From: justin corwin (outlawpoet@gmail.com)
Date: Tue Dec 28 2004 - 04:29:12 MST
In my work, I concentrate largely on the practical, necessary research
to allow us to build an artificial intelligence. It is the central
fascination of most of the people in my company. I would imagine that
most people in this community have great interest(if not actual
involvement) in the research, development, and application of novel
intelligent systems, IA, AI, or otherwise.
However, in the process of explaining my involvement to other people,
as well as attempting to instill enthusiasm (or at least explain
potential impact) for my research, I've been encountering the
following baffling response with increasing frequency. My fearless
leader here at A2I2, Peter Voss, has been encountering the same thing.
"How do you intend to productize your research, what is it that you
expect to come out of this company, and how can you make money?"
I would like to take a moment to say that I am only indirectly
interested in money. My involvement in A2I2 and AI research in general
is motivated both by interest and idealism, with a backdrop of
pragmatic analysis. AI is a very large lever. It will count, in game
theoretic terms, an inconceivable amount, before changing the
landscape entirely. Money, for me, is just a poorly normalized utility
token, and inasmuch as I am interested in it, I expect to be more than
able to backwards exchange the influence I have on the creation of AI
for it. Digression ended.
What these people are really asking, via the agency of hypothetical
investors, is "what is AI good for, and how can that be delivered from
your research."
Initially, much like Peter had in previous discussion, I discounted
this reaction as simply the miscategorization of AI as 'yet another
techno-widget', to be judged in the marketplace and priced for proper
placement on shelves. It has become clear to me, however, that it runs
somewhat deeper than this.
Artificial Intelligence, even very weakly achieved, is not just
another technology. It represents, at the very least, a complete
industry, and most likely, is one of those events that redefines the
landscape of human activity.
Any transhuman intelligence, of course, represents an absolute
departure from human prediction, but for the time being, let us speak
of what we can.
The unfortunate thing, from my point of view, is that generating a
conservative estimation of the economic impact of AI is nearly
impossible. It pre-supposes several things.
-First, that AI impacts economically before it changes the entire
landscape, this seems quite possible, AI will take some time to
develop, and even once complete will require some time to run. Even if
it's just inflation hitting the roof as everyone with any money does
whatever they think will avert the apocalypse during the last week of
the Final Program, that counts as economic impact.
-Second, that there is some period of stability in the development of
AI that allows for AI 'products' to be evaluated in terms of
relatively cognizant economic terms. This is very tricky. It has been
popularly supposed by some that human-commensurate intelligence
represents the top level, or a hard barrier, that AI research will
continue to that point and then stop, or at least be slowed. It is
likely that a certain level of intelligence represents the maximum
effective potential of a particular design, due to scaling laws,
architectural support requirements, or flaws in the design to start
with. Unfortunately, an AI will not be using the same design as a
human. It is, in my estimation, just as likely to top out at the
commensurate intelligence of a mouse, or a dolphin, or so far above us
that the intelligence is not measurable. It seems clear to me that
minds need not follow a uniform plan with uniform strengths, although
they may be very correlated. This makes design-independent analysis
complicated.
Some hope in the form of computer power requirements, assuming
biologicals and previous experience with unintelligent mechanical
computation hold, the physical task of running an intelligence may
limit it to certain levels of potential until larger/faster computers
can be built. Unfortunately even Kurzweil's rather charming little
graphs give us little time before available computation far outstrips
human level, leaving us in the same boat. The stability given us there
is fleeting, but does allow enough years to be evaluated on the
economic scale.
-Third, that our status, as AI researchers and developers, will give
us a privileged and controllable stake in the construction and
deployment of AI products and resources, allowing us to capitalize on
our investment, as per the standard industrial research model. This
seems fairly safe, until one realizes that there are many forces that
oppose such status, merely because of the nature of AI. Governments
may not allow technology of this kind to remain concentrated in the
hands of private corporations. AI may follow the same path as other
technologies, with many parallel breakthroughs at the same time,
leaving us as merely members of a population of AI projects suddenly
getting results. The information nature of this development increases
this problem a great deal. I have no reason to imagine that AI
development requires specialized hardware, or is impossible to employ
without the experience gained in the research of said AI software. So
piracy, industrial espionage, and simple reverse-engineering may
render our position very tenuous indeed. I have no easy answers for
this assumption, save that while worrying, little evidence exists
either way. I personally believe that our position is privileged and
will remain so until the formation of other AI projects with
commensurate theory, developed technology, and talent, at that point
it becomes more problematic.
