̽��ֱ�� of Cambridge - Michal Kosinski

Computers using digital footprints are better judges of personality than friends and family

fpjl2 — Mon, 12 Jan 2015 20:05:04 +0000

A new study, published today in the journal PNAS, 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.

̽��ֱ��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. Given enough Likes to analyse, only a person's spouse rivalled the computer for accuracy of broad psychological traits.

Researchers at the ̽��ֱ�� of Cambridge and Stanford ̽��ֱ�� 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.

"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," said lead author Wu Youyou, from Cambridge's Psychometrics Centre.

"In this context, the human-computer interactions depicted in science fiction films such as Her seem to be within our reach."

̽��ֱ��researchers say these results might raise concerns over privacy as such technology develops; the research team support policies giving users full control of their digital footprint.

In the study, a computer could more accurately predict the subject's personality than a work colleague by analysing just ten Likes; more than a friend or a cohabitant (roommate) with 70, a family member (parent, sibling) with 150, and a spouse with 300 Likes.

Given that an average Facebook user has about 227 Likes (and this number is growing steadily), the researchers say that this kind of AI has the potential to know us better than our closest companions.

̽��ֱ��latest results build on previous work from the ̽��ֱ�� of Cambridge, published in March 2013, which showed that a variety of psychological and demographic characteristics could be predicted with startling accuracy through Facebook Likes.

In the new study, researchers used a sample of 86,220 volunteers on Facebook who completed a 100-item personality questionnaire through the 'myPersonality' app, as well as providing access to their Likes.

These results provided self-reported personality scores for what are known in psychological practice as the 'big five' traits: openness, conscientiousness, extraversion, agreeableness, and neuroticism— the OCEAN model. Through this, researchers could establish which Likes equated with higher levels of particular traits e.g. liking 'Salvador Dali' or 'meditation' showed a high degree of openness.

Users of the 'myPersonality' app were then given the option of inviting friends and family to judge the psychological traits of the user through a shorter version of the personality test. These were the human judges in the study—those listed on Facebook as friends or family expressing their judgement of a subject's personality using a 10-item questionnaire

Researchers were able to get a sample of 17,622 participants judged by one friend or family member, and a sample of 14,410 judged by two.

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.

In this way, the researchers were able to come up with accuracy comparisons between computer algorithms and the personality judgements made by humans. Given enough Likes, the computers came closer to a person's self-reported personality than their brothers, mothers or partners.

Dr Michal Kosinski, co-author and researcher at Stanford, says 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'.

"Big Data and machine-learning provide accuracy that the human mind has a hard time achieving, as humans tend to give too much weight to one or two examples, or lapse into non-rational ways of thinking," he said. Nevertheless, the authors concede that detection of some traits might be best left to human abilities, those without digital footprints or dependant on subtle cognition.

̽��ֱ��authors of the study write that automated, accurate, and cheap personality assessments could improve societal and personal decision-making in many ways—from recruitment to romance.

" ̽��ֱ��ability to judge personality is an essential component of social living— from day-to-day decisions to long-term plans such as whom to marry, trust, hire, or elect as president," said Cambridge co-author Dr David Stillwell. " ̽��ֱ��results of such data analysis can be very useful in aiding people when making decisions."

Youyou explains: "Recruiters could better match candidates with jobs based on their personality; products and services could adjust their behaviour to best match their users' characters and changing moods.

"People may choose to augment their own intuitions and judgments with this kind of data analysis when making important life decisions such as choosing activities, career paths, or even romantic partners. Such data-driven decisions may well improve people's lives," she said.

̽��ֱ��researchers say that this kind of data mining and its inferences has hallmarks of techniques currently used by some digital service providers, and that—for many people— a future in which machines read our habits as an open book on a massive scale may seem dystopian to those concerned with privacy.

It's a concern shared by the researchers. "We hope that consumers, technology developers, and policy-makers will tackle those challenges by supporting privacy-protecting laws and technologies, and giving the users full control over their digital footprints," said Kosinski.

Take the Facebook personality test yourself here: applymagicsauce.com

Researchers have found that, based on enough Facebook Likes, computers can judge your personality traits better than your friends, family and even your partner. Using a new algorithm, researchers have calculated the average number of Likes artificial intelligence (AI) needs to draw personality inferences about you as accurately as your partner or parents.

