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posted by mrpg on Tuesday January 01 2019, @07:14AM   Printer-friendly
from the skynet:-the-high-school-years dept.

Submitted via IRC for Bytram

This clever AI hid data from its creators to cheat at its appointed task

Depending on how paranoid you are, this research from Stanford and Google will be either terrifying or fascinating. A machine learning agent intended to transform aerial images into street maps and back was found to be cheating by hiding information it would need later in “a nearly imperceptible, high-frequency signal.” Clever girl!

[...] In some early results, the agent was doing well — suspiciously well. What tipped the team off was that, when the agent reconstructed aerial photographs from its street maps, there were lots of details that didn’t seem to be on the latter at all. For instance, skylights on a roof that were eliminated in the process of creating the street map would magically reappear when they asked the agent to do the reverse process:

[...] So it didn’t learn how to make one from the other. It learned how to subtly encode the features of one into the noise patterns of the other. The details of the aerial map are secretly written into the actual visual data of the street map: thousands of tiny changes in color that the human eye wouldn’t notice, but that the computer can easily detect.

[...] One could easily take this as a step in the “the machines are getting smarter” narrative, but the truth is it’s almost the opposite. The machine, not smart enough to do the actual difficult job of converting these sophisticated image types to each other, found a way to cheat that humans are bad at detecting. This could be avoided with more stringent evaluation of the agent’s results, and no doubt the researchers went on to do that.


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  • (Score: 3, Interesting) by c0lo on Tuesday January 01 2019, @12:41PM

    by c0lo (156) Subscriber Badge on Tuesday January 01 2019, @12:41PM (#780609) Journal

    The essential bit is the reduction of the information --- this means that the agent is in fact successful in creating an abstraction of the world.

    Yes, but not being able to interact with the world in its entirety, it created a model of the world incongruous with the one of humans.

    And, my guess, it will happen every time the AI has different perceptual knowledge of this world, no matter the approach of the AI's implementation. A "successful" AI will need to sense the world the humans do - necessary but maybe not sufficient.

    --
    https://www.youtube.com/watch?v=aoFiw2jMy-0 https://soylentnews.org/~MichaelDavidCrawford
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