11-14-2017, 02:04 AM
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ON THE FIRST DAY of school, a child looks into a digital camera linked to the school’s computer. Upon a quick scan, the machine reports that the child’s facial contours indicate a likelihood toward aggression, and she is tagged for extra supervision. Not far away, another artificial intelligence screening system scans a man’s face. It deduces from his brow shape that he is likely to be introverted, and he is rejected for a sales job. Plastic surgeons, meanwhile, find themselves overwhelmed with requests for a “perfect” face that doesn’t show any “bad” traits.
This dystopian nightmare might not be that farfetched, some academics warn, given the rise of big data, advances in machine learning, and — most worryingly — the current rise in studies that bear a troubling resemblance to the long-abandoned pseudoscience of physiognomy, which held that the shape of the human head and face revealed character traits. Modern computers are much better at scanning minute details in human physiology, modern advocates of such research say, and thus the inferences they draw are more reliable. Critics, on the other hand, dismiss this as bunkum. There is little evidence linking outward physical characteristics and anything like predictable behavior, they note. And in any case, machines only learn what we teach them, and humans — rife with biases and prejudicial thinking, from the overt to the subtle and unacknowledged — are terrible teachers.
Still, the research continues.
Just one year ago, engineering professor Xiaolin Wu of McMaster University and Xi Zhang of Shanghai Jiao Tong University jointly published a paper at ArXiv.org, a popular online repository of unreviewed science papers in various stages of development, suggesting that it was possible for a computer to predict who might be a convicted criminal based solely on scanned photographs. (The study has since been taken down, but the authors posted a response to critics here). Wu followed with another study that said machine learning could be used to infer the personality traits of women whose pictures were associated with different words — coquettish and sweet, for example, or endearing and pompous — by a group of young Chinese men.
While the abstract noted that the algorithm is only learning, aggregating, and then regurgitating human perceptions, which are prone to errors, the authors also suggest that “our empirical evidences point to the possibility of training machine learning algorithms, using example face images, to predict personality traits and behavioral propensity.”
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Continue reading article @ undark.org
ON THE FIRST DAY of school, a child looks into a digital camera linked to the school’s computer. Upon a quick scan, the machine reports that the child’s facial contours indicate a likelihood toward aggression, and she is tagged for extra supervision. Not far away, another artificial intelligence screening system scans a man’s face. It deduces from his brow shape that he is likely to be introverted, and he is rejected for a sales job. Plastic surgeons, meanwhile, find themselves overwhelmed with requests for a “perfect” face that doesn’t show any “bad” traits.
This dystopian nightmare might not be that farfetched, some academics warn, given the rise of big data, advances in machine learning, and — most worryingly — the current rise in studies that bear a troubling resemblance to the long-abandoned pseudoscience of physiognomy, which held that the shape of the human head and face revealed character traits. Modern computers are much better at scanning minute details in human physiology, modern advocates of such research say, and thus the inferences they draw are more reliable. Critics, on the other hand, dismiss this as bunkum. There is little evidence linking outward physical characteristics and anything like predictable behavior, they note. And in any case, machines only learn what we teach them, and humans — rife with biases and prejudicial thinking, from the overt to the subtle and unacknowledged — are terrible teachers.
Still, the research continues.
Just one year ago, engineering professor Xiaolin Wu of McMaster University and Xi Zhang of Shanghai Jiao Tong University jointly published a paper at ArXiv.org, a popular online repository of unreviewed science papers in various stages of development, suggesting that it was possible for a computer to predict who might be a convicted criminal based solely on scanned photographs. (The study has since been taken down, but the authors posted a response to critics here). Wu followed with another study that said machine learning could be used to infer the personality traits of women whose pictures were associated with different words — coquettish and sweet, for example, or endearing and pompous — by a group of young Chinese men.
While the abstract noted that the algorithm is only learning, aggregating, and then regurgitating human perceptions, which are prone to errors, the authors also suggest that “our empirical evidences point to the possibility of training machine learning algorithms, using example face images, to predict personality traits and behavioral propensity.”
<<<
Continue reading article @ undark.org
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