For those who believe that human-level AI isn’t far off and that a rosy scenario isn’t inevitable, 2009 is a somewhat sad and depressing time. Popular opinion is that AI won’t be here for centuries, but that isn’t a huge problem or issue. (In fact, it makes things easier by limiting the number of people involved in AI research, thus allowing me and my confederates to keep a closer eye on them.)
What is disturbing is the medium-sized and growing group of folks who believe that AI could be here within a few decades, but that the challenge of programming it for benevolence or moral common sense is trivial or already solved. I’m currently reading Wendell Wallach and Colin Allen’s new book Moral Machines: Teaching Robots Right from Wrong, published by Oxford University Press, which is arguably the first actual book on Friendly AI. In the book, they mention that every time they talk to people about the challenge of AI morality, they hear “didn’t Asimov already solve that problem?” This is silly in more ways than one, the most obvious being that Asimov made up his list of laws with the intention of them breaking down, to provide fodder for the stories. Anyway, Anissimov is telling you that Asimov didn’t solve the problem.

Another common error, rampant among transhumanists, is that human beings will magically fuse with AI the instant it is created, and these humans (who they are obviously imagining as themselves) will make sure that everything is fine and dandy. Kurzweil is the primary source of this fallacy. This belief has the added benefit of making humans feel important, giving them a guaranteed role in the post-AI future, no extra effort needed. Technology makes it happen — automatically. This helps heal the anxiety inherent in transitioning between a human-only world and a world with much greater physical and cognitive diversity.
Problem is, it doesn’t make sense. While it is possible that the first Artificial Intelligence will be created in a way that it is completely at the service of augmented human(s), it seems highly unlikely. Here is why.
1) Most new technologies are created as stand-alone objects. It would be incredibly more difficult to create a technology completely fused with the deep volition and will of a 100 billion neuron human brain than to just create the technology by itself. Is it easier to create a toaster, or create a toaster whose every element is in complete harmony with a human being, who views the toaster as an extension of himself?
Because AI is complex, mysterious, and has to do with the mind, people seem to assume that making an AI and making an AI that is a harmonious extension of human will are close enough that the latter would not be much more difficult (in some cases, required) than the former. Seriously, there is probably someone reading this right now that actually believes that AI will only be possible if it is created as an extension of human brains. This is because they see humans as the source of the “special sauce” of all that is good, holy, and intelligent, and find it impossible to imagine a stand-alone artifact displaying intelligence without direct and constant human involvement. This is anthropocentric silliness.
2) Human biological neurons are not inherently compatible with silicon computer chips and code. This is a pretty obvious one. Perhaps some thinkers can only imagine AI being created in the exact image of humans, after exhaustive research of the brain, so if AI is possible, then perfect human-computer interfaces should be too. But, was the first flying machine a perfect copy of a bird? No. So why should we expect the first AI to be an exact copy of ourselves? Even if it was, connecting a human being to an AI in a close and intimate way would not be a 1-2-3 endeavor. It would make complete sense if the first million attempts only result in some insane or non-functional amalgam. In the space of all mind-like data arrangements, only a tiny sector corresponds to what we would consider as normalcy. We are fooled into thinking that a large portion of this space contains normalcy because evolution killed off most of the non-functional or insane brains millions of years ago. We see the (mostly) positive outcome, we don’t see the quadrillions of failures.
3) The way things are going now, the first AI is likely to be created for some niche, money-making application — like predicting stocks or planning battles. Cognitive features that are superfluous to the crucial activity at hand will be postponed to implementation at a later date (if ever). The problem with this scenario is that basic goal-formulating activity in these AIs will likely lead to spontaneous attempts at the accumulation of power and the concealment of that accumulation from those who might threaten it. Paranoid? No. This category of behaviors is sometimes known as convergent subgoals — basic goals that make everything else easier, so most minds pursuing goals that require matter and energy would have an incentive to fulfill them. Unfortunately, it seems nearly impossible for anyone to wrap their heads around the idea, leaving 99% of futurists with completely anthropomorphic notions of how Artificial Intelligence will behave.
Blind optimists like to imagine AI popping into existence completely functional, reasonable, human-like, and ready to help out around the household, chatting up little Tommy just like any member of the family. If the first AIs are not like this, and are instead monomaniacal day traders, then they presume that such AIs will be kept in check until the day that Rosie the Robot Maid is online and ready to go. However, it needn’t be the case. Like the supercomputer in Colossus: the Forbin Project, the monomaniacal day trader might find itself thinking so far outside the box that it decides to take control of the entire stock exchange, or even the world economy, and manipulate it precisely to maximize its personal utility, meatbags be damned. What to a human day trader would seem “absurd” would seem “obvious” to an AI with very little background morality or understanding of the nuances of human values and meaning. While a human philosopher might spend hours upon hours debating the fine points of morality, a recursively self-improving AI might simply say, “Why argue? I already know what good is. It’s 45 lines of code that forms the top level of my goal system.” The human philosophers might then say, “But Kant said…” as they are steamrolled over for extra space.
We have spent so much time dealing with humans that we assume that human psychology is typical of minds in general and that humans are the center of the cognitive universe. In much transhumanist futurist lore, nascent AI minds are portrayed as practically falling over themselves to seamlessly merge together with us and create a Kurzweilian Utopia, or that AI morality is as simple a matter as turning a switch from “Naughty” to “Nice”.
AIs will not automatically merge together with us and become extensions of our mind, like friendly cognitive light sabers. Minds do not slide into each other like legos. There are early efforts to make an AI goalset that does actually serve as an extension of the minds of humanity, but it remains to be seen whether this can be translated into actual math, and whether or not the specific implementation in a space of 10^120 possibilities actually provides the desired outcome as planned.
But, it’s worth trying. Of course, human intelligence enhancement should be pursued too, and narrow AI may have a role to play in this, but if human intelligence is as difficult to enhance as I think it is, DARPA will have developed AGI long before we can give old Lenny a smart pill to turn his hillbilly mind into that of a theoretical physicist.
Michael Anissimov is a science writer, transhumanist activist and frequent public speaker on futurism living in San Francisco. He writes a popular blog on futurist issues, Accelerating Future. He co-founded the Immortality Institute and the SF Bay Area chapter of the WTA, BA-Trans. He is also active in the Lifeboat Foundation, the Singularity Institute for Artificial Intelligence, the Institute for Accelerating Change, and the Center for Responsible Nanotechnology’s Global Task Force.
It’s interesting you bring up day-trading as an example. The difficulty with all automated trading logics, even those backed by sophisticated and adaptive algorithms, is that human irrationally en masse is too chaotic and non-linear to adapt to without some large-scale modeling of the trading population. Therefore, the real impediment to that is data (the stream of where volume is going) or capital (the ability to move the market enough for systematic and adapting manipulation).
At this point, maybe a day-trading AI is the best ticket. Maybe the AI can apportion resources to be deployed by humans, or roll up the whole global markets and give it all out fresh.