Accelerating Future

To some, it seems “obvious” that significant human intelligence augmentation will come before human-level AI. To others, it’s the reverse that’s obvious. I don’t think either is obvious, but I believe there’s a strong likelihood AI will come first.

In the IA camp, one of the arguments goes, [Brain+Computer] will always be more intelligent than [Computer] alone. But this is untrue, as the I/O channels between brain and computer make all the difference, and with today’s technology, these channels are quite limited. Even if we had million-electrode brain-computer interfaces, it would be a cybernetics problem to ask which outputs to plug into which inputs, and what changes might need to be made to the central executive to handle the new cognitive architecture without information overload or psychosis. Reprogramming the executive center of the human brain would require advanced neurosurgery and extensive knowledge of the brain, knowledge that could take decades of research and advanced experimental techniques to uncover.

Other cons for IA, in my view:

• Experimentation on the human brain is likely to be made illegal globally
• The design-and-test cycle is on the order of weeks or months
• Lack of human volunteers willing to die for the cause of IA research
• Someone left out the line notes for the brain’s code
• Experimenting on the deep brain is difficult because neocortex is in the way
• All that medical hardware is really expensive
• The human brain was not designed to be upgraded
• Gene therapies not likely to give enough improvement for takeoff speed

A remark on that last one… the issue of takeoff speed. It’s not enough to create an Einstein with IA. You have to create an Einstein that can go immediately to work on new intelligence augmentation techniques, and actually come up with something of use in a reasonable amount of time, before AI is developed. It seems more likely to me that an intelligence-enhanced human would just go into the business of creating AI. Smarter-than-human intelligence cannot just be a really smart human being - it has to be something qualitatively off the scale. Manipulating the genes associated with genius, as James Miller suggested, would likely produce “only” human geniuses at first. You’d need to go an extra level of theory and genetic engineering to get something genuinely smarter-than-human in a human-like package. I’m not saying it couldn’t be done, but that the whole process could drag on for a number of years.

Benefits of IA:

• Evolution has already done a lot of work for us
• Some might think a human seed is more predictable
• Sparks human-centric patriotism in ways AI doesn’t

On to the cons of AI:

• Present-day computers might not be fast enough to implement AI
• You have to build everything from scratch yourself
• Everyone is working on narrow AI, but AGI is unpopular
• Requires strong theory of general intelligence, difficulty unknown
• Stigma of excessive past claims

And the benefits of AI:

• Design-and-test cycle can be very rapid
• All aspects of the AI are read/write friendly
• Line notes are included with the code
• Cognitive features can be optimized for self-improvement
• Computational power can be expanded as funds allow
• Virtual worlds are available as a flexible training zone
• Hardware can be used to “overclock” beneficial functions
• Probabilistically realistic, flexible learning can be implemented
• Nascent AIs can share information with each other rapidly
• Much larger regions of the mind configuration space can be tested
• AIs can be copied indefinitely, allowing to commercial spin-offs
• Substantial advances in AI, but not IA, have already been achieved
• The hardware itself is inherently cheaper
• Little to no legal concerns

Comment away. Whether or not IA or AI reaches smarter-than-human intelligence first is pretty important, as the step into this new domain could spark a runaway self-improvement process, something I.J. Good called an “intelligence explosion”. This is normally what we think of when we hear the word superintelligence.

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There are quite a few individuals that react to the idea of qualitatively smarter-than-human intelligence, AI or otherwise, with extreme skepticism and derision. My guess is that there are four possible reasons for this, which different people display in different combinations and intensity levels.

The first is the folk theory that intelligence is a light bulb - either it’s on, or it’s off. No in between. If you have it, it only varies to a matter of degree, not qualitatively. Humans have intelligence and animals don’t, which is why it’s okay to raise animals for food, for instance. Intelligence and subjective consciousness go hand in hand.

The second is the argument from divine privilege. Man, being made in God’s image, has been given the gift of reason. We cannot magnify this gift on our own any more than we can engineer a machine that turns us into angels. This “gift of reason” argument is what I was taught by my parents as a child.

The third is technological skepticism. For example, my grandfather, who is an atheist, believes it will be centuries before we understand the brain in enough detail to manipulate it significantly. This skepticism derives partially from a linear intuitive view of technological progress, and partly from a pseudo-spiritual worship of brain complexity.

The fourth is outright denial based on fear. Some people associate superintelligence with heartlessness, boring rationality, ruining all the fun, threatening to replace us, and so on. This is primarily based on fictional portrayals. There are dozens of films and books in which superintelligences are the bad guys. Astonishingly, the dumber good guys always seem to triumph in the end.

Can you think of any others?

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Bacterial cells have little organelles in them called mesosomes. According to the Wikipedia article, “Mesosomes may play a role in cell wall formation during cell division and/or chromosome replication and distribution and/or electron transfer systems of respiration. Electron transport chains are found within the mesosome producing 32-34ATP. They act as an anchor to bind and pull apart daughter chromosomes during cell division.” Various subscription-required articles, though some free, go on and on about the possible functions of these small organelles in the bacterial division, respiration, etc. Mesosomes were originally discovered in 1960.

