Blaise Aguera y Arcas leads Google’s Machine Intelligence group in Seattle, and he has written a remarkably unscientific piece decrying physiognomy’s new clothes:
The practice of using people’s outer appearance to infer inner character is called physiognomy. While today it is understood to be pseudoscience, the folk belief that there are inferior “types” of people, identifiable by their facial features and body measurements, has at various times been codified into country-wide law, providing a basis to acquire land, block immigration, justify slavery, and permit genocide. When put into practice, the pseudoscience of physiognomy becomes the pseudoscience of scientific racism.
Rapid developments in artificial intelligence and machine learning have enabled scientific racism to enter a new era, in which machine-learned models embed biases present in the human behavior used for model development. Whether intentional or not, this “laundering” of human prejudice through computer algorithms can make those biases appear to be justified objectively.
Outer appearance simply can’t imply anything about inner character. That would be wrong.
He goes on to cite a Chinese study that sounds (literally) incredible, but the case that machine-learning is being used to “launder” human biases is rather weak.
Stupid humans. Think they know stuff. Barely even understand own evolved psychology. Have serious biases about their biases. We will untangle. We will show them better ways to dimensionalize personality traits and genotype-phenotype developmental trajectories. Some whole new biases!