"Deepfakes probably are still best known for their bad uses. Just a couple of years after deepfakes hit the internet in 2017, the vast majority of deepfakes were pornographic, often depicting famous people doing things they hadn't actually been recorded doing. Later, deepfakes were being deployed for political destabilization, even as wartime disinformation tactics. For instance, not long after Russia invaded Ukraine in 2022, a deepfake spread on social media, falsely depicting Ukrainian President Volodymyr Zelensky as telling his people to surrender."
"More generally, there are justified worries that the proliferation of deepfakes-or perhaps even knowledge about deepfakes-is likely to erode social trust in digital media as reliable sources of evidence supporting critical parts of our social and political infrastructure, e.g., the role of video evidence in legal proceedings. That's all bad. But are there good uses for deepfakes? Yes, but I'll come back to those shortly."
Deepfakes are defined loosely as realistic digital video, audio, or image media generated by contemporary machine learning techniques. Classic deepfakes replace the likeness of one person in a source video with another person's likeness, while newer models can generate wholly new media from scratch. Early uses were predominantly pornographic soon after 2017, and deepfakes later appeared in political destabilization and wartime disinformation. The spread of deepfakes threatens social trust in digital media and undermines the evidentiary role of video in legal and political institutions. Honest, trustworthy use of deepfakes remains difficult despite potential beneficial applications.
Read at Apaonline
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