The study discovered that a higher proportion of people thought white faces generated by artificial intelligence were human than photos of actual people.

The same, however, wasn’t true for images of people of colour. Dr Amy Dawel, the senior author of the paper, said that the reason for the discrepancy is that AI algorithms are trained disproportionately on white faces.

“If White AI faces are consistently perceived as more realistic, this technology could have serious implications for people of colour by ultimately reinforcing racial biases online,” explained Dr Dawel.

“This problem is already apparent in current AI technologies that are being used to create professional-looking headshots. When used for people of colour, the AI is altering their skin and eye colour to those of White people.”

The researchers also found that people often don’t realise they’re being fooled, highlighting the sheer effectiveness of AI’s image-making capabilities.

“Concerningly, people who thought that the AI faces were real most often were paradoxically the most confident their judgements were correct,” said Elizabeth Miller, study co-author and PhD candidate at the Australian National University.

“This means people who are mistaking AI imposters for real people don’t know they are being tricked.”

Although there are physical differences between real faces and ones that are generated by AI, people tend to misinterpret them, Dr Dawel noted. “For example, White AI faces tend to be more in-proportion and people mistake this as a sign of humanness.

“However, we can’t rely on these physical cues for long. AI technology is advancing so quickly that the differences between AI and human faces will probably disappear soon.”

In response to the numerous, serious implications of this — not least concerning cyber-crime — the researchers have called for increased transparency around AI and its development.

“AI technology can’t become sectioned off so only tech companies know what’s going on behind the scenes. There needs to be greater transparency around AI so researchers and civil society can identify issues before they become a major problem,” Dr Dawel said.

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Further, the researchers advocated for greater public awareness on the issue as well as actionable tools, thereby helping to reduce the risks posed by the technology.

“Given that humans can no longer detect AI faces, society needs tools that can accurately identify AI imposters,” Dr Dawel advised.

“Educating people about the perceived realism of AI faces could help make the public appropriately sceptical about the images they’re seeing online.”

Dr Clare Sutherland, who also co-authored the paper, added: “As the world changes extremely rapidly with the introduction of AI, it’s critical that we make sure that no one is left behind or disadvantaged in any way – whether due to their ethnicity, gender, age, or any other protected characteristic.”