Thy can also accurately determine our religious and political beliefs, whether we take drugs, and our ethnicity. It’s done through comparatively simple statistical analysis – which anyone can do. Smart marketers are already doing this sort of profiling, which is likely to become much more widespread in future.
The study was conducted by a team led by Michael Kosinksi at the University of Cambridge and published in the Proceedings of the Natural Academy of Sciences.
“Facebook Likes can be used to automatically and accurately predict a range of highly sensitive personal attributes,” says Kosinski. “These include sexual orientation, ethnicity, religious and political views, personality traits, intelligence, happiness, use of addictive substances, parental separation, age, and gender.”
The analysis was based on a dataset of over 58,000 US volunteers who provided their Facebook Likes, detailed demographic proﬁles, and the results of several psychometric tests. The model uses statistical techniques called dimensionality reduction and linear regression to predict individual psychodemographic proﬁles from Likes.
“The model correctly discriminates between homosexual and heterosexual men in 88% of cases, African Americans and Caucasian Americans in 95% of cases, and between Democrat and Republican in 85% of cases,” says Kosinski.
“A growing proportion of human activities, such as social interactions, entertainment, shopping, and gathering information, are now mediated by digital services and devices. Such digitally mediated behaviours can easily be recorded and analysed, fuelling the emergence of computational social science and new services such as personalised search engines, recommender systems, and targeted online marketing.”
But Kosinski says the widespread availability of extensive records of individual behaviour, together with the desire to learn more about customers and citizens, presents serious challenges related to privacy and data ownership. “We need to distinguish between data that are actually recorded and information that can be statistically predicted from such records.
“People may choose not to reveal certain pieces of information about their lives, such as their sexual orientation or age, and yet this information might be predicted in a statistical sense from other aspects of their lives that they do reveal. For example, a major US retail network used customer shopping records to predict pregnancies of its female customers and send them well-timed and well targeted offers.
“In some contexts, an unexpected ﬂood of vouchers for prenatal vitamins and maternity clothing may be welcome, but it could also lead to a tragic outcome, e.g., by revealing (or incorrectly suggesting) a pregnancy of an unmarried woman to her family in a culture where this is unacceptable.
“Predicting personal information to improve products, services, and targeting can also lead to dangerous invasions of privacy. Predicting individual traits and attributes based on various cues, such as samples of written text, answers to a psychometric test, or the appearance of spaces people inhabit, has a long history.”
Location within a friendship network at Facebook is also predictive of sexual orientation. Kosinski says the study demonstrates the degree to which relatively basic digital records of human behaviour can be used to automatically and accurately estimate a wide range of personal attributes that people would typically assume to be private.
“One can imagine situations in which such predictions, even if incorrect, could pose a threat to an individual’s well-being, freedom, or even life. Importantly, given the ever-increasing amount of digital traces people leave behind, it becomes difﬁcult for individuals to control which of their attributes are being revealed. For example, merely avoiding explicitly homosexual content may be insufﬁcient to prevent others from discovering one’s sexual orientation.
“There is a risk that the growing awareness of digital exposure may negatively affect people’s experience of digital technologies, decrease their trust in online services, or even completely deter them from using digital technology. It is our hope, however, that the trust and goodwill among parties interacting in the digital environment can be maintained by providing users with transparency and control over their information, leading to an individually controlled balance between the promises and perils of the Digital Age.”
Big Brother is already here. He is your Facebook account.