People may choose to augment their own intuitions and judgments with this kind of data analysis when making important life decisions

Wu Youyou

Ksayer1

Facebook's Infection

Some example personality traits and associated Likes

Liberal & artistic	Shy & reserved	Cooperative	Calm & relaxed
TED	J-pop	Life of Pi	Ferrari
John Coltrane	Minecraft	the Bible	Volunteering
̽��ֱ��Daily Show	Wikipedia	smiling	Usain Bolt
Atheism	̽��ֱ��X-Files	Bourne Identity	Kayaking

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Digital records could expose intimate details and personality traits of millions

fpjl2 — Mon, 11 Mar 2013 18:49:49 +0000

New research, published today in the journal PNAS, shows that surprisingly accurate estimates of Facebook users’ race, age, IQ, sexuality, personality, substance use and political views can be inferred from automated analysis of only their Facebook Likes - information currently publicly available by default.

In the study, researchers describe Facebook Likes as a “generic class” of digital record - similar to web search queries and browsing histories - and suggest that such techniques could be used to extract sensitive information for almost anyone regularly online.

Researchers at Cambridge’s Psychometrics Centre, in collaboration with Microsoft Research Cambridge, analysed a dataset of over 58,000 US Facebook users, who volunteered their Likes, demographic profiles and psychometric testing results through the myPersonality application.

Users opted in to provide data and gave consent to have profile information recorded for analysis. Facebook Likes were fed into algorithms and corroborated with information from profiles and personality tests.

Researchers created statistical models able to predict personal details using Facebook Likes alone. Models proved 88% accurate for determining male sexuality, 95% accurate distinguishing African-American from Caucasian American and 85% accurate differentiating Republican from Democrat. Christians and Muslims were correctly classified in 82% of cases, and good prediction accuracy was achieved for relationship status and substance abuse – between 65 and 73%.

But few users clicked Likes explicitly revealing these attributes. For example, less that 5% of gay users clicked obvious Likes such as Gay Marriage. Accurate predictions relied on ‘inference’ - aggregating huge amounts of less informative but more popular Likes such as music and TV shows to produce incisive personal profiles.

Even seemingly opaque personal details such as whether users’ parents separated before the user reached the age of 21 were accurate to 60%, enough to make the information “worthwhile for advertisers”, suggest the researchers.

While they highlight the potential for personalised marketing to improve online services using predictive models, the researchers also warn of the threats posed to users’ privacy. They argue that many online consumers might feel such levels of digital exposure exceed acceptable limits - as corporations, governments, and even individuals could use predictive software to accurately infer highly sensitive information from Facebook Likes and other digital ‘traces’.

̽��ֱ��researchers also tested for personality traits including intelligence, emotional stability, openness and extraversion. While such latent traits are far more difficult to gauge, the accuracy of the analysis was striking. Study of the openness trait – the spectrum of those who dislike change to those who welcome it – revealed that observation of Likes alone is roughly as informative as using an individual’s actual personality test score.

Some Likes had a strong but seemingly incongruous or random link with a personal attribute, such as Curly Fries with high IQ, or That Spider is More Scared Than U Are with non-smokers.

When taken as a whole, researchers believe that the varying estimations of personal attributes and personality traits gleaned from Facebook Like analysis alone can form surprisingly accurate personal portraits of potentially millions of users worldwide.

They say the results suggest a possible revolution in psychological assessment which – based on this research – could be carried out on an unprecedented scale without costly assessment centres and questionnaires.

“We believe that our results, while based on Facebook Likes, apply to a wider range of online behaviours.” said Michal Kosinski, Operations Director at the Psychometric Centre, who conducted the research with his Cambridge colleague David Stillwell and Thore Graepel from Microsoft Research.

“Similar predictions could be made from all manner of digital data, with this kind of secondary ‘inference’ made with remarkable accuracy - statistically predicting sensitive information people might not want revealed. Given the variety of digital traces people leave behind, it’s becoming increasingly difficult for individuals to control.

“I am a great fan and active user of new amazing technologies, including Facebook. I appreciate automated book recommendations, or Facebook selecting the most relevant stories for my newsfeed,” said Kosinski. “However, I can imagine situations in which the same data and technology is used to predict political views or sexual orientation, posing threats to freedom or even life.”

“Just the possibility of this happening could deter people from using digital technologies and diminish trust between individuals and institutions – hampering technological and economic progress. Users need to be provided with transparency and control over their information.”

Thore Graepel from Microsoft Research said he hoped the research would contribute to the on-going discussions about user privacy: “Consumers rightly expect strong privacy protection to be built into the products and services they use and this research may well serve as a reminder for consumers to take a careful approach to sharing information online, utilising privacy controls and never sharing content with unfamiliar parties.”

David Stillwell from Cambridge ̽��ֱ�� added: “I have used Facebook since 2005, and I will continue to do so. But I might be more careful to use the privacy settings that Facebook provides.”

