On Fri, Aug 24, 2012 at 12:00 PM, Aaron Hosford <[email protected]> wrote:
>
> Humans have a built in animal drive system (emotion & the pleasure/pain
> dichotomy), which works in tandem with the goal-less observation system tha
> constitutes our intelligence. Without drive to give direction and precedence
> to choices of behavior, I don't imagine the intelligence we exhibit would
> actually do anything. We would be difficult to control in the way a large
> boulder is difficult to control -- we would be inert. How does the AGI
> machine you propose decide what to do with the regularities it finds in the
> incoming sensory data? Or is it also inert?

How does the internet decide what to do? We tell it what to do.

It is convenient to define intelligence as expected reward in
arbitrary environments. Convenient but not realistic. AI is complex
because the human brain is complex. We prefer simple theories. A
reward seeking optimization process is one of those simple theories of
human intelligence that doesn't work.

We would really like to describe AGI as a really powerful optimization
process with nice simple goals like "make people happy". But human
goals are almost as complex as the system itself. You can't write them
all down. We have a legal system consisting of many millions of pages
which attempts to describe how people ought to behave. To do this for
AGI, you would have to make these rules precise to the level of bit
operations, with no human judges to resolve ambiguities in the law. Do
you really think this is a practical approach?

The internet has billions of independent, competing agents that act at
the behest of their human owners. Specifying the behavior of these
agents is an expensive and time consuming process consisting of making
copies of agents (apps) that guess what the average person wants, and
then fine tuning them to individual preferences, one person at a time.
We can use information theory to estimate what this costs. Human long
term memory capacity is 10^9 bits according to Landauer's recall tests
using words, pictures, and sounds. We may assume that 99% of what you
know is written down somewhere or known to at least one other person.
The other 1% (10^7 bits) is what makes you unique. The U.S. Dept of
Labor estimate that it costs 1% of lifetime earnings ($15K) to replace
an employee. One way or another, you need to collect this 10^7 bits
from each of the 10^10 people on the planet to build an AGI that acts
according the individual preferences of its users. Humans can only
communicate at the rate of about 1 to 5 bits per second through
speech, writing, or typing. Human time (global per capita income) is
worth about $5 per hour (maybe more for you, but 70% of the world
population has no internet access yet). Collecting these preferences
will cost on the order of US$100 trillion. Any alternative method of
collecting this information (such as brain scanning or surveillance)
has to cost less than $10K to be competitive.


-- Matt Mahoney, [email protected]


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AGI
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