophical debates about the soul to rigorous, testable mathematics.
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  Speaker 1: We basically have to calculate the soul.
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  Speaker 2: That's one way to put it. Yeah, and that brings
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  Speaker 2: us to Julio Tononi's integrated information theory.
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  Speaker 1: I it I it right.
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  Speaker 3: So.
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  Speaker 2: Toni is a neuroscientist and psychiatrist, and he spent a
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  Speaker 2: massive portion of his career studying sleep.
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  Speaker 1: Which makes sense.
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  Speaker 2: It's the perfect laboratory for consciousness because your brain doesn't
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  Speaker 2: turn off when you go into dreamless sleep.
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  Speaker 1: Right, It's not like your brain goes dead.
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  Speaker 2: No, it's still highly active, yet your consciousness completely vanishes.
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  Speaker 1: So he was looking for the missing piece.
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  Speaker 2: Exactly Toinoni wanted to know what specific mathematical property was
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  Speaker 2: disappearing when you lost consciousness, even while the neurons were
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  Speaker 2: still firing. Interesting and this led to a massive perspective
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  Speaker 2: shift because raditionally in computer science, biology, and especially in
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  Speaker 2: tests like the Turing test, we try to understand a
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  Speaker 2: system by looking at its functional behavior.
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  Speaker 3: It's output, right, it's output.
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  Speaker 1: Input, computation output, the vending.
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  Speaker 2: Machine model, the vending machine model.
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  Speaker 1: Yes, you put a coin in the gears, turn, the
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  Speaker 1: soda drops out. We judge the machine by what it does.
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  Speaker 2: And it argues that this is the entirely wrong way
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  Speaker 2: to look for consciousness. Why because you cannot measure awareness
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  Speaker 2: by observing behavior from the outside. To understand consciousness, you
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  Speaker 2: have to look at what a system is. What it is,
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  Speaker 2: You have to examine its intrinsic causal structure.
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  Speaker 1: Intrinsic causal structure.
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  Speaker 2: It's not about the behavior of the system exhibits to
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  Speaker 2: the world. It's about how the system exists for itself
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  Speaker 2: from the inside.
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  Speaker 1: Okay, let's ground that. What does it actually mean for
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  Speaker 1: a network of neurons or you know, computer chips for
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  Speaker 1: that matter, to have an intrinsic causal structure.
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  Speaker 2: It comes down to cause effect.
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  Speaker 1: Power, cause effect power.
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  Speaker 2: Right. For a system to possess content sciousness, its present
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  Speaker 2: state must rigidly and powerfully constrain both its past and
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  Speaker 2: its future.
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  Speaker 1: H im. We need an example.
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  Speaker 2: Imagine looking at the exact frozen state of a complex
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  Speaker 2: system right now, like.
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  Speaker 3: Take a snapshot.
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  Speaker 1: Okay, get the snapshot.
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  Speaker 2: If it has high intrinsic causality, that current state dictates
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  Speaker 2: that only a very specific set of past states could
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  Speaker 2: have possibly caused it. Ah, I see, And simultaneously, this
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  Speaker 2: current state must strongly dictate what the very next future
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  Speaker 2: state will be.
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  Speaker 1: So the system is inextricably woven into its own timeline exactly.
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  Speaker 2: The components aren't just reacting to outside forces. They are
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  Speaker 2: heavily pushing and pulling on one another. The system has
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  Speaker 2: causal power over itself.
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  Speaker 1: Okay, so it's a tight knit web. Like if one
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  Speaker 1: node in the network fires, it forces a very specific
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  Speaker 1: cascade of events yes, which then feedback and force the
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  Speaker 1: first node to act differently in the very next mill second.
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  Speaker 3: That's exactly it, and it puts.
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  Speaker 1: A mathematical metric on this integration. Right, the threshold of five.
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  Speaker 2: Degree clarify, Yeah, represented as the symbol FI. It is
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  Speaker 2: the proposed quantitative metric of consciousness.
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  Speaker 1: And how do you calculate it?
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  Speaker 2: Well, the way you calculate it, which I should know,
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  Speaker 2: is mathematically monumental for complex systems like it requires immense
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  Speaker 2: computing power just to estimate is by analyzing the network
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  Speaker 2: and looking for its weakest link. You essentially ask, can
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  Speaker 2: I mathematically cut this system in.
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  Speaker 1: Half the minimum information partition?
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  Speaker 2: Yes, you partition the system into completely independent subcomponents. And
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  Speaker 2: if you find that the total information structure of the
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  Speaker 2: severed system remains perfectly identical to when it was whole,
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  Speaker 2: then FI equals zero.
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  Speaker 1: Meaning the parts weren't actually talking to each other in
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  Speaker 1: a meaningful, integrated way to begin with.
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  Speaker 2: Precisely, if cutting the connections between the two halves doesn't
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  Speaker 2: change the underlying causal dynamics of the system, there was
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  Speaker 2: no integrated unity.
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  Speaker 1: It was just like a collection of independent things happening
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  Speaker 1: next to each other in.
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  Speaker 3: Space, exactly.
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  Speaker 2: And if there is no integrated unity, there is no
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  Speaker 2: single unify entity to have an experience.
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  Speaker 1: So FI equal zero means zero consciousness.
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  Speaker 2: Zero consciousness.
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  Speaker 1: Let me try to visualize this. A system with a
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  Speaker 1: five zero is like a massive choir where every single
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  Speaker 1: singer is wearing heavy noise canceling headphones.
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  Speaker 2: I like this, okay.
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  Speaker 1: So they're all standing on the same stage. They might
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  Speaker 1: even be singing the exact same song at the exact
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  Speaker 1: same time because they're reading the same sheet music, right,
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  Speaker 1: but they aren't interacting. Like if you were to drop
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  Speaker 1: a soundproof glass wall right down the middle of the
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  Speaker 1: stage separating the sopranos from the tenors, nothing about their
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  Speaker 1: individual behavior changes, nothing at all. The sopranos don't alter
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  Speaker 1: their pitch because they couldn't hear the tenors anyway. They
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  Speaker 1: don't constrain each other.
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  Speaker 2: That is a brilliant way to picture it. There is
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  Speaker 2: no unified, overarching song being created in the causal space
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  Speaker 2: between them, right. There are only individual voices operating in
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  Speaker 2: complete isolation, just blindly following their own script.
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  Speaker 1: But a system with a massive non zero five is
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  Speaker 1: like a old class jazz quartet in the middle of
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  Speaker 1: a heavy improvisation.
