VIDEO - Sen. Chris Coons questions former Cambridge Analytica employee on company's use of Facebook data to influence American voters: "Was voter suppression a service that U.S. clients could request?"

Yesterday, Sen. Chris Coons questioned former Cambridge Analytica employee Christopher Wylie in a Senate Judiciary Committee hearing on Cambridge Analytica’s use of illicit Facebook data to target political messaging.

Sen. Coons: Thank you to the panel for the chance to be with you today. I think the reason this matters is that we’re talking about the intersection of several important developments that are difficult for the average American to understand: big data and social media and foreign interference in our 2016 election. And, we are trying to tease out what actually happened or didn’t happen. Mr. Wylie, let me start with you.

Cambridge University Professor Michal Kosinski studied the use of Facebook data and found that, based on average of 68 Facebook likes by a user, there are just likes, what you liked and disliked, you could predict sexual orientation, political party affiliation, race, with 85% accuracy. Further factors like religious affiliation, alcohol or drug use, even whether your parents were divorced could be deduced. Is that your understanding of that analysis and do you think Cambridge Analytica and the work of

Professor Kogan used that predictive power to develop algorithms that then weaponized differences between different Americans for electoral gain?

Mr. Wylie: So, the basis of the research we were doing at Cambridge Analytica was from the papers that you’re citing from Dr. Kosinski. So, the firm replicated his approach and then sought to improve it.

Sen. Coons: And, did I correctly summarize the incredibly high correlation that you could show in terms of really knowing the individual Facebook user if you had access to their likes and their friends and their social media activity.

Mr. Wylie: Yes, the particular paper that you’re citing, the number of likes once you surpass 100 and 200, you can get to the same level of accuracy at predicting for example personality traits as your spouse would if they were answering questions about you and in comparison, how you would answer.

Sen. Coons: Okay, to the point that Professor Hersh made earlier, all of us who have stood for election have struggled with the difficulty of actually targeting our votes effectively. Because, the data sets we’ve had access to, mostly publicly available data, are very thin, very narrow, there is very little that we have. The data sets that Facebook has access to, that’s why it’s a multi-billion-dollar company, are unbelievably deep and rich. And, so it’s unlike anything we’ve had to confront before, correct?

Mr. Wylie: Yeah, I don’t contest what Professor Hersh was saying in the sense that there are, it is true, persuading someone compared to motivating them to turn out is much more difficult and the data sets that traditionally were used are often very sparse and not necessarily reliable.

Sen. Coons: The data sets that are available now through Facebook are orders of magnitude...

Mr. Wylie: Yes, and that’s why Cambridge Analytica ended up pursuing that path, because it found that, in comparison to traditional marketing data sets, the data that you could procure from social networking sites was much denser and actually much more reliable to create a precise algorithm.

Sen. Coons: And, to be clear, a billionaire, American, megadonor and supporter of the Trump campaign funded a shell corporation, Cambridge Analytica, still run by foreign nationals, to take advantage of this research, this understanding, and gained access to 87 million Americans Facebook information and developed some of the algorithms that came out of that.

I want to ask you in the time I have remaining about your experience with Steve Bannon, one of President Trump’s senior campaign advisors and the goals he used Cambridge Analytica to achieve. Was one of Bannon’s goals to suppress voting certain or discourage certain individuals in the U.S. from voting?

Mr. Wylie: That was my understanding, yes.

Sen. Coons: Was voter suppression a service that U.S. clients could request in their contracts with Cambridge Analytica while Bannon was vice president?

Mr. Wylie: Yes.

Sen. Coons: And, so Steve Bannon is running an organization where you could, as a client, request in contracts voter suppression using this remarkable data set?

Mr. Wylie: I don’t know if it was referenced in contracts, but I have seen documents that make reference to it in relation to client requests and services provided.

Sen. Coons: Okay, one last question.

You testified that back in 2014, Cambridge Analytica set up focus groups, message testing, and polling on Americans’ views on the leadership of Vladimir Putin and Russia’s expansionism in Eastern Europe. You’ve also testified that it’s entirely possible, would have been relatively easy for Russian intelligence to put a key logger on Professor Kogan’s computer and get access to this full data set.

Why do you think Cambridge Analytica was testing Putin’s aggressive actions and what threat would it pose to our 2018 elections if this entire data set, all the algorithms that go with it, are currently in the hands of Russian intelligence?

Mr. Wylie: So, I don’t have a clear answer as to why the company was so engaged in testing Russian expansionism and the leadership of Vladimir Putin.

That’s a question better put to Steve Bannon. In terms of the dangers for not just American democracy, but other democracies around the world, this data is powerful and if it is put into the wrong hands, it becomes a weapon.

And, we have to understand that companies like Facebook and platforms like Facebook and Twitter are not just social networking sties, they’re opportunities for information warfare. Not just by state actors, but by non-state actors. And, so we really do need to look at protecting cyberspace as a national security issue in the same way that we have agencies to protect our borders, land, sea, and air.

Sen. Coons: Thank you very much, Mr. Wylie.