Technology alone is not enough to combat deepfakes, we need a concerted effort
Narendra Modi, the Prime Minister of India, declared in a speech recently that he himself had become a victim of a ‘deepfake.’ He was shown participating in a folk dance that he did not participate in. He went on to say that he had personally talked to ChatGPT’s maker OpenAI about it. A few days before that, India’s IT minister had warned AI and social media firms that they needed to weed out deep-fakes.
Earlier that week, three of India’s most popular film actors had suffered from deep-fake scandals. While we seem to have seen a spate of deep-fakes recently, this phenomenon is not new. There is the infamous case of a Christmas broadcast featuring Queen Elizabeth seemingly delivering a message, only for it to be revealed as a deep-fake designed to highlight the potential dangers of this technology.
Another example is a manipulated video of US politician Nancy Pelosi, who seemed intoxicated during an official speech. A more recent video clip was of a debonair looking Pope in a white Balenciaga puffer jacket. The world’s first ‘certified’ deep-fake was probably of an AI professional, Nina Schick, delivering a warning about how “the lines between reality and fiction are becoming blurred." Manipulated or concocted videos are called ‘deep-fakes,’ a term that combines two words—‘deep learning’ and ‘fake’—as coined in 2017 on Reddit.
The same Reddit thread morphed the faces of actors like Gal Gadot and Taylor Swift onto porn stars, opening a Pandora’s Box. Around 95% of all deep-fakes are estimated to be pornographic, causing an untold number of women distress. The technology behind deep-fakes is called Generative Adversarial Networks (GANs), invented by a famous AI scientist, Ian Goodfellow.
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