Michal Kosinski to appear at the CeBIT Global Conferences
Can intelligent Big Data technologies sway election outcomes? Are consumers now "public domain"? How do I go about having an online life while still protecting my privacy? Answers to these questions and more will be provided by the noted social scientist Dr. Michal Kosinski, from the Stanford University Graduate School of Business, when he takes the stage at the CeBIT Global Conferences on 23 March.
Kosinski enjoys international renown as an expert on psychometrics – a rapidly up-and-coming area of psychology that deals, among much else, with the influence of Big Data and other digital technologies. While studying at Cambridge University, Kosinski developed a mathematical method that analyzes Facebook likes and publicly available data to determine people's personality traits and predict their behavior. His method was used by the Trump campaign to spread personalized posts via a range of social media channels in the run-up to the presidential election.
Psychometric tools for pushing consumer goods, and even political messages
Personalized advertising has been part of online life for a long time. But psychometric targeting opens up completely new opportunities – particularly for marketing services and consumer goods. In today's age of Big Data, wearables, car connectivity and the Internet of Things, the average consumer generates vast stores of personal data with everything they do, whether it's driving their car or strapping on a fitness tracker. This data is an absolute bonanza for corporations, who can, within certain legal constraints, harvest it to tailor their marketing message to specific consumer groups.
"A growing proportion of human activities, such as social interactions, entertainment, shopping, and gathering information, are now mediated by digital services and devices. Our research shows that capturing digital behavior patterns, such as tweets, Facebook likes or web browser logs, is sufficient to be able to build up a detailed picture of an individual's personality, intelligence or political leanings. These types of Big Data analysis do not require any active participation on the part of the data subjects. They can be applied to large populations, are cost-effective and potentially have revolutionary applications in many areas. But in the wrong hands, they pose substantial risks to privacy."
For these reasons, Kosinski urges people to support individuals, organizations and corporations who are committed to safeguarding privacy, whether in the context of purchase decisions, clicks in social networks or political elections. Misuse of privacy for political gain doubtless harbors real risks. For instance, intelligent Big Data technologies could well be used to influence France's presidential elections this spring or Germany's parliamentary elections in the fall.