House holds hearing on “deepfakes” and artificial intelligence

The House Intelligence Committee heard from experts on the threats that so-called “deep fake” videos and other types of artificial intelligence-generated synthetic data pose to the U.S. election system and national security at large. Witnesses at Thursday’s hearing included professors from the University of Maryland, University at Buffalo and other experts on AI and digital policy. 

In a statement, the committee says it aims to “examine the national security threats posed by AI-enabled fake content, what can be done to detect and combat it, and what role the public sector, the private sector, and society as a whole should play to counter a potentially grim, ‘post-truth’ future,” during Thursday’s hearing. 

The hearing comes amid a growing trend of internet videos showing high-profile figures appearing to say things they’ve never said. 

Trending News

Recently, a doctored video of House Speaker Nancy Pelosi, in which she appears to be impaired, made the rounds on social media. The video garnered more than 2.5 million views on Facebook after President Trump shared it in an attempt to make light of Pelosi’s speech patterns and fitness for office. Republicans and Democrats are now concerned these manipulated videos will become the latest weapon in disinformation wars against the United States and other Western democracies.

“Deep fakes raise profound questions about national security and democratic governance, with individuals and voters no longer able to trust their own eyes or ears when assessing the authenticity of what they see on their screens,” the committee said in a statement. 

In his opening remarks, Committee chair Rep. Adam Schiff said the spread of manipulated videos presents a “nightmarish” scenario for the 2020 presidential elections — leaving lawmakers, members of the news media and public “struggling to discern what is real and what is fake.”

Schiff urged that “now is the time for social media companies to put in place policies to protect users from

View Source