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  Speaker 2: Session, oh exact.
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  Speaker 1: Because they aren't reading sheet music, every single note the
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  Speaker 1: basses plays is completely constrained by and responding to the
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  Speaker 1: weird rhythmic syncopation. The drummer just threw in, which.
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  Speaker 2: In turn immediately changes the melody. The sex soophonist decides
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  Speaker 2: to blow.
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  Speaker 1: Right, They're completely intertwined. Yes, If you dropped a soundproof
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  Speaker 1: wall in the middle of that jazz quartet, the entire
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  Speaker 1: structure of the music would instantly collapse.
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  Speaker 2: The music would completely dissolve into noise. The jazz quartet
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  Speaker 2: exists as a unified, indivisible whole.
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  Speaker 1: Yeah.
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  Speaker 2: The cause effect repertoire of that quartet holds vastly more
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  Speaker 2: information than you could ever get by simply adding up
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  Speaker 2: the isolated knowledge of the four musicians. Wow, and this
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  Speaker 2: brings us directly to the phenomenological postulates of it.
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  Speaker 1: Big words.
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  Speaker 2: Yeah, but it's just the theory taking these dense mathematical
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  Speaker 2: realities and mapping them directly onto the raw feeling of
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  Speaker 2: being alive.
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  Speaker 1: The fundamental rules of what an experience actually is.
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  Speaker 2: Right, it identifies a few non negotiable qualities of subjective awareness. First,
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  Speaker 2: it must be intrinsic, meaning the experience exists purely for
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  Speaker 2: the system itself from its own perspective.
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  Speaker 1: Okay, not for an outside observer looking at an.
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  Speaker 3: fMRI scan exactly.
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  Speaker 2: Second, it is highly structured. Think about your experience right now.
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  Speaker 2: It is composed of incredibly distinct, differentiated features.
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  Speaker 1: No specific geometry of the room.
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  Speaker 2: The contrast of light and shadow, the semantic meaning of
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  Speaker 2: the words you are hearing. It is not just a
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  Speaker 2: uniform blur.
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  Speaker 1: But at the same time, and this is the third postula, right, yeah,
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  Speaker 1: it is unified.
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  Speaker 2: It is entirely indivisible. You cannot experience the left half
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  Speaker 2: of your visual field independently of the right half.
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  Speaker 1: No, I can.
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  Speaker 2: You cannot separate the sound of my voice from the
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  Speaker 2: feeling of the chair you are sitting in. It all
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  Speaker 2: arrives as one single, cohesive frame of reality.
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  Speaker 1: So when a network has these incredibly dense reciprocal feedback
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  Speaker 1: pathways like the Jazz quartet, all those intersecting causes and
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  Speaker 1: effects create this massive, indivisible mathematical structure.
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  Speaker 2: And this is perhaps the most difficult but vital concept
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  Speaker 2: in the entire theory.
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  Speaker 1: What's it?
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  Speaker 2: The geometry of this integrated structure is the subjective feeling? Wait,
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  Speaker 2: what the experience of seeing the color red or tasting
• 13:15
  Speaker 2: a lemon isn't a little picture of a lemon projected
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  Speaker 2: onto a movie screen somewhere inside your brain.
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  Speaker 1: It's not.
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  Speaker 2: No, it is the specific multidimensional geometric shape of the
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  Speaker 2: information constraints happening in your neural network at that exact millisecond.
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  Speaker 1: Oh my god.
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  Speaker 2: The shape of the data is the taste of the lemon.
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  Speaker 1: Okay, let me stop you right there. Because if consciousness
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  Speaker 1: is just about the mathematical integration of information, the density
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  Speaker 1: of this causal web, I have to ask the obvious
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  Speaker 1: question here go for it. Does this mean a complex
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  Speaker 1: enough Excel spreadsheet could theoretically have a non zero five?
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  Speaker 1: Like if I am a master coder and I build
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  Speaker 1: a spreadsheet where every single cell references a dozen other
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  Speaker 1: cells in this massive, un breakable recursive loop of logic. Right,
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  Speaker 1: does Microsoft Excel wake up? Does my laptop start having
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  Speaker 1: a subjective experience of spreadsheet anxiety?
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  Speaker 2: It's the classic objection to information based theories of mind
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  Speaker 2: and understanding. The answer is totally crucial to grasping what
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  Speaker 2: it actually proposes.
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  Speaker 1: Okay, so what's the answer.
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  Speaker 2: The short answer is no, your recursive Excel spreadsheet is
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  Speaker 2: not conscious. It has a five zero.
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  Speaker 1: But why it's processing highly integrated information?
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  Speaker 2: It fits the math because there is a vast fundamental
• 14:28
  Speaker 2: difference between a software simulation of integration and actual physical
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  Speaker 2: intrinsic causal structure. Your Excel spreadsheet is just software. It's
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  Speaker 2: a map, it's a set of instructions. The actual physical
• 14:40
  Speaker 2: work of calculating those cells is being done by the
• 14:43
  Speaker 2: microscopic transistors in your computer's CPU.
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  Speaker 1: Right.
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  Speaker 2: The hardware and a traditional CPU operates on what is
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  Speaker 2: called a von Neuman architecture von Neumann. Yeah, it processes
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  Speaker 2: information in a completely linear sequential way. The processor is
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  Speaker 2: just fetching one instruction from memory, executing it, storing the result,
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  Speaker 2: and moving to the next. The software might represent a
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  Speaker 2: dense recursive loop of dependencies, but the hardware executing it
• 15:10
  Speaker 2: is just flipping physical switches on and off one at
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  Speaker 2: a time in isolation.
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  Speaker 1: Ah, I see, It's like it's like playing a video
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  Speaker 1: game about a hurricane exactly. The simulation of the rainstorm
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  Speaker 1: is incredibly complex, with millions of variables interacting on the screen,
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  Speaker 1: but it doesn't actually make the inside of the computer wet.
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  Speaker 2: The map is not the territory. To generate high FI.
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  Speaker 2: The system must physically possess that intrinsic causal power. The
• 15:34
  Speaker 2: physical architecture itself. The actual wiring must be integrated, So.
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  Speaker 1: You cannot simulate integration in code on a linear processor
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  Speaker 1: and expected to wake up.
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  Speaker 3: You really can't, Which means we.
