Is it a robot, or is it a human? Sometimes, the conclusions overlap. The first picture refers to the profanity habit picked up by IBM’s Watson early in the course of its training. It must be disconcerting to hear the word “bullshit” in a synthetic voice (even if it’s Q*bert). A more recent example of this comes from Microsoft's ill-fated attempt at politically-correct AI, giving us more of a robo-fascist instead [1].
Speaking of artificial systems that reveals the less-promoted side of intelligent behavior, I have run across a number of references to the computational exploration of artificial pareidolia [2]. Having first-hand experience with this phenomenon on Facebook, it's nice to see people exploring this oft-maligned feature of human cognition using artificial intelligence.
In these two articles [3, 4], studying digital pareidolia means generating certain types of false-positive using facial recognition software. Whether this highly-restricted definition [5] qualifies as the study of neurological pareidolia, there are many shapes and patterns that have many of the features found in faces [6].
Converging to Mona Lisa (using a fitness function).
NOTES:
[1] the goal was not actually to build a politically-correct AI, only a Twitterbot that did not pick up the worst habits of humanity. The project has since been terminated.
[3] Rosen, R.J. Pareidolia: a bizarre bug of the human mind emerges in computers. The Atlantic, August 7 (2012).
[4] Borenstein, G. Machine Pareidolia: hello little fella meets facetracker. Ideas for Dozens blog, January 14 (2012).
[5] One problem with this definition involves the restriction of the pareidolia phenomenon to faces. The other (and potentially more significant) problem is that biologically speaking, faces (and perhaps other objects) may be processed holistically rather than by evaluating sets of landmarks.
[6] For more reading on the topic, please see:
Taubert, J., Apthorp, D., Aagten-Murphy, D., and Alais, D. The role of holistic processing in face perception: evidence from the face inversion effect. Vision Research, 51(11), 1273-1278 (2011).
Goffaux, V. The discriminability of local cues determines the strength of holistic face processing. Vision Research, 64, 17-22 (2012). Goffaux lab explainer.
Richler, J.J. and Gauthier, I. A meta-analysis and review of holistic face processing. Psychological Bulletin, 140(5), 1281-1302 (2014).
[7] Johansson, R. Evolution of Mona Lisa. December 7 (2008).
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