First they laugh at you, then they fight you...

[elfs]

Dr. William Struthers is apparently making a big splash all of a sudden. A researcher into neurobiology and neurophysiology, he's now making the lecture circuit of Evangelical churches preaching that his research shows that pornography is addictive "crack for the brain" and "more addicting than drugs."

So I went and looked up his curriculum vitae. Before he found this gig, Struthers' big thing was in the ethical application of neurobiology. His paper, Evangelical Neuroethics: Mapping The Mindfield, is fascinating because of its view of transhumanism. In a section entitled, "The Faking of Life Issues," Struthers claims that mind-machine interfaces and their potential for augmentation create a "wholly mechanistic" view of humanity, encourages intolerance for those who won't take augmentation, are more likely harmful than not, will not result in an improved quality of life, and will result in a "kind of person" that is not congruent with Biblical teachings. In his endnotes he discusses the need for Christians to come up with a game plan for "civil engagement."

Woah. Struthers is a man who can see the Singularity bearing down on him like cybertank and now feels that he must do everything he can to hold it off as long as possible; long enough, he hopes, for Jesus to come. I've said it before: Jesus better show up in the next fifty years because, if he doesn't, his promise of eternal life with be a paltry and pathetic offering compared to what we'll be able to do for ourselves.

Comments

[http://users.livejournal.com/_candide_/]

Before he found this gig, Struthers' big thing was in the 'ethical' application of neurobiology. [quotes mine] So, in other word, "Brainwashing-4-Jeezus."

In a section entitled, "The Faking of Life Issues," Struthers claims that mind-machine interfaces and their potential for augmentation create a "wholly mechanistic" view of humanity, Ah, but we're already have a "wholly mechanistic" view of humanity. To whit: almost everyone in all branches of science approaches human cognition as if it were a purely-linear process.

Of course, it's not. Even small collections of neurons are highly-nonlinear systems.

Having specialized in nonlinear-dynamics for my doctorate, I can tell you a few things about them:

1. They are inherently unpredictable.
2. They aren't random. They're just not predictable. (The two aren't the same.)
3. In a linear system, the whole is the sum of its parts. In a nonlinear system, the whole almost never the sum of its parts.
4. There are strong indications (but no conclusive data or models yet) that, sometimes, in a nonlinear system, the whole is greater than the sum of its parts …

There's something else that I recall from my grad-school days, from a course in the emerging science of "Complexity". We were studying ANN
==artificial neural nets. As I recall, real neurons are kinda-sorta-vaguely-like analog transistors. Only, not. Unlike a a transistor, a biological neuron has arbitrary number of inputs, outputs, and can be anything between "on" or "off"(Think dimmer knobs, not light switch.) Yet even the esteemed computer scientist, Peter Naur, in a recent technical article, conflated neurons with the on-or-off, switchlike behavior of a transistor.

So, question: How do we develop humans who are, "beyond-human," if we can't let go of our über-simplified analogies of the brain's "circuitry" long enough to start looking at the actual components and how they work?

But I have a second problem with the whole trans-human idea, again, stemming from studying ANNs in that class. Seems that ANNs have a "capacity," though not like the RAM in your computer. No, this "capacity" is more of a soft-limit of how much you can "store" in the artificial neural net. For example, if you teach 8 letters to an ANN that does character-recognition, all and good. Let's say this ANN's "capacity" is 10 characters. What happens if you try and teach it all 26 letters?

Oh, it appears to learn them. But a funny thing happens — it starts having trouble recognizing letters. It'll confuse, for example, "E" and "F". And as you try to store more letters in it, it'll start confusing "E" and "Z". In short: try to store too much in an artificial neural net, and it has trouble remembing.

Sound familiar?

So, what if those implications are correct? What if the flaky-memory of old age isn't merely physiological, but also due to our brains just getting full? What does that mean for a nigh-immortal trans-human?

[elfs.livejournal.com]

There are two interesting conclusions I reach from your neural-net analogy: one, that human brains don't work, and two, that they can't be successfully extended by technology.

I suddenly understand where Descarte was coming from.

Neural-net analogies are poor because there's no evidence the brain is just a neural net. It could well be a cellular automata with a robust but distance-poor signaling system; in which case, transhumans will have to come up with a more efficient but equally robust signaling system to make sure that all parts of a mind stay in sync.

The notion that a flaky memory "isn't physiological but due to our brains getting full" is something of a misstatement. All that says is that the physiology is insufficient.

[http://users.livejournal.com/_candide_/]

Neural-net analogies are poor because there's no evidence the brain is just a neural net. It could well be a cellular automata with a robust but distance-poor signaling system; in which case, transhumans will have to come up with a more efficient but equally robust signaling system to make sure that all parts of a mind stay in sync.

J…ein. The brain is, by definition, a neural net. Any collection of biological neurons is a neural net. That's why everyone makes sure to refer to the "artificial" when talking about ANNs.

As for signalling, I happen to also remember that biological neurons don't propagate electric signals instantly. If they did, synapses wouldn't fire, but sorta sputter, if they did anything. If neurons didn't act like capacitors, our brains wouldn't function.

Our neurons aren't analogous to the wiring on a CPU chip. They're more like combination wire/capacitor. The neurotransmitters crossing the synapses cause a change in voltage drop across the neuron.

Lately, I've been wondering if human cognition isn't a self-emergent property of … well all of the brain's variable aspects: neurotransmitter quantities, the individual ion-propagation time constants of each neuron, the number of connections between each neuron, and how a given set of signals to each neuron are summed to produce an internal voltage change.

The notion that a flaky memory "isn't physiological but due to our brains getting full" is something of a misstatement. All that says is that the physiology is insufficient.

:)

That brings us back to the analogy I made earlier. I'll admit, it has been 10 years since I last saw this stuff. But I do recall that ANNs are closely modelled after some experimental biology studies of living neural nets, and how those behave. That includes the whole "capacity measurement," which is determined solely by the number of neurons and the topology of their interconnections. It could, in principle, be used to measure the lower-bound capacity of biological neural nets, and not just ANNs. The problem in practice is: what's the base-unit of information stored by a BNN? For an ANN, it's bits, obviously.

But for BNNs, much less brains, much less human brains? Who even knows? We don't even know how to measure the information size of, say, the image of grandma's face. So how can we say how much space in your brain that image of Grandma occupies? ;)

Our brains are finite, nonetheless. So, their capacity … whatever the units of measure … is also finite. Now, I know your response, Elf: "Then, we need to find ways to enhance that capacity." True enough, and I'd love nothing more than to have an eidetic memory for the duration of my lifetime.

I just don't see it happening. If our best models of the brain, ANNs, are too crude, as you say (and I agree with that), then how can we hope to understand, much less modify, much less enhance the real thing?