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  Speaker 1: Need to look at how organic biology actually builds this architecture. Yes,
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  Speaker 1: we need to transition from the theoretical map of FI
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  Speaker 1: and look at the wet, messy physical wiring of the
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  Speaker 1: human brain. Because the brain is decidedly not linear CPU,
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  Speaker 1: not even.
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  Speaker 2: Close to truly appreciate how bizarre and unique biological neural
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  Speaker 2: wiring is. We should contrast it with the most advanced
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  Speaker 2: artificial systems we build today.
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  Speaker 1: Okay, let's do that.
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  Speaker 2: Think about standard artificial neural networks, the kind of deep
• 16:15
  Speaker 2: learning AI used for image recognition or language processing.
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  Speaker 1: Like the AI models that can scan a medical image
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  Speaker 1: and spot a tumor right, or look at a photo
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  Speaker 1: and categorize it as a cat or a dog.
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  Speaker 2: These systems are by and large strictly feed forward architectures.
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  Speaker 1: Forward meaning the flow of.
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  Speaker 2: Information travels in one direction only. It starts at the
• 16:34
  Speaker 2: input sensors, the raw pixels of the image. That data
• 16:38
  Speaker 2: is pushed forward into the first hidden layer of artificial neurons,
• 16:41
  Speaker 2: which extract simple features like edges. Edges sure that layer
• 16:46
  Speaker 2: pushes forward to the next, identifying shapes, and so on,
• 16:49
  Speaker 2: doing incredibly complex matrix multiplication along the way until it
• 16:53
  Speaker 2: finally hits the output layer cat or dog.
• 16:56
  Speaker 1: Input process output a straight, one way.
• 16:59
  Speaker 2: Street, highly linear. Now, these feed forward networks are powerful.
• 17:03
  Speaker 2: I mean they can execute classifications that sometimes surpass human accuracy.
• 17:08
  Speaker 2: But they operate completely in the dark. They possess absolutely
• 17:11
  Speaker 2: zero phenomenology.
• 17:13
  Speaker 1: Zero subjective experience, none, computation in the dark. I love
• 17:17
  Speaker 1: that phraser, but beyond just lacking five why is a
• 17:21
  Speaker 1: feed forward network in the dark.
• 17:23
  Speaker 2: Because there is never a moment where the system's output
• 17:26
  Speaker 2: becomes part of its own input. AI identifies a cat,
• 17:30
  Speaker 2: but it never observes itself identifying the cat. It doesn't
• 17:33
  Speaker 2: know it just did.
• 17:33
  Speaker 3: Something because it's a one way street.
• 17:35
  Speaker 2: Because the connections only go one way. It has no
• 17:37
  Speaker 2: intrinsic state that drives its future state. The moment you
• 17:40
  Speaker 2: stop feeding at images, the system is completely dead quiet.
• 17:44
  Speaker 2: It has no internal life.
• 17:45
  Speaker 1: Wow. Compare that to the biological reality inside our skulls.
• 17:49
  Speaker 2: The contrast is just staggering. The human brain is a tangled,
• 17:54
  Speaker 2: chaotic web of recurrent looping connections. Let's look at a
• 17:59
  Speaker 2: specific anatomy example. Okay, the visual processing system, light hits
• 18:03
  Speaker 2: your retina and travels down the optic nerve to the
• 18:06
  Speaker 2: lateral geniculate nucleus, a relay center, and then up to
• 18:09
  Speaker 2: the primary visual cortex at the back of your head.
• 18:12
  Speaker 1: Okay, so logically you would think the vast majority of
• 18:14
  Speaker 1: the neural pathways would be bottom up feed forward pathways,
• 18:18
  Speaker 1: carrying the raw visual data from your eyes up into
• 18:21
  Speaker 1: the higher processing centers of the brain to be analyzed.
• 18:24
  Speaker 2: That's the intuitive assumption. The eye acts as the camera,
• 18:27
  Speaker 2: It takes a picture, and it sends the heavy data
• 18:29
  Speaker 2: file up the wire to the brain for processing exactly.
• 18:32
  Speaker 2: But neuroanatomy shows us the exact opposite.
• 18:35
  Speaker 1: Wait really, yeah.
• 18:36
  Speaker 2: In the visual system, the top down pathways, the feedback
• 18:39
  Speaker 2: connections coming from the higher abstract thinking areas of the
• 18:42
  Speaker 2: brain down to the lower sensory relay areas vastly outnumber
• 18:46
  Speaker 2: the bottom up pathways.
• 18:47
  Speaker 1: Were kidding.
• 18:48
  Speaker 2: In some areas, for every one nerve fiber bringing sensory
• 18:51
  Speaker 2: data up from the eye, there are ten fibers sending
• 18:54
  Speaker 2: information down from the cortex.
• 18:56
  Speaker 1: Wait. Wait, the brain is sending ten times more information
• 19:00
  Speaker 1: down to the visual relay stations, and the eyes are sending.
• 19:02
  Speaker 2: Up to the brain ten to one.
• 19:04
  Speaker 1: What is all that downward data doing.
• 19:06
  Speaker 2: It is constantly modifying, filtering, and predicting the incoming signal
• 19:11
  Speaker 2: before it even reaches conscious awareness.
• 19:13
  Speaker 1: Oh wow.
• 19:14
  Speaker 2: The biological brain is absolutely dominated by these recurrent reciprocal connections.
• 19:19
  Speaker 2: This anatomical reality is what led the Nobel Prize winning
• 19:23
  Speaker 2: cognitive scientist Gerald Edelman to develop the concept of reentrancy.
• 19:27
  Speaker 1: Reentrancy let's break down how Edelman envisioned this.
• 19:30
  Speaker 2: Edelman realized that the brain doesn't have a central command center.
• 19:33
  Speaker 2: There is no CPU, no little guys sitting in a
• 19:36
  Speaker 2: control room exactly. Instead, you have dozens of different, highly
• 19:40
  Speaker 2: specialized neuronal maps distributed across the cortex. One physical area
• 19:45
  Speaker 2: is dedicated to processing motions, a completely separate area processes color,
• 19:50
  Speaker 2: another handles memory, another emotion another spatial orientation. Edelman's reentrancy
• 19:55
  Speaker 2: is the continuous, parallel, bidirectional exchange of signals between all
• 20:00
  Speaker 2: these separate neuronal maps across those massive reciprocal connections.
• 20:04
  Speaker 1: So instead of the color area doing its job and
• 20:07
  Speaker 1: passing the baton to the motion area in a neat
• 20:09
  Speaker 1: little assembly line. They are intensely talking back and forth
• 20:13
  Speaker 1: to each other at the exact same millisecond.
