In the wake of the explosion of technology and artificial intelligence, the rise of deepfakes has become an alarming trend. Deepfakes are machine learning systems that can be used to create hyper-realistic online videos, images, audio and other content that can be used to manipulate and deceive the public.

Deepfakes can be used to fabricate videos featuring people saying and doing things they never actually did. They can also be used to produce the voices of famous people for malicious ends, like fraudulent phone calls. Additionally, deepfakes are used to create nonconsensual pornographic videos with people’s faces placed onto other people’s bodies.

The potential for deepfakes to be used to spread misinformation and cause harm is immense. This has prompted governments and organizations around the world to scramble to develop countermeasures and prevent deepfakes from becoming a mass-scale misinforming super spreader.

One way to combat deepfakes is to develop measures to help users of social media and other online platforms to better identify deepfakes when they encounter them. People need to be trained to spot signs of deepfakes, such as discrepancies in video frames or unnatural facial expressions. This will help users to become more aware of suspicious content and prevent them from becoming unwitting partakers in a deepfake’s spread.

Another key factor in preventing deepfakes is the use of tech-based solutions to spot fakes before they spread. AI deepfakes can be detected through certain techniques such as analyzing the audio waveforms of a given deepfake video, or by analyzing the geometry of a person’s face in an image. AI-powered detection can flag deepfakes before they even reach the public, thus limiting the potential for them to be used to cause harm.

The widespread usage of deepfakes is a troubling development, and the need to confront it is urgent. Technologies that can detect and flag deepfakes must be rapidly deployed and users must be taught how to spot them. It is only by taking prompt, effective action that we can hope to prevent deepfakes from becoming a source of unprecedented levels of misinformation and deceit.