
Artificial Intelligence and the Good Society - infodocket
http://csreports.aspeninstitute.org/Roundtable-on-Artificial-Intelligence
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Liquix
I applaud the authors of this and people behind similar foundations such as
OpenAI for the time and resources they are devoting. Neural networks have
rapidly surpassed human capabilities in some regards; care and consideration
are vital when it comes to turning one loose in the wild.

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gumby
> Neural networks have rapidly surpassed human capabilities in some regards;
> care and consideration are vital when it comes to turning one loose in the
> wild.

I don't mean to harsh on you for this comment; it's quite a widespread belief.
But cars rapidly surpassed human (or even cheetah) capabilities in running,
and ordinary algorithms rapidly surpassed human capabilities in calculating
trajectories, summing up columns of numbers or drawing rectangles.

The same moral panic we see today has been repeated over and over for those
technologies. Are there issues, sure, but don't be faked out by the bogus use
of "intelligence" for RNNs.

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kennyloginNTH
>This socalled winner-take-most dynamic, or 80/20 rule (in which 20 percent of
participants reap 80 percent of the gains) appears to be a structural feature
of network-based activity because well-positioned business players are able to
realize most of the productivity gains that materialize as economic
“frictions” are radically reduced at an extremely rapid rate. This is
displacing middle-class jobs at an accelerated rate, leaving people reeling
from the pace of change and government scrambling to solve market disruptions
using archaic policy architectures.

I would really like some input from someone with familiarity in the field of
economics to vet this statement.

>In the report, Kim Taipale, Founder and Executive Director of the Stilwell
Center for Advanced Studies, said that the paradoxical result of network
effects is that “freedom results in inequality. That is, the more freedom
there is in a system, the more unequal the outcomes.” This stems in part from
the self-reinforcing benefits that accrue to the “super-nodes” of a network, a
phenomenon sometimes called “preferential attachment.” Players that function
as super-nodes capture a far disproportionate share of rewards relative to
their effort, while hard-working smaller players and individuals find it very
difficult (for structural reasons) to increase their share of benefits.
Because of this dynamic, said Taipale, “The era of bell curve distributions
that sup-ported a bulging social middle class is over, and we are headed for
the power-law distribution of economic opportunities. Education per se is not
going to make up the difference.”

Will the middle class in a wealthy economy ever be viable when so few control
decisions?

