Do you have any evidence that this effect results in machines making systematically wrong inferences?
Near as I can tell, your paper shows that these "biases" result in significantly more accurate predictions. For example, Fig 1 shows that a machine trained on human language can accurately predict the % female of many professions. Fig 2 shows the machine can accurately predict the gender of humans.
Normally I'd expect a "bias" to result in wrong predictions - but in this case (due to an unusual redefinition of "bias") the exact opposite seems to occur.
Near as I can tell, your paper shows that these "biases" result in significantly more accurate predictions. For example, Fig 1 shows that a machine trained on human language can accurately predict the % female of many professions. Fig 2 shows the machine can accurately predict the gender of humans.
Normally I'd expect a "bias" to result in wrong predictions - but in this case (due to an unusual redefinition of "bias") the exact opposite seems to occur.
(Drawing on your analogy with stereotypes, it's probably also worth linking to a pointer on stereotype accuracy: http://emilkirkegaard.dk/en/wp-content/uploads/Jussim-et-al-... http://spsp.org/blog/stereotype-accuracy-response )