Before Cambridge Analytica 'research' was 'gay' face and 'personality' studies
In a 2018 interview, the Stanford professor of organisational behaviour Michal Kosinski discussed his research, which included a controversial and widely debunked 2017 study claiming that his algorithms could distinguish gay and straight faces; a 2013 study of 58,000 people that explored the relationship between Facebook Likes and psychological and demographic characteristics; and the myPersonality project, which collected data on 6 million people via a personality quiz that went viral on social media and asked respondents for permission to donate their results to academic research. In May 2018, the quiz-generated dataset was discovered left open to the public on GitHub; for four years anyone could have accessed it. During that time about 280 researchers used it for research filling more than 100 academic papers, including Kosinski's 2013 study. Kosinski's research methods attracted the interest of the Russian cabinet and were later copied by Cambridge Analytica parent SCL Group, which tried to buy the myPersonality data and, after failing to do so, employed Cambridge psychologist Aleksandr Kogan to build a new one.
Writer: Paul Lewis
Data should be protected
Data should be protected from access by persons who are not the user.
Limit data analysis by design
As nearly every human interaction now generates some form of data, systems should be designed to limit the invasiveness of data analysis by all parties in the transaction and networking.
Control over intelligence
Individuals should have control over the data generated about their activities, conduct, devices, and interactions, and be able to determine who is gaining this intelligence and how it is to be used.
Identities under our control
Individuals must be able to selectively disclose their identity, generate new identities, pseudonyms, and/or remain anonymous.
We should know all our data and profiles
Individuals need to have full insight into their profiles. This includes full access to derived, inferred and predicted data about them.
We may challenge consequential decisions
Individuals should be able to know about, understand, question and challenge consequential decisions that are made about them and their environment. This means that controllers too should have an insight into and control over this processing.