systematic attempts to extract secret information such as sexuality, emotional state, or medical records. But in this case still more serious for several reasons.the
In an article published in the Journal of Personality and Social Psychology, describes in detail quite a common approach based on reinforcement learning, the task of which is determination of the possibility to identify people as gay or not in their faces. Note: work is still in the form of a draft.
Using a database with pictures of faces (which were taken from Dating websites with open data), the scientists gathered 35 326 pictures 14 776 people, among which were equally represented homosexual men and women. Their facial features were extracted and calculated from the shape of the nose and eyebrows to facial hair and facial expressions.
The neural Network deep learning ate all of these features, noticing which are usually associated with a certain sexual orientation. Scientists are not "seeded" it with preconceptions about how usually are people with normal or homosexual orientation; the system simply assigned features and correlated them with the sexual preferences.
These patterns can be accessed to allow the computer to guess the sexual preferences of the person and it turned out that the AI system is much better at handling this task than humans. The algorithm was able to correctly determine the orientation of 91% of the men and 83% women, two at a time. The people who provided those images were right in 61% and 54% of cases, respectively — that is, a coin toss would give the same result.
Variations between the four groups described in the second article; aside from the obvious behavioral differences, like courting the same group or a similar makeup, the General trend was in the presence of "female" traits in gay men and "masculine" traits in lesbians.
the figure shows, where features indicating sexual orientation
It Should be noted that the accuracy of the system was achieved in ideal conditions the choice between two people, one of whom is homosexual. When the system was evaluated in a group of 1,000 individuals, of which only 7% belonged to homosexual people (for more representativeness is the actual percentage of the population), the results were not the best. In the best case a sample of 10 individuals were recognized with 90% accuracy.
There is also a real possibility of bias in the system due to the data: first, they included only young white Americans of the type of man/woman and homosexual/normal.
"Despite our attempts to obtain a more diverse sample, we were limited to the study of white participants from the United States. Because of prejudice against homosexuals and the use of online Dating sites are unevenly distributed among different ethnic groups, we were unable to find a sufficient number of non-white homosexual members."
Although scientists suggest that other ethnic groups are likely to have similar facial patterns and the system will also be effective to define, in fact it is necessary to confirm and not to assume.
You can Also argue that the classifier is collected, the characteristic features of people on Dating sites, not without the help of the mechanism of self-selection, for example, American men with a normal sexual orientation can deliberately avoided appearance, which would show that they can be homosexual.
Of Course, the real effectiveness of this system reasonably questioned, since it is trained based on the limited amount of data and mostly effective examples from this pool. Further research will be necessary. However, it seems short-sighted to assume that the running system is impossible.the
Many argue that this technology is no better than "phrenology 2.0", shell when unrelated physical traits with complex internal processes, and that is understandable, but not true.
"Physiognomy is now widely and rightly rejected as a combination of superstition and racism disguised as science," the scientists write in the introduction to the work (physiognomy judging by the facial features, while the phrenologists studied the shape of t