On January 21, Patricia Gingrich was about to sit down for dinner when her landline phone rang. The New Hampshire voter picked up and heard a voice telling her not to vote in the upcoming presidential primary. "As I listened to it, I thought, gosh, that sounds like Joe Biden," Gingrich told Al Jazeera. "But the fact that he was saying to save your vote, don't use it in this next election -- I knew Joe Biden would never say that." The voice may have sounded like the United States president, but it wasn't him: It was a deepfake, generated by artificial intelligence (AI).

Drug discovery companies such as Insilico Medicine are using deepfake AI technology to design new molecules that can help treat diseases. Intel made a splash earlier this week when it unveiled its latest technology that can detect a deepfake in real-time with 96pc accuracy. AI such as this can help organisations around the world to prevent the spread of misinformation and protect themselves from cybercrime. But not all kinds of deepfakes are bad. The advancement of any emerging technology brings with it positive and negative uses – and the future of healthcare certainly has much to gain from deepfakes.

Today, the most successful and damaging cyberattacks are executed by highly professional criminal networks rather than "lone-wolf" hackers. These criminal organizations have also become highly adept at leveraging artificial intelligence (AI) and machine learning (ML) tools, making it extremely hard for IT security organizations to keep up -- much less stay ahead of these threats. Cybercriminals are using AI and ML to exploit vulnerabilities such as user behavior or security gaps to gain access to valuable business systems and data. A perfect example of these types of threats are deepfakes – they are realistic, hard to detect and surprisingly easy-to-create facsimiles of real people. Deepfakes have been rightly denounced for the personal harm they inflict through celebrity pornographic videos, the spread of fake news, conspiracy theories, hoaxes and financial fraud.