In May last year, a video surfaced online in which Donald Trump berated Belgium for not doing enough to tackle climate change.

¡°As you know I had the balls to withdraw from the Paris climate agreement. And so should you,¡± the US president appeared to say.

If this sounds slightly unbelievable, that¡¯s because it was: the video was a fabrication by the Flemish Socialist Party. At the end of the video, ¡°Trump¡± admits as much, although the clip still fooled some online commentators.

This was one of the early ¨C and relatively crude ¨C examples of a political ¡°deepfake¡±, a new breed of sometimes spookily realistic videos that some fear could derail democracy itself.

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¡°You can get the president of the United States to say whatever you want to say and make it look fairly realistic with relatively little time and effort,¡± warned Matthew Wright, director of the Center for Cybersecurity Research at the Rochester Institute of Technology and one of a number of academics racing to find detection systems for deepfakes before they proliferate across the web.

Manipulated videos and images ¨C ¡°shallowfakes¡± ¨C have been around for decades. But deepfakes are made using so-called deep learning, a type of artificial intelligence that in some respects mimics the human brain. This allows ¡°just about anybody who has basic fluency with computers¡± to automate a previously laborious manual effort requiring skills with a program such as Photoshop, explained Professor Wright. ¡°They are getting better¡± all the time, he said

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Earlier this year, Professor Wright and his team won a $100,000 (?82,600) grant from the Ethics and Governance of AI Initiative, part of a of funding to help newsrooms use machine learning to improve their coverage. His team hopes to create a website where journalists with ¡°legitimate credentials¡± can use Rochester¡¯s own checks on videos suspected of fakery.

Opening up such a website to the broader public, however, would allow deepfake creators to figure out how Professor Wright¡¯s detection tool worked ¨C and adjust their own methods to avoid being caught.

There is an ¡°arms race¡± between academics¡¯ detection systems and deepfake creators, said Edward Delp, a professor at Purdue University specialising in media security and one of the researchers involved in a project to create deepfake detection tools for the US¡¯ Defense Advance Research Projects Agency.

The risk is not just of fake videos of politicians. Such technology also allows the creation of ¡°fake revenge porn¡± ¨C where photos of a victim are used in fabricated pornography ¨C something that has already been . Meanwhile, Professor Wright has been contacted by the risk team of a large corporation; he assumes they are worried about deepfakes of their chief executive.

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His aim is to create detection tools for others. But should academics directly intervene to test a video¡¯s veracity? Earlier this year, Heinz-Christian Strache, who was then the vice-chancellor in the Austrian government, was caught by hidden cameras in an Ibiza holiday villa offering to trade public contracts for illegal donations and positive media coverage for his far-right Freedom Party. He subsequently resigned, triggering fresh elections set for September. Experts from Germany¡¯s Fraunhofer Institute for Secure Information Technology helped journalists who obtained the video to verify that it was genuine.

For Professor Delp, though, this kind of direct testing, despite ¡°many, many¡± requests, was off limits. ¡°The downside is too high,¡± he said, as ¡°you could get sucked into legal problems, or political debates ¨C I¡¯m really not interested in that.¡± Instead, he saw his role as developing underlying methods that can be deployed by others.

It is also unclear whether this kind of post hoc fact-checking will change anyone¡¯s mind.

¡°We can label a video as being fake, but the question is whether people are going to believe that it¡¯s fake. And I?don¡¯t know how to do that problem,¡± Professor Delp said.

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The risk is that videos get out, go viral, and are viewed by millions before they are debunked ¨C with the damage already done. ¡°Our brains don¡¯t work that way¡­you can¡¯t unsee,¡± said Professor Wright.

This is why academics tackling deepfakes say they need the major online platforms to install automatic detection: flagging and blocking systems to stop deepfakes before they go viral. Professor Delp has talked to social media companies about this issue, but did not disclose which ones.

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¡°We [academics] can make a difference, but we need the cooperation of the social media companies,¡± said Hany Farid, a professor at the University of California, Berkeley, specialising in image analysis. ¡°To this end, we are working with Facebook under a research grant to operationalise some of our forensic work in detecting deepfakes and misinformation in general. We are also working with Google on similar efforts,¡± he said.

david.matthews@timeshighereducation.com