Assuming we have answers to all these questions, we may find that AI
is indeed a good way to make money, or at least in the near term.
I have a story I can tell here, but the supporting evidence is
abstract, and indirect. Artificial Intelligence is likely, in my
opinion, to follow an accelerating series of plateaus of development,
starting with the low animal intelligence which is the focus of our
research now. Progress will be slow, and spin off products limited in
their scope. As intelligence increases, the more significant
bottleneck will be trainability and transfer of learned content
between AIs. This period represents the most fruitful opportunity for
standard economic gain. The AI technology at this point will create
three divisions across most industry, in terms of decision technology.
You will have tasks that require human decision-making, tasks that can
be fully mechanized, performed by standard programmatic
approaches(normal coding, specialized hardware, special purpose
products), and a new category, AI decision-making. This will be any
task too general or too expensive to be solved algorithmically, and
not complex enough to require human intervention. Both borders will
expand, as it gets cheaper to throw AI at the problem than to go
through and solve it mechanically, and as the upper bound of decision
making gets more and more capable.
I'm afraid I have no real evidence as to how long this period will
last. It depends entirely on the difficulty of increasing the
intelligence of the AI, which may reside in design, hardware, and to a
certain extent, motivation(goal systems are a thesis in themselves,
ask EY). I suspect, based on my experiences thus far, that early AI
designs will be very lossy and faulty and poorly optimized for
increasing in intelligence. This may mean that a complete redesign of
AI theory will be necessary to get to the next series of plateaus.
Unless this is simply beyond human capability, there is no reason to
think this will take any longer than the development of AI theory
sufficient to get us to this point.
Sometime after this, economic aspirations become fleeting in the
general upheaval and reconstitution caused by the arrival of another
kind of intelligence. Some might say this is rather the point of AI
research.
Projecting into the future is always dangerous. I think that any
attempt, especially the one above, to characterize the trajectory of
any technology is doomed to be largely irrelevant. But some choices
must be made on best available guesses, so here are mine. AI research
will change a lot of things. In the near term, it will remain a fringe
activity, and people will still ask the strange question 'what will
those AIs be good for, anyway?'. But some investors will come, and the
clearest way I can communicate with them what the goals and value of
AI research is that it is vastly enabling. I don't know what the first
task an AI will perform is. I know that it will be something that
can't be done with anything else. It represents, in the near term, an
investment in future capability. If money is what you're after
primarily, I don't know how to defend an investment in AI research
from the perspective of, say, venture capital. I can point to examples
of enabling technology, like CAD, or tooling, or electrical power,
which did not fit into the world they arrived in, but created their
own industries.
I'm not saying I can't make up clever uses for AI technologies that
could make a gazillion dollars, if I had designs for them in my hand.
There are obvious and clear storytelling ideas. But that would be
intellectually dishonest. I'm looking for a way to express, in terms
of investment return, what AI is likely to actually do for us, in a
conservative, defensible sense.
This must be separated from, for example, safety concerns, in which it
is perhaps useful to imagine, as some do on this forum, what the
failure modes, what the fastest take off, what the actual capability
of such developments may be. That isn't helpful in this kind of
planning.
I must anticipate a response suggesting that non-profit, private
efforts to research AI, such as the Singularity Institute, AGIRI, etc
are better suited for this subject matter, and in fact invalidate my
queries as relevant at all. I remain very doubtful that this is the
case. AI is not something to be solved quickly, nor something to be
solved with few people with no money. It is in it's first stages of
real development, and a massive amount of research and data needs to
be collected, if AI theories are to be informed by more than
introspection and biological analogue. Like so many things in our
modern world, AI will be done long before we can properly evaluate and
prepare ourselves for the results, however long it takes. But people
need to have reasons to join AI efforts, to fund them, and to support
them, in levels thus far not seen. I submit this is at least partially
because this kind of analysis is either not publicised, or has simply
not been done.
...
This kind of analysis also raises the rather uncomfortable spectre of
doubt, that I have jumped into a field of study without sufficient
research and investigation, or have unrealistic(at least ungrounded)
expectations for the fruits of my work. I submit that my primary
interest in AI is at least partially unrelated to gain of these kinds,
and secondarily informed by the safety concerns, asymmetric potential,
and increasing importance investigated much more clearly by other
authors(Vinge, Yudkowsky, Good).
Any responses or questions can be asked on the sl4 mailing list, to
which this is posted, to me privately, or on my blog.
Justin Corwin
outlawpoet@hell.com
http://outlawpoet.blogspot.com
http://www.adaptiveai.com
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