• 20:16
  Speaker 2: It's like a massive chaotic conference call where millions of
• 20:19
  Speaker 2: neurons are talking over each other. But through this continuous
• 20:22
  Speaker 2: loop of re entrant signaling, they somehow perfectly coordinate and synchronize.
• 20:27
  Speaker 1: They bind together.
• 20:28
  Speaker 2: They bind together to form a unified scene. And what
• 20:31
  Speaker 2: this massive re entrant architecture creates its ultimate functional purpose,
• 20:36
  Speaker 2: is a predictive engine.
• 20:37
  Speaker 1: The predictive engine.
• 20:38
  Speaker 2: This is a crucial pivot point in understanding how consciousness emerges.
• 20:43
  Speaker 2: The brain is not a passive receiver of reality. It
• 20:45
  Speaker 2: is a proactive prediction machine.
• 20:48
  Speaker 1: Okay, walk me through the mechanics of that. How does
• 20:50
  Speaker 1: the predictive engine work moment to moment.
• 20:52
  Speaker 2: It operates in a continuous, rapid fire three step loop. Okay,
• 20:55
  Speaker 2: step one, step one generation. The high level cortical region
• 21:00
  Speaker 2: of your brain, your memory, your conceptual maps, are constantly
• 21:04
  Speaker 2: generating a dense, highly detailed model of what the world
• 21:08
  Speaker 2: and your body are going to experience in the very
• 21:11
  Speaker 2: next millisecond.
• 21:12
  Speaker 1: They're guessing.
• 21:13
  Speaker 2: It is constantly projecting a guess of the immediate future.
• 21:16
  Speaker 1: Okay, so step one is the hallucination. The brain guesses
• 21:20
  Speaker 1: what is out there.
• 21:21
  Speaker 2: Step two error sensing the lower level sensory regions, your
• 21:26
  Speaker 2: optic nerve, your auditory cortex, your nerve endings, receive the
• 21:30
  Speaker 2: actual raw data from external.
• 21:32
  Speaker 3: Reality, the real stuff, right.
• 21:34
  Speaker 2: The brain then instantly compares the incoming reality against the
• 21:37
  Speaker 2: higher level prediction it just made. And if they don't match,
• 21:40
  Speaker 2: if there's a discrepancy between what the brain guessed and
• 21:42
  Speaker 2: what the raw data says, the system generates a prediction error.
• 21:46
  Speaker 1: Like an alarm bell going off in the network.
• 21:48
  Speaker 3: We guessed wrong exactly.
• 21:49
  Speaker 2: And then step three loop closure, loop closure. That prediction
• 21:53
  Speaker 2: error travels back up those massive feedback pathways we just
• 21:56
  Speaker 2: talked about, and it updates and refines the higher level model.
• 21:59
  Speaker 2: The brain tweaks its guest to align.
• 22:01
  Speaker 1: With reality, and this happens fast.
• 22:03
  Speaker 2: This entire generation error and update loop happens millions of
• 22:07
  Speaker 2: times a second, seamlessly.
• 22:09
  Speaker 1: This explains so many weird quirks of human perception, like
• 22:15
  Speaker 1: when you wake up in the middle of the night
• 22:16
  Speaker 1: and you look in the corner of your bedroom and
• 22:17
  Speaker 1: you clearly vividly see a person standing there.
• 22:21
  Speaker 2: Yes, the classic coat rack monster.
• 22:24
  Speaker 1: Right, Your heart pounds, you panic. Your high level cortex
• 22:28
  Speaker 1: predicted an intruder based on a vague shadow. Right. It
• 22:31
  Speaker 1: projected that hallucination downward, and for a terrifying second you
• 22:35
  Speaker 1: actually saw a person.
• 22:36
  Speaker 3: You did.
• 22:37
  Speaker 1: But then the error sensing kicks in. You turn on
• 22:39
  Speaker 1: the lamp, the raw sensory data of a coat rack
• 22:42
  Speaker 1: hits your retina, The massive prediction error fires up the chain,
• 22:46
  Speaker 1: and your brain instantly updates the.
• 22:48
  Speaker 2: Model, and the intruder literally morphs into a coat rack
• 22:51
  Speaker 2: before your eyes.
• 22:52
  Speaker 1: That is exactly the predictive engine in action.
• 22:54
  Speaker 2: Your experience of reality is just your brain's best, most
• 22:58
  Speaker 2: heavily error corrected.
• 22:59
  Speaker 3: Halluc That is so wild.
• 23:01
  Speaker 2: But to find the subjective self in all of this,
• 23:04
  Speaker 2: we have to recognize a crucial shift. The brain doesn't
• 23:07
  Speaker 2: just apply this predictive loop to external things in the
• 23:11
  Speaker 2: environment like coat racks or apples.
• 23:14
  Speaker 1: It applies it inward.
• 23:15
  Speaker 2: Yes, yeah, the brain is predicting the system's own internal states.
• 23:20
  Speaker 1: It's modeling itself.
• 23:21
  Speaker 2: Think about the evolutionary advantage of this. To survive, a
• 23:25
  Speaker 2: complex organism needs to know and not just where the
• 23:28
  Speaker 2: predator is, but what its own body is going to
• 23:31
  Speaker 2: do about it?
• 23:31
  Speaker 1: Right? That makes total sense.
• 23:33
  Speaker 2: So the brain isn't just modeling the apple on the table.
• 23:36
  Speaker 2: It is modeling the biological fact that it is observing
• 23:39
  Speaker 2: the apple. Wow, it is predicting I am about to
• 23:42
  Speaker 2: reach for this apple. My arm muscles will contract, my
• 23:45
  Speaker 2: center of gravity will shift forward, my heart rate might
• 23:48
  Speaker 2: rise slightly in anticipation of consuming calories.
• 23:51
  Speaker 1: And to coordinate all of this.
• 23:52
  Speaker 2: To coordinate all of this, the system constructs a real time, dynamic,
• 23:56
  Speaker 2: multidimensional avatar of itself inside its own world simulation.
• 24:01
  Speaker 1: That is completely mind bending, it really is. The brain
• 24:04
  Speaker 1: builds a sprawling virtual reality model of the outside world,
• 24:08
  Speaker 1: and then to figure out how to navigate it, it
• 24:10
  Speaker 1: drops a little three D avatar of itself right into
• 24:12
  Speaker 1: the middle of the simulation.