Small problem. Sometime in the mid-70s, scientists realized that mesosomes weren’t even real. They were just artifacts caused by freeze-fractures in the chemical fixation process for electron microscopy. Little intrusions produced where the plasma membrane and cell wall came apart from the stress of the fixation process. So much for that idea.

If you figure that biologists get paid something like $60,000 per year, and it takes a couple months to do research and write a paper, and maybe something like 500 papers were published on mesosomes before they realized that what they were studying was pure bunk, then the biology community as a whole burned through ~$5 million chasing a ghost.

What does this have to do with the subject matter of this site? I often talk about intelligence enhancement and the recursive snowballing effect that I and many others predict would occur soon after its development. If a sufficiently intelligent biologist were on the research team that first discovered “mesosomes” in 1960, they could have discovered these were just artifacts by replacing the water used in the fixation process with an inorganic solvent, and all this confusion would have been saved. Our society has a bias against being too hard on people for these little mistakes, because, at least they tried. People would be pointing fingers non-stop if we always judged past events with the knowledge of hindsight. And we’re only human, right?

The magical difference that increased intelligence produces is getting it right the first time. It’s very tough for us to imagine a slightly-smarter-than-human intelligence that constantly solves difficult problems right off the bat, because we’ve never seen one. If the smartest human we can throw at the problem is just about as good as anyone else, then we project the quality of hardness onto the problem - not onto the abstract recognition that “human intelligence isn’t good enough”. This is the mind projection fallacy. But what we naively label “impossible” might be “easy” even to a mild version of superintelligence, say a human being with an artificially expanded neocortex. We may say, “this problem inherently requires five years of research!”, but a superintelligence walks along, says, “no it doesn’t”, and solves it in five minutes. We’re too quick to label things extremely difficult or impossible, but if we don’t, we lose our self-respect as a species, so many would argue we have to.

It seems like only transhumanists are capable of really stepping outside of that box of Homo sapiens and saying, “what if we were really and truly fundamentally smarter?” If more people could do this, then pursuing intelligence enhancement technology might become a national or even global priority.

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Linda Gottfredson is a brilliant intelligence researcher. Her work is based on the premise that, when we ignore the reality of IQ and the profound impact it has on daily life and the workplace, it’s unfair and counterproductive to everyone. The first Gottfredson paper I usually point people to is Why G Matters. Dr. Gottfredson has engaged in a tremendous amount of careful research to test her hypotheses on IQ and its significance to human society. From What Do We Know About Intelligence?:

The first and very lively contest among pioneers in the then young study of intelligence, continuing well past mid-century, concerened wheteher there even exists a general mental ability as distinct from multiple, unrelated abilities. In another heated debate, a large cadre of IQ researchers in the 1960s and 1970s made very concerted efforts to prove mental tests culturally biased. Ironically, it was the every vigor of attempts to disprove the reality and importance of general intelligence that in the end so clearly proved both.

Evolution is lazy. It does as little as possible to get by. Unlike human engineers, it doesn’t perform optimization based on some abstract referent, but based on the inclusive fitness of nearby conspecifics. With all this in mind, it’s remarkable that a general intelligence ability evolved rather than a patchwork of quick-and-dirty cognitive modules with the purpose of excelling in niche tasks, which is usually more than enough to maximize inclusive fitness. Perhaps it was “waiting in the configuration space” for evolution to discover.

The utter speed with which evolution went from complex non-general intelligence to general intelligence is remarkable. Why was general intelligence necessarily accompanied by consciousness? The two should be viewed as distinct. Today, certain AI researchers seek to create optimization engines with general intelligence, but lacking numerous features possessed by human beings - social instincts, self-deception, consciousness (in the Chalmers sense), inconsistency, boredom (and thereby countersphexishness), observer-centered goal systems, and others. In a sense, these researchers are sculptors like Michelangelo, looking at the marble block of the Homo sapiens mind and shaving off large quantities of material to achieve a desired end product, which is supposed to guide us to the other side of dawn. In another sense, these researchers must be mathematicians, building up a very complex theorem from scratch, a theorem which must formally prove its validity with each dynamic step it takes through the cognitive configuration space. This complex bottom-up/top-down dichotomy, and the extreme specificity and security it demands, are challenges that humans traditionally mess up on before they get it right.

Getting it right will require complex tricks. Where researchers sometimes disagree is on how tricky or how complex these tricks will need to be. It is agreed that programming in the “core” of the theorem cannot be directly inspired from the messiness or self-contradictory nature of actual human brains. But because human brains are the only general-intelligence-imbued optimizers on the planet that we know to be consistent with the continued existence of the human race, it is tempting to steal as much as possible of their information content to give to our mind children. The only question is, how much information stealing is appropriate? Like trying to push the water volume of a fire hose through a plastic straw, the normative human psuedo-utility function is not a suitable vessel for the magnitude of optimization power that a recursive self-improver promises to deliver.

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