A recent study published in PNAS concludes that a computer is capable of predict a person’s personality more accurately than their own friends and family… from the analysis of some of the data we have left Facebook.
The researchers conclude that by analyzing 10 “likes”, a computer can better describe our personality than our colleagues; with 70, better than our friends or roommates; with 150, better than a parent; and with 300, better than a spouse. It is thus shown that machines, although they lack the social skills to interpret human language and intentions, may be able to make valid judgments about us by accessing our internet fingerprint.
Facebook knows you better than your own friends
For this research, a personality test based on the Big Five model was provided to 86,220 people. Each of them had to fill out these 100-item forms designed to record information about the different traits that define the way we act, perceive and feel things.
In addition to having the information obtained through personality tests, some volunteers also gave their permission to the research team to analyze the “I appreciate” which they had donated from their Facebook accounts. These “likes” are not the ones that can be clicked on on Facebook statuses, photos or videos, but those associated with pages on movies, books, TV shows, celebrities , etc.
Later, software has found trends and relationships between personality traits and certain preferences for either page located on this social network. For example, it has been found that people with a high score on “Open to Change” tend to show affection for Salvador Dalí or the TED Talks, while extroverts show a taste for dancing. This may be a conclusion that stems from stereotypes, and yet there is empirical evidence to support these ideas.
While the software played to learn how human behavior works, a group formed with the others. assessors who had to predict personality scores of volunteers. This group consisted of friends, family and acquaintances of the participants who had completed the test. Each of these flesh-and-blood judges had to describe the personality of the subject being assessed by completing a questionnaire. The results (somewhat humiliating for our species) at the head of the article emerged in the compare the degree of precision with which humans and machines predict personality scores. Only a Husband or Wife Can Compete With Computer Generated Personality Models from some data obtained by Facebook.
How can software speak with such precision about the aspects that define us and make us unique? The biggest advantage they have over us is theirs access to huge amounts of information the staff and their ability to relate some data to others and find patterns of behavior in fractions of a second. Thanks to this, computer-generated personality models can automatically predict certain behavioral patterns, without the need for social skills, and with more accuracy than humans.
As a result, today we are closer to know the characteristics of certain aspects of the psychology of people without having to interact with them face to face, After information about the movies, books and celebrities that we love, goes through a kitchen of algorithms. Given that the average “likes” that each of us has accumulated on Facebook is around 227, we can imagine what this innovation in psychometry means for statistical centers, recruitment agencies or even all the groups involved in espionage and social control. All this makes the website created by Mark Zuckerberg more streamlined as a tool. market segmentation than a social network.
In addition, the consequences that this may have on the world of advertising and marketing they are obvious. If today it is possible to largely like a person’s tastes and hobbies from their Google searches, perhaps in the future a car brand will be able to know which model can attract us the most because a day we made about twenty clicks on a social network.
One of the paradoxes of this psychological assessment methodology is that we study the qualities that make us social and unique without the need for social interaction and applying generic rules about human behavior. This prospect can be as appealing to organizations as Cambridge University you already have an app that lets you see what your Facebook profile, tweets, and other forms of fingerprints are saying about your psychological profile. One of the supposed benefits that can be read on their website is “it avoids having to ask unnecessary questions”. It remains to be seen how this methodology will affect privacy protection.
Big Data: Facebook and its database
Ultimately, it is now possible that computers are increasingly capable of deduce information about us that we have never declared directly, and that this information is of better quality than that deduced by anyone else. All of this can be made possible, in large part, by big data analytics. and Facebook: The massive processing of data (personal or other) that we provide voluntarily. The research team evokes this qualitative leap in the conclusions of their article:
Popular culture has come to depict robots outperforming humans when it comes to making psychological inferences. In the movie Her, for example, the protagonist falls in love with his operating system. By managing and analyzing your fingerprint, your computer can understand and respond to your thoughts and needs much better than other humans, including your girlfriend and closest friends. Our research, along with advances in robotics, provides empirical evidence that this hypothetical situation is becoming increasingly possible as digital assessment tools mature.
What will computing be capable of when a computer is able to read not only Facebook pages, but also photographs and texts with the same level of precision? Will we be beings without mystery in the eyes of mass processors? It is worth considering whether this form of understanding of the human being that machines can achieve in the future reflects our essence as unique feelings and people.
- Youyou W., Kosinski, M. and Stillwell, D. (2015). Computer-based personality judgments are more accurate than those made by humans. PNAS 112 (4), pages 1036-1040.