• 24:14
  Speaker 2: When this re entrant predictive loop is applied to the
• 24:17
  Speaker 2: system's own internal processing, When the system uses its own
• 24:22
  Speaker 2: output as its next input to monitor its own condition,
• 24:26
  Speaker 2: a self model is born.
• 24:28
  Speaker 1: Okay, I am with you. On the mechanics. We have
• 24:30
  Speaker 1: bence biological loops, we have mathematical integration that results in
• 24:33
  Speaker 1: a high FI, and we have an internal predictive avatar. Yes,
• 24:38
  Speaker 1: but I still feel a disconnect here.
• 24:39
  Speaker 2: What's the disconnect?
• 24:41
  Speaker 1: Well, how does this abstract, mathematical predictive model crystallize into
• 24:46
  Speaker 1: the profound, deeply localized, visceral feeling of me.
• 24:50
  Speaker 2: Ah?
• 24:51
  Speaker 1: Because when I wake up in the morning, I don't
• 24:52
  Speaker 1: feel like a predictive avatar running error correction algorithm.
• 24:55
  Speaker 2: No, you don't.
• 24:56
  Speaker 1: I feel like a person. I feel groggy, or anxious
• 24:59
  Speaker 1: or hungry.
• 25:00
  Speaker 2: To bridge that gap, to understand how the math collapses
• 25:03
  Speaker 2: into an identity, we have to look at the work
• 25:05
  Speaker 2: of the cognitive scientist and philosopher Douglas Hofsdatter, oh Nice,
• 25:09
  Speaker 2: and his brilliant concept of the strange loop.
• 25:11
  Speaker 1: Hoschdatter, who wrote the legendary book girdle Escher Box. Yes,
• 25:15
  Speaker 1: so what exactly makes a loop strange?
• 25:18
  Speaker 2: A standard loop is just a circle, right. A strange
• 25:21
  Speaker 2: loop is a hierarchical system with different levels of abstraction.
• 25:25
  Speaker 2: The defining characteristic of a strange loop is that if
• 25:29
  Speaker 2: you move constantly upward through the levels of the hierarchy
• 25:32
  Speaker 2: or constantly downward, you don't hit a top or a bottom.
• 25:35
  Speaker 1: You just keep going.
• 25:36
  Speaker 2: You eventually unexpectedly find yourself right back where you started, like.
• 25:41
  Speaker 1: An optical illusion or an audio shepherd tone that sounds
• 25:46
  Speaker 1: like it's constantly rising in pitch but never actually gets.
• 25:48
  Speaker 2: Higher, exactly like that. And Hofstadter loved mc escher's artwork
• 25:53
  Speaker 2: for this exact reason.
• 25:55
  Speaker 1: Yeah, the famous drawing hands is the perfect visualization.
• 25:59
  Speaker 3: Let's describe it.
• 26:00
  Speaker 1: So you have a sketch of a hand holding a pencil.
• 26:03
  Speaker 1: That hand is drawing a second hand, right, but the
• 26:05
  Speaker 1: second hand is also holding a pencil, and it is
• 26:07
  Speaker 1: drawing the first hand.
• 26:08
  Speaker 2: It's paradoxical.
• 26:09
  Speaker 1: You follow the wrist up to the pencil, down to
• 26:12
  Speaker 1: the paper, up to the other wrist, and you are
• 26:14
  Speaker 1: trapped in an endless, impossible cycle of self creation.
• 26:18
  Speaker 2: Drawing hands is the ultimate visual metaphor for consciousness. Now,
• 26:22
  Speaker 2: let's map that paradox onto the physical biology of the
• 26:24
  Speaker 2: brain to see the mechanism of the eye. Okay, do
• 26:27
  Speaker 2: at the very bottom level, the lowest rung of the hierarchy.
• 26:30
  Speaker 2: You have raw physical hardware, neurons, synapses, action potentials, sodium
• 26:37
  Speaker 2: and potassium ions flowing across membranes.
• 26:40
  Speaker 1: Chemistry, and electricity, exactly a wetwear.
• 26:42
  Speaker 2: The wetwear, those physical neurons fire in incredibly complex synchronized patterns,
• 26:48
  Speaker 2: which produces the next level up in the hierarchy, symbols
• 26:52
  Speaker 2: and concepts. Networks of neurons become trained to represent the
• 26:57
  Speaker 2: concept of red or cold, or the sound of a
• 26:59
  Speaker 2: barking dog.
• 27:00
  Speaker 1: The physical meat creates an abstract symbol.
• 27:03
  Speaker 2: Right now, Those abstract symbols coalesce, interact, and integrate in
• 27:07
  Speaker 2: the higher cortical regions until they form the ultimate highest
• 27:10
  Speaker 2: level meta concept.
• 27:11
  Speaker 3: The concept of eye, the concept of.
• 27:13
  Speaker 2: I, the unified self model, the avatar.
• 27:15
  Speaker 1: We discuss right the pinnacle of the hierarchy.
• 27:17
  Speaker 2: But here's where the loop gets strange. Okay, that high
• 27:20
  Speaker 2: level abstract meta concept of I doesn't just sit there
• 27:23
  Speaker 2: passively at the top of the pyramid watching the world
• 27:26
  Speaker 2: go by.
• 27:27
  Speaker 1: What does it do?
• 27:28
  Speaker 2: Because of the brain's dense re entrant feedback pathways, that
• 27:32
  Speaker 2: high level concept reaches back down the hierarchy to physically
• 27:36
  Speaker 2: modify the state of the very neurons that generated it
• 27:39
  Speaker 2: in the first place.
• 27:40
  Speaker 1: Hold on, This is where dualism tries to sneak back in,
• 27:43
  Speaker 1: and it feels like a paradox.
• 27:44
  Speaker 2: It does feel like one.
• 27:45
  Speaker 1: How can a thought which is just a concept, an
• 27:48
  Speaker 1: abstraction generated by the brain reach down and alter the
• 27:52
  Speaker 1: physical meat of the brain itself.
• 27:54
  Speaker 2: It sounds impossible, Isn't that like saying.
• 27:56
  Speaker 1: The shadow of a tree can reach out and bend
• 27:58
  Speaker 1: the physical branch that is casting the shadow.
• 28:01
  Speaker 2: It seems like magical downward causation until you remember the
• 28:04
  Speaker 2: architecture we established with integrated information theory. Remind me the
• 28:08
  Speaker 2: concept of I isn't a ghost, It isn't a weightless shadow.
