A new study has demonstrated that computers that use digital footprints can judge personality better than the user's friends and family.
A new study has demonstrated that computers that use digital footprints can judge personality better than the user's friends and family.
The study, conducted at University of Cambridge, compares the ability of computers and people to make accurate judgments about our personalities. People's judgments were based on their familiarity with the judged individual, while computer models used a specific digital signal: Facebook likes. The results show that by mining Facebook likes, the computer model was able to predict a person's personality more accurately than most of their friends and family.
Researchers at the University of Cambridge and Stanford University describe the finding as an "emphatic demonstration" of the capacity of computers to discover an individual's psychological traits through pure data analysis, showing machines can know us better than we'd previously thought: an "important milestone" on the path towards more social human-computer interactions. Lead author Wu Youyou, from Cambridge's Psychometrics Centre, said that in the future, computers could be able to infer our psychological traits and react accordingly, leading to the emergence of emotionally-intelligent and socially skilled machines.
In the study, a computer could more accurately predict the subject's personality than a work colleague by analysing Facebook likes i.e. more than a friend or a cohabitant (roommate) with 70, a family member (parent, sibling) with 150, and a spouse with 300 Likes. To gauge the accuracy of these measurements, the online personality judgements were corroborated with a meta-analysis of previous psychological studies over decades which looked at how people's colleagues, family and so on judge their personality. Researchers found their online values similar to the averages from years of person-to-person research.
Dr Michal Kosinski, co-author and researcher at Stanford, said that machines have a couple of key advantages that make these results possible; the ability to retain and access vast quantities of information, and the ability to analyse it with algorithms--the techniques of 'Big Data'.
The study is published in the journal PNAS.
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