Scientist in Facebook data scandal says being scapegoated

Scientist in Facebook data scandal says being scapegoated

Aleksandr Kogan, a researcher at Cambridge University who created a personality quiz to collect users data on Facebook, gives evidence to Parliament's Digital, Culture, Media and Sport committe in Westminster, London.

The academic behind the app that allowed consulting firm Cambridge Analytica to farm the data of some 87 million Facebook users said today he was being scapegoated while the social network was being "mined left and right by thousands" of companies.

Aleksandr Kogan, who teaches at Cambridge University, told a British parliamentary committee that criticism of his work by Facebook showed the US social media giant was in "PR crisis mode".

"I don't believe they actually think these things because I think they realise that their platform has been mined left and right by thousands of others," said the Russian-American scientist, who is now banned from Facebook.

"I was just the unlucky person that ended up somehow linked to the Trump campaign. It's convenient to point the finger at a single entity," he said, playing down his own work as of little political value.

Kogan created a personality prediction app through his company Global Science Research (GSR), which offered a small financial payment in return for users filling out a personality test.

Facebook says it was downloaded by 270,000 people, but it also gave Kogan access to their friends, giving him a wealth of information on 90 million users, according to the social media giant's boss Mark Zuckerberg.

The data was sold to Cambridge Analytica's parent company.

Cambridge Analytica went on to work on Donald Trump's 2016 presidential campaign. However, Kogan told MPs today that the data was too imprecise to build up accurate profiles that could be used to effectively target political Facebook ads.

"One of the biggest points of confusion has been how accurate the personality scores we provided to SCL (CA's parent company) were," he said.

"The scores were highly inaccurate. We found that the scores were more accurate than a random guess, but less accurate than assuming everyone is average on every trait." 

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