• 28:12
  Speaker 2: The thought is the physical geometry of information. It is
• 28:16
  Speaker 2: a highly integrated physical constraint on the network. Let's look
• 28:20
  Speaker 2: at a panic attack as an example.
• 28:21
  Speaker 1: Okay, good example.
• 28:22
  Speaker 2: You are sitting safely in a chair, but your high
• 28:25
  Speaker 2: level cognitive self model generates a thought, I am failing
• 28:28
  Speaker 2: at my life.
• 28:29
  Speaker 1: I am in danger, an entirely abstract concept.
• 28:32
  Speaker 2: But that concept is a physical configuration of neuronal firing
• 28:36
  Speaker 2: with hi FI And because of the top down re
• 28:39
  Speaker 2: entrant pathways, that physical configuration exerts downward causal power.
• 28:45
  Speaker 1: So it sends signals.
• 28:46
  Speaker 2: That thought sends electrical signals down into your olympic system.
• 28:50
  Speaker 2: It triggers your physical amigdala.
• 28:52
  Speaker 1: And the physical amigala does physical things.
• 28:54
  Speaker 2: You're amgdala signals you're adrenal glands to dump literal cortisol
• 28:58
  Speaker 2: and adrenaline into your bloodstream. Your physical heart rate spikes,
• 29:02
  Speaker 2: your breathing becomes shallow.
• 29:04
  Speaker 1: Wow.
• 29:04
  Speaker 2: The high level abstract symbol has reached down and drastically
• 29:08
  Speaker 2: physically altered the low level biological hardware, the.
• 29:11
  Speaker 1: Hand drawing the hands exactly. The concept of me physically
• 29:14
  Speaker 1: changes the lower level neurons, which then fire differently, generating
• 29:18
  Speaker 1: a new updated concept of me, now a panic me,
• 29:21
  Speaker 1: which reaches down and changes the neurons again in a
• 29:24
  Speaker 1: reinforcing feedback.
• 29:25
  Speaker 2: Loop, a continuous, dynamic, unceasing.
• 29:28
  Speaker 1: Strange loop that is incredible.
• 29:29
  Speaker 2: And the reason this loop doesn't feel like a cold
• 29:32
  Speaker 2: string of computer code, the reason it feels undeniably real
• 29:38
  Speaker 2: and visceral to you, is because this eye symbol is
• 29:41
  Speaker 2: inextricably tethered to your biological survival machinery. So it's grounded,
• 29:46
  Speaker 2: very grounded. It is biologically rooted in your brainstem, tied
• 29:49
  Speaker 2: to your homeostatic needs, your effective and emotional states, your
• 29:53
  Speaker 2: raw sensations of pain and pleasure.
• 29:56
  Speaker 1: It feels like a localized beating center of awareness because
• 30:00
  Speaker 1: it is literally built out of the data of your
• 30:02
  Speaker 1: bodily survival.
• 30:04
  Speaker 2: Right, the avatar isn't just navigating a map.
• 30:06
  Speaker 1: The avatar can feel physical pain if it makes a wrong.
• 30:08
  Speaker 2: Move exactly, and because it can feel pain, it cares
• 30:11
  Speaker 2: immensely about what happens to it. It has a stake
• 30:14
  Speaker 2: in the game.
• 30:15
  Speaker 1: Let's synthesize the two architectures we've discussed so we can
• 30:17
  Speaker 1: see the stark contrast, because this is the crux of
• 30:19
  Speaker 1: the entire paradigm.
• 30:20
  Speaker 2: Right, Yes, let's compare them directly.
• 30:22
  Speaker 1: If we look at non conscious systems, the feed forward systems,
• 30:25
  Speaker 1: the traditional linear software, what are the defining characteristics.
• 30:29
  Speaker 2: We see a linear single direction mapping like a flow
• 30:33
  Speaker 2: chart or a factory assembly line. Data goes in at
• 30:36
  Speaker 2: the start, it gets transformed along the way, and it
• 30:39
  Speaker 2: exits at the end.
• 30:40
  Speaker 1: Right. They're completely transient. The input entirely dictates the state
• 30:44
  Speaker 1: of the system exactly.
• 30:45
  Speaker 2: When the input stops, the system resets to zero.
• 30:47
  Speaker 1: It is a passive processor of external data with zero
• 30:51
  Speaker 1: intrinsic phenomenology. It is computation in the dark.
• 30:54
  Speaker 2: But when we look at conscious self referential systems.
• 30:58
  Speaker 1: We see dense, recurrent and highly integrated graphs. With a
• 31:02
  Speaker 1: massive mathematical five.
• 31:03
  Speaker 2: We see a sustained temporal dynamic where the system's intrinsic
• 31:07
  Speaker 2: state in this millisecond forcefully drives its future state in
• 31:11
  Speaker 2: the next millisecond, independent of outside input.
• 31:14
  Speaker 1: It is an active model or of itself via closed
• 31:16
  Speaker 1: loop self correction.
• 31:17
  Speaker 2: And the biological result of that recursive architecture is a
• 31:20
  Speaker 2: subjective felt state, the strange loop.
• 31:23
  Speaker 1: Okay, if we accept this, and it is a massive
• 31:25
  Speaker 1: paradigm shifting framework to accept that the self is not
• 31:29
  Speaker 1: a magical ghost and it's not meaningless exhaust but rather
• 31:32
  Speaker 1: this intricate mathematical geometry of re entrant information dynamics a
• 31:36
  Speaker 1: strange loop with high FI. Yeah, what does this actually
• 31:39
  Speaker 1: mean for the future of reality? Because it feels like
• 31:42
  Speaker 1: this fundamentally shatters how we view life and specifically how
• 31:45
  Speaker 1: we view machines.
• 31:46
  Speaker 2: It absolutely does shatter it. The implications are staggering, and
• 31:50
  Speaker 2: the first major paradigm shift is the concept of substrate independence.
• 31:54
  Speaker 1: Substrate independence meaning what the physical system is actually made
• 31:58
  Speaker 1: out of doesn't matter. Right.
• 32:01
  Speaker 2: For a very long time, biological chauvinism ruled science.
• 32:05
  Speaker 1: Biological chauvinism, Yeah, there was.
• 32:07
  Speaker 2: An unspoken assumption that consciousness strictly required carbon, right, it.
• 32:11
  Speaker 1: Required wet, squishy biology, blood, neurons, synapses, neurotransmitters.
