AI can create such realistic human faces that people can’t distinguish them from real faces – and they actually trust the fake faces more. Fictional, computer-generated human faces are so convincing they can fool even trained observers. They can be easily downloaded online and used for internet scams and fake social media profiles. AI programs called generative adversarial networks (GANs), can learn to create fake images that are less and less distinguishable from real images, by pitting two neural networks against each other. Researchers at the University of California, Berkeley, asked 315 participants, recruited on a crowdsourcing website, to say whether they could distinguish a selection of 400 fake photos from 400 photographs of real people. Each set consisted of 100 people from each of four ethnic groups: white, Black, East Asian and South Asian.
This group had an accuracy rate
of 48.2% (slightly worse than chance). A second group of 219 participants were
given training to recognise computer-generated faces. This group had an
accuracy rate of 59%. White faces were the hardest for people to distinguish
between real and fake, perhaps because the synthesis software was trained on
disproportionally more white faces. The researchers also asked a separate group
of 223 participants to rate a selection of the same faces on their level of
trustworthiness, on a scale of 1 to 7. They rated the fake faces as 8 per cent
more trustworthy, on average, than the real faces (a small yet significant
difference). That might be because synthetic faces look more like average human
faces, and people are more likely to trust typical-looking faces. Looking at
the extremes, the four faces rated most untrustworthy were real, whereas the
three most trustworthy faces were fake.
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