Opinion: Content validation is hard to pull off, but it’s a huge market opportunity

Photo credit: Rawpixel

By now, you’ve probably seen the fake video of Barack Obama calling Donald Trump “a total and complete dipsh*t.”  The voice may not be exactly right, but the clip—which took a team of video pros at BuzzFeed 56 hours to create—vividly illustrates the nascent threat of deepfakes (i.e. digitally altered videos that can make anyone say anything).

Deepfake technology is already being widely (and controversially) used to insert celebrity faces into pornography. But it’s not hard to see how dangerous it may prove in the political realm. The threat is so real that DARPA, the US defense agency responsible for emerging military technology, has already assembled an official media forensics lab to sniff out fakes.

Of course, forged videos aren’t the only threat on the fake news front. There are also plain old fake headlines and news stories.

In the end, we’re left deeply uncertain about who and what to trust.

As someone who has built a career in social media, I find this worrying. I have tremendous faith in the power of social channels to create connection and open up dialogue, but the spread of fake content is a real and growing threat.

How do we restore trust and confidence in online content? To me, the way forward isn’t just an algorithm tweak or a new set of regulations. This challenge is far too complex for that. We’re talking, at root, about faith in what we see and hear online, about trusting the raw data that informs the decisions of individuals, companies, and whole countries.

The time for a band-aid fix has long passed. Instead, we may be talking about the digital era’s next growth industry: content validation.

The burgeoning content validation industry

Interestingly, we’re already seeing a flurry of activity in this arena, as the arms race between fakers and detectives accelerates.

The deepfake phenomenon, in particular, has inspired a growing technological response, outlined recently by Axios’ Kaveh Waddell.

The startup Trupic, which has just attracted more than US$10 million in funding from the likes of Reuters, has set its sights on sniffing out details like eye reflectivity and hair placement, which are nearly impossible to fake across the thousands of frames in a video.

Gfycat, the gif-hosting platform, uses AI-powered tools that check for anomalies to identify and pull down offending clips on its site.

On the academic and research front, scientists at Los Alamos are building algorithms that hunt out repeated visual elements (a tell-tale sign of video manipulation), while researchers from the University at Albany have developed a system that monitors video blinking patterns. DARPA and its media forensics team, meanwhile, look for inconsistencies in lighting on AI-generated faces.

The problem of fake text-based stories

Trickier still, however, is flagging fake and biased text-based news stories—the kind of content that’s easy to make and likeliest to find its ways into our social streams.

The future of trust