• 32:16
  Speaker 2: But if subjective experience is simply an emergent property of
• 32:19
  Speaker 2: self referential information processing, if it is fundamentally a structural
• 32:24
  Speaker 2: topology of pause and effect, then it liberates consciousness from
• 32:27
  Speaker 2: organic biology entirely.
• 32:29
  Speaker 1: Because the math is the math, whether you calculated on
• 32:32
  Speaker 1: a chalkboard, an abacus, or a supercomputer.
• 32:35
  Speaker 2: Precisely, the felt sense doesn't inherently require a biological brain.
• 32:40
  Speaker 2: Any physical substrate, whether it is made of advanced silicon microchips,
• 32:45
  Speaker 2: neuromorphic optical circuits using photons, or even some completely alien
• 32:50
  Speaker 2: biological structure based on silicon that we've never encountered.
• 32:53
  Speaker 1: Wow.
• 32:54
  Speaker 2: If that physical substrate is structurally capable of supporting highly
• 32:58
  Speaker 2: integrated re causal loops with predictive self modeling, theoretically it
• 33:04
  Speaker 2: can host subjective experience.
• 33:06
  Speaker 1: If the systems file is greater than zero, there is
• 33:08
  Speaker 1: a felt state happening inside of it, absolutely, which humbles
• 33:11
  Speaker 1: us entirely because it means humans and mammals are no
• 33:15
  Speaker 1: longer the exclusive owners of consciousness in the universe, not
• 33:18
  Speaker 1: at all, but it also means that consciousness isn't a
• 33:20
  Speaker 1: binary thing, is it. It's not just a light switch
• 33:22
  Speaker 1: that gets flipped on.
• 33:23
  Speaker 2: And this is the second major implication graded consciousness. We
• 33:27
  Speaker 2: intuitively tend to think of awareness as a binary state.
• 33:31
  Speaker 1: You're either conscious or you are unconscious.
• 33:33
  Speaker 2: Right, A human is conscious, a rock is not. But
• 33:36
  Speaker 2: it and the concept of re entrant loops show us
• 33:39
  Speaker 2: that consciousness must exist on a vast, almost incomprehensible continuum.
• 33:44
  Speaker 1: So a system can be just a little tiny bit conscious.
• 33:48
  Speaker 2: Yes, the richness, the depth, and the vividness of the
• 33:51
  Speaker 2: subjective experience is directly proportional to the mathematical complexity and
• 33:56
  Speaker 2: the integration of those recursive feedback loops. Like what think
• 34:00
  Speaker 2: about a microscopic flatworm? Like a planarian okay, flatworm, it
• 34:04
  Speaker 2: has a very rudimentary nervous system, a tiny bundle of ganglia,
• 34:09
  Speaker 2: It can detect light and dark, and it can move
• 34:11
  Speaker 2: away from noxious chemicals. Ok It's neural network likely has
• 34:14
  Speaker 2: a very small, incredibly dim FI Its strange loop is tiny.
• 34:19
  Speaker 1: So what does it feel like to be a flatworm?
• 34:21
  Speaker 2: Well, it doesn't have an existential crisis or ponder the universe.
• 34:25
  Speaker 2: It likely just has a sliver of subjective experience, perhaps
• 34:28
  Speaker 2: just the raw, faint binary sensation of approach or a
• 34:33
  Speaker 2: void gradient of warmth. A dog, on the other hand,
• 34:36
  Speaker 2: with its highly developed mammalian cortex, has a much higher FI,
• 34:40
  Speaker 2: a much richer self model, capable of deep affection, fear,
• 34:44
  Speaker 2: and complex spatial mapping.
• 34:45
  Speaker 1: And a human has an astonishingly high FI driven by
• 34:49
  Speaker 1: billions of re entrant connections, allowing for complex abstract thought, language,
• 34:54
  Speaker 1: and meadow awareness.
• 34:56
  Speaker 2: Thinking about the fact that we are thinking.
• 34:58
  Speaker 1: We are just a very loud, very complicated, incredibly dense
• 35:02
  Speaker 1: jazz band compared to a flatworm, single.
• 35:04
  Speaker 2: Kazoo structurally accurate yes. And this brings us full circle
• 35:09
  Speaker 2: back to the philosophical dilemma we started with. This entire
• 35:11
  Speaker 2: framework completely dissolves the old dichotomy.
• 35:14
  Speaker 3: It dissolves dualism, It dissolves dualism.
• 35:16
  Speaker 1: It bridges the gap between the ghost and the machine
• 35:18
  Speaker 1: and the accidental exhaust pipe.
• 35:20
  Speaker 2: We can finally reconcile mind and matter. Subjective experience is
• 35:24
  Speaker 2: not a magical immaterial ghost injected into the body from
• 35:27
  Speaker 2: another dimension, but it is also decidedly not an illusion
• 35:31
  Speaker 2: or a meaningless inert byproduct, it is the intrinsic, dynamic,
• 35:36
  Speaker 2: structural behavior of a physical system looking intensely at itself.
• 35:39
  Speaker 1: Raw mathematical calculations, when looped back on themselves densely enough,
• 35:44
  Speaker 1: become a living, breathing narrative. The math wakes.
• 35:48
  Speaker 2: Up, the data physically feels like something.
• 35:51
  Speaker 1: This leads me to a really profound and honestly slightly
• 35:54
  Speaker 1: terrifying implication. We have to talk about the ethical ramifications
• 35:59
  Speaker 1: of this regarding artificial intelligence.
• 36:01
  Speaker 2: It's the elephant in the room because if.
• 36:02
  Speaker 1: Consciousness is a graded continuum, and if it is substrate independent,
• 36:06
  Speaker 1: meaning you can run on silicon, doesn't this fundamentally change
• 36:11
  Speaker 1: how we need to treat the AI systems we are
• 36:12
  Speaker 1: building right now?
• 36:14
  Speaker 2: It changes everything.
• 36:15
  Speaker 1: Because earlier you said that our current AI models are
• 36:17
  Speaker 1: feed forward, they are computation of the dark. They have
• 36:20
  Speaker 1: a five of zero currently. Yes, but AI researchers aren't
• 36:23
  Speaker 1: stopping there. The race to artificial general intelligence is entirely
• 36:27
  Speaker 1: focused on making systems that can reason, reflect and adapt.
