|FROM ||Ruben Safir
|SUBJECT ||Subject: [Hangout-NYLXS] Artificial Intelligence Gets Aggressive Without
|From hangout-bounces-at-nylxs.com Mon Feb 13 22:16:48 2017
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From: Ruben Safir
Date: Mon, 13 Feb 2017 22:16:44 -0500
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Subject: [Hangout-NYLXS] Artificial Intelligence Gets Aggressive Without
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Last year, we reported on Stephen Hawking issuing a warning that the
continuation of of AI will either be "the best, or the worst thing, ever
to happen to humanity."
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We've all seen the worst of the Terminator movies and the apocalypse
that could hit us. However, now that there are recent behavior tests
from Google's DeepMind AI system, it is clear that it is all possible.
In tests last year, the DeepMind system showed that it could learn
independently from its memory and beat the world's best Go players at
Since learning, it has been trying to figure out how to mimic a human voice.
Researchers have also been testing its willingness to cooperate with
others, and found something a little troubling: when DeepMind feels like
it is going to lose, it opts for a "highly aggressive" strategy that
will ensure it comes out on top. They tested this theory during 40
million runs of a fruit gathering game where two DeepMind agents
competed against each other to gather as many apples as they could. They
found that things were smooth when there were enough apples to go
around, but as soon as their numbers dwindled, they became aggressive.
They used laser beams to knock each other out of the game to steal the
Watch the video below to see what happened. The DeepMind agents are in
red and blue and the virtual apples in green:
Interestingly, if an agent tags an opponent with a laser beam, there
isn't an extra reward. It simply knocks the opponent out of the game for
a set period. This allows the other agent to collect more apples.
If the agents didn't use the beams, the would end up with the same
number of apples, which is what "less intelligent" iterations of
DeepMind opted to do.
It was only when they became more complex did DeepMind turn to greed,
sabotage, and aggression.
According to Gizmodo, the researchers used smaller DeepMind networks as
agents, it was more likely to be peaceful. When they used larger, more
complex networks as agents, the AI was more willing to sabotage its
Researchers suggest that the more intelligent the agent, the better it
became at learning from its environment, which allowed it to be highly
"This model ... shows that some aspects of human-like behaviour emerge
as a product of the environment and learning," one of the team, Joel Z
Leibo, told Wired. "Less aggressive policies emerge from learning in
relatively abundant environments with less possibility for costly
action. The greed motivation reflects the temptation to take out a rival
and collect all the apples oneself."
When DeepMind played a second game called Wolfpack, they used three AI
agents: two playing wolves and one playing prey. They needed to
cooperate because if they took down the prey, they both got the reward.
"The idea is that the prey is dangerous - a lone wolf can overcome it,
but is at risk of losing the carcass to scavengers," the team explains
in their paper. "However, when the two wolves capture the prey together,
they can better protect the carcass from scavengers, and hence receive a
Just as the DeepMind agents learned that aggression and selfishness
netted them the best results, they learned that co-operation could also
Tread carefully - they might just be coming.
So many immigrant groups have swept through our town
that Brooklyn, like Atlantis, reaches mythological
proportions in the mind of the world - RI Safir 1998
DRM is THEFT - We are the STAKEHOLDERS - RI Safir 2002
http://www.nylxs.com - Leadership Development in Free Software
http://www2.mrbrklyn.com/resources - Unpublished Archive
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Being so tracked is for FARM ANIMALS and and extermination camps,
but incompatible with living as a free human being. -RI Safir 2013
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