Google’s Artificial Intelligence Getting ‘Greedy,’ ‘Aggressive’

[Razer]

Garbage In Garbage Out...

"Will artificial intelligence get more aggressive and selfish the more
intelligent it becomes? A new report out of Google’s DeepMind AI
division suggests this is possible based on the outcome of millions of
video game sessions it monitored. The results of the two games indicate
that as artificial intelligence becomes more complex, it is more likely
to take extreme measures to ensure victory, including sabotage and greed.

The first game, Gathering, is a simple one that involves gathering
digital fruit. Two DeepMind AI agents were pitted against each other
after being trained in the ways of deep reinforcement learning. After 40
million turns, the researchers began to notice something curious.
Everything was ok as long as there were enough apples, but when scarcity
set in, the agents used their laser beams to knock each other out and
seize all the apples.

Watch the video battle below, showcasing two AI bots fighting over green
apples:

Video

The aggression, they determined, was the result of higher levels of
complexity in the AI agents themselves. When they tested the game on
less intelligent AI agents, they found that the laser beams were left
unused and equal amounts of apples were gathered. The simpler AIs seemed
to naturally gravitate toward peaceful coexistence.

Researchers believe the more advanced AI agents learn from their
environment and figure out how to use available resources to manipulate
their situation — and they do it aggressively if they need to.

“This model … shows that some aspects of human-like behaviour emerge as
a product of the environment and learning,” a DeepMind team member, 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.”

The second game, Wolfpack, tested the AI agents’ ability to work
together to catch prey. The agents played the game as wolves who were
being tested to see if they would join forces as strategic predators; if
they jointly protected the prey from scavengers they would enjoy a
greater reward. Researchers once again concluded that the agents were
learning from their environment and figuring out how they could
collaboratively win. For example, one agent would corner the prey and
then wait for the other to join.

Researchers believe both games show an ability in artificial
intelligence entities to learn quickly from their environments in
achieving objectives. The first game, however, presented an added bit of
abstract speculation.

If more complex iterations of artificial intelligence necessarily
develop aggressive, greedy ‘impulses,’ does this present a problem for a
species already mired in its own avarice? While the abstract presented
by DeepMind does not venture to speculate on the future of advanced
artificial minds, there is at least anecdotal evidence here to suggest
AI will not necessarily be a totally logical egalitarian network. With
complex environments and willful agents, perhaps aggression and
self-preservation arise naturally…even in machines."

Link, with more links:
http://theantimedia.org/artificial-intelligence-human-like/

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