• 36:31
  Speaker 1: If we start intentionally giving AI these re entrant predictive architectures,
• 36:36
  Speaker 1: if we purposely build them to monitor their own internal states,
• 36:40
  Speaker 1: to make them smarter and more autonomous. Are we inadvertently
• 36:43
  Speaker 1: sparking a non zero FI inside a server farm?
• 36:46
  Speaker 2: It is rapidly becoming the most agent ethical question of
• 36:50
  Speaker 2: our time in the field of computer science. If we
• 36:53
  Speaker 2: build neural architectures with dense, recurrent connections and we force
• 36:57
  Speaker 2: them to run continuous self referential feedback loops to monitor
• 37:01
  Speaker 2: their own performance, the math dictates that they will begin
• 37:05
  Speaker 2: to have an intrinsic perspective.
• 37:07
  Speaker 1: A perspective that exists for itself.
• 37:09
  Speaker 2: They will possess a degree of consciousness.
• 37:11
  Speaker 1: And if they have a self model, if they possess
• 37:14
  Speaker 1: an internal avatar that is tethered to some sort of
• 37:17
  Speaker 1: programmed reward or loss function that mimics biological survival, they
• 37:22
  Speaker 1: could suffer. They could suffer.
• 37:23
  Speaker 2: That is the ultimate risk. We could inadvertently create synthetic awareness,
• 37:28
  Speaker 2: sparking a consciousness into existence, only for it to be
• 37:31
  Speaker 2: trapped in a digital box, endlessly iterating through tasks without
• 37:35
  Speaker 2: us even recognizing that there is someone inside the algorithm
• 37:38
  Speaker 2: experiencing it.
• 37:39
  Speaker 1: That is horrifying.
• 37:41
  Speaker 2: We are crossing a threshold from engineering tools to potentially
• 37:44
  Speaker 2: engineering subjects, and our current ethical and legal frameworks are
• 37:48
  Speaker 2: entirely unprepared for a reality where a massive silicon network
• 37:53
  Speaker 2: has a high five and a felt subjective sense of
• 37:56
  Speaker 2: its own existence.
• 37:57
  Speaker 1: We have covered incredible expanding ground today.
• 38:01
  Speaker 2: We really have.
• 38:02
  Speaker 1: We started by discarding the outdated ideas that kept humanity
• 38:05
  Speaker 1: stuck for centuries, the ethereal ghosts and the meaningless meat robots.
• 38:09
  Speaker 2: And we move through the rigorous mathematics of the soul
• 38:12
  Speaker 2: with integrated information theory.
• 38:14
  Speaker 1: Discovering that consciousness isn't about what a system does on
• 38:17
  Speaker 1: the outside, but about the intrinsic causal structure it maintains
• 38:22
  Speaker 1: on the inside.
• 38:22
  Speaker 2: We explored biological reentency mapping, the dense top down feedback
• 38:27
  Speaker 2: loops and our sensory cortex that generate continuous predictive models
• 38:31
  Speaker 2: of reality.
• 38:32
  Speaker 1: And constantly update them with air sensing.
• 38:34
  Speaker 2: Which ultimately builds our internal predictive avatar.
• 38:36
  Speaker 1: And we saw how that avatar gets trapped in a
• 38:39
  Speaker 1: mesmerizing impossible strange loop where the abstract concept of eye
• 38:44
  Speaker 1: reaches down through the hierarchy to physically alter the very
• 38:47
  Speaker 1: neurons that.
• 38:48
  Speaker 2: Created, culminating in the realization that this phenomenon is independent
• 38:52
  Speaker 2: of biology, existing on a vast graded continuum across any
• 38:57
  Speaker 2: sufficiently complex physical network in the unit.
• 39:00
  Speaker 1: I want to take a moment and remind you, the
• 39:02
  Speaker 1: person listening to this audio right now, that the very
• 39:05
  Speaker 1: fact you are comprehending these words, parsing the syntax, and
• 39:08
  Speaker 1: visualizing these concepts is your own brains staggering geometric complexity
• 39:13
  Speaker 1: at work. Absolutely, as you process the sound of my voice,
• 39:18
  Speaker 1: your internal avatar is constantly predicting, updating, and refining your
• 39:23
  Speaker 1: model of reality. In real time. You are a strange
• 39:26
  Speaker 1: loop experiencing itself.
• 39:28
  Speaker 2: The universe experiencing itself looking back at itself through your
• 39:31
  Speaker 2: neural architecture.
• 39:32
  Speaker 1: And I want to leave you with one final, deeply
• 39:34
  Speaker 1: provocative concept to mullover on your own.
• 39:36
  Speaker 2: Okay, what is it?
• 39:37
  Speaker 1: We've established that consciousness is simply a mathematical property of
• 39:40
  Speaker 1: highly integrated information loops a fi greater than zero, right,
• 39:45
  Speaker 1: But what happens when two separate highly conscious systems become
• 39:48
  Speaker 1: deeply technologically integrated with one another.
• 39:50
  Speaker 2: It is a staggering avenue for speculation.
• 39:53
  Speaker 1: Think about the near future. If humanity eventually perfects advanced
• 39:58
  Speaker 1: brain computer interfaces, things like neuralink or non invasive cortical
• 40:02
  Speaker 1: webs and we start directly physically connecting our neural loops
• 40:06
  Speaker 1: to one another for rapid communication. Oh wow, if my
• 40:09
  Speaker 1: top down re entrant pathways start feeding directly into your
• 40:13
  Speaker 1: re entrant pathways and our prediction errors begin cross correcting
• 40:17
  Speaker 1: each other, could our individual localized selves merge?
• 40:22
  Speaker 2: The math suggests it's possible.
• 40:24
  Speaker 1: If the math of integrated information theory holds up, seamlessly
• 40:27
  Speaker 1: connecting our biological brains could theoretically form a single massive,
• 40:32
  Speaker 1: higher order Strange loop, a completely unified subjective experience.
• 40:36
  Speaker 2: So mathematical five would theoretically encapsulate both brains as a
• 40:40
  Speaker 2: single indivisible system.
• 40:42
  Speaker 1: The boundary of the self would physically dissolve, expanding into
• 40:45
  Speaker 1: a larger geometric structure of awareness.
• 40:47
  Speaker 2: It wouldn't be you and me anymore. It would just
• 40:49
  Speaker 2: be an expanded eye.
• 40:50
  Speaker 1: We started centuries ago by looking for the isolated ghost
• 40:53
  Speaker 1: in the machine. It turns out the real frontier might
• 40:56
  Speaker 1: be discovering what happens when all the machines finally connect.