For more information, please contact fred.lewsey@admin.cam.ac.uk

Research shows that intimate personal attributes can be predicted with high levels of accuracy from ‘traces’ left by seemingly innocuous digital behaviour, in this case Facebook Likes. ̽��ֱ��study raises important questions about personalised marketing and online privacy.

Similar predictions could be made from all manner of digital data, with this kind of secondary ‘inference’ made with remarkable accuracy

Michal Kosinski

Cambridge Psychometrics Centre

Graphic from mypersonality app

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Are we being sold online?

fpjl2 — Sat, 27 Oct 2012 08:00:06 +0000

One in every nine people on Earth is on Facebook and the average Briton devotes an entire day to the site each month. Personal information, much of it volunteered, has become so prevalent and readily available that for many it constitutes the most powerful marketing tool in human history. ̽��ֱ��question is, how is this information being used, and by whom? And, should we be worried?

Listen to the debate here:

From 3:30pm on Saturday afternoon (27 October) at the Faculty of Law, a panel of experts will explore the questions that surround the dream of global connectivity, and the nightmare of human commodity, as part of this year’s Festival of Ideas.

From social interactions, entertainment, shopping, and gathering information, almost any human activity you can think of is now mediated digitally. As such, these behaviours can easily be recorded and analysed, fuelling the emergence of personalised search engines, recommender systems, and targeted online marketing.

This raises highly sensitive questions about privacy and data ownership. Who should have access to such an extraordinarily powerful reservoir of information, and where it should be stored?

“ ̽��ֱ��widespread availability of extensive records of individual behaviour, and the desire to learn more about customers and citizens presents serious challenges to future society, particularly in relation to trust,” says Michal Kosinski, Director of Operations for the ̽��ֱ��’s Psychometrics Centre and Leader of the e-Psychometrics Unit.

“Trust between consumers and corporations, governments and their citizens, families even can be seriously harmed once people realize how exposed they are in the digital environment. It can all still seem quite innocent, with Facebook ‘likes’ and photos of friends, but new research is starting to show that this seemingly harmless information can be used to make very accurate inferences of highly sensitive traits.”

Kosinski, one of the panellists, spends much of his time cultivating and analysing the increasingly immense tracts of data in order to show the precision with which estimations can be made about personality traits, such as openness, extroversion and stability.

“Never before have we had access to such comprehensive behavioural data about consumers,” says Kosinski. “A marketing revolution is upon us, a completely new dimension is added through the combination of scientifically robust personality tests and other demographic information.”

̽��ֱ��other panellists are William Dutton, Professor of Internet Studies at the ̽��ֱ�� of Oxford’s Internet Institute, Nick Pickles, Director of the civil liberties and privacy campaign group Big Brother Watch, and Mariam Cook, Senior Digital Consultant at PR firm Porter Novelli.

“ ̽��ֱ��web connects us more closely than ever before, giving organisations and brands the capability to understand us, target us, and to fulfil our needs and desires in increasingly sophisticated ways,” says Cook. “This presents many fantastic opportunities for marketers, and potential delights for those formerly known as the audience, but it also means great responsibility lies on our shoulders.”

“This presents a challenge - how to balance the apparently conflicting ideals of privacy and openness in all of our data dealings.”

But for Nick Pickles, the increasingly heard motto ‘if we're not paying to use a service, then we're the product’ is at the very core of this issue: “Our personal data is the oil of the internet age and yet we have grown oblivious to how our every movement is being monitored and analysed for commercial gain.”

“As an entire generation outsources it's privacy to social media companies, I believe strengthening individual privacy will soon become a social necessity and a commercial imperative.”

Panel discussion ‘Are we being sold online?’ starts at 3.30pm on Saturday 27 October at the Faculty of Law. With Michal Kosinski, Cambridge's Psychometrics Centre; Professor William Dutton, Oxford Internet Institute; Nick Pickles, Big Brother Watch; Mariam Cook, Porter Novelli and the Chair, Spencer Kelly, Click presenter.

A panel discussion for the Festival of Ideas examines whether social media giants are profiting from our willingness to share the most intimate details of our lives online, and whether we should be worried by this compromise to our privacy.

Never before have we had access to such comprehensive behavioural data about consumers.

Michal Kosinski

Ed Yourdon from flickr

Thinkin' about the code

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̽��ֱ�� of Cambridge - Michal Kosinski

Computers using digital footprints are better judges of personality than friends and family

Liberal & artistic

Shy & reserved

Cooperative

Calm & relaxed

Digital records could expose intimate details and personality traits of millions

Are we being sold online?