We have become to rely on machine learning systems in everything from creating playlists to control cars, but like any tool, they can be used in a dangerous and unethical purposes, even by accident. Today's illustration of this fact — a new article by researchers from Stanford who created a system of machine learning, which, they claim, can tell you several photo... gay in front of you. Or not.
Obviously, this study is surprising and disheartening in equal measure. Besides the fact that vulnerable group of people once again will be subject to a systematic invasion of privacy and intimate themes, this directly affects the egalitarian notion that we cannot (and should not) judge a person by his appearance, and does not have the right to guess the sexual orientation of one or two images. Absurd? The system accuracy reported in the work, however, leaves no room for doubt: it is now not only possible, but done.
The System picks up the emanations much more subtle than capable of vosprinimat people see the clue, which you do not even know. And it shows as intended that the privacy, private life in the era of ubiquitous computer vision can be simply destroyed.
Before proceeding to the discussion of the system itself, it is necessary to clarify that the study was conducted with good intentions. The questions, of course, there are countless. Most relevant, perhaps, were the remarks of Michal Kosinski and Elon Wong as to why the work actually saw the light:
"We were very concerned about these results and spent a lot of time to do them public. We didn't want to expose people to those risks about which they were warned. The ability to control when and to whom to disclose their sexual orientation, is crucial not only for human welfare but also for his safety."
"We thought that the legislators and the LGBTQ community needs to be aware of the risks faced. We did not create a tool of invasion of privacy, but rather showed that the simple and widely used methods pose a serious threat to life."
Definitely, this is just one of many 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 homo