2 hours ago
https://www.eurekalert.org/news-releases/1135087
EXCERPTS: Psychology PhD student Alexis McGuire said: “Our research shows that people are at risk of being fooled by AI-generated images. These AI models have democratised the online space and they are accessible for anyone without technical skills to create fake faces that can be used for a variety of different harms. It is important to inform the public about the ease of creating such images and the potential misuses, and ways in which they might fall victim, for example, through the spread of misinformation, identify fraud, and catfishing.”
Humans are experts at processing real faces, automatically assessing a face in as little as 100 milliseconds. However, AI-generated faces are highly realistic and are becoming more trustworthy with newer, more sophisticated technology creating fake images that can fool people into thinking they are genuine around a third of the time.
When 169 participants were asked to look at a collection of 96 faces (diverse across race, gender, and age) presented at random and indicate whether each face was real or AI-synthesised, their average accuracy was 58.4% - only slightly better than random guessing (similar to flipping a coin at 50%). Surprisingly, faces generated by the newer AI diffusion model (DM) were rated as less realistic than faces produced by an earlier AI model (GAN).
However, in a follow up experiment, a new set of participants were asked to rate the trustworthiness of 96 faces presented at random on a scale of one (very untrustworthy) to seven (very trustworthy).
Real faces were rated as the least trustworthy with an average trust rating of 4.03. Both types of AI-synthesised faces were rated as more trustworthy than real faces while faces produced by the diffusion model (DM) were more trustworthy than both the real and GAN faces. GAN faces received an average trust rating of 4.36, and diffusion-synthesized DM faces were the most trustworthy with an average rating of 4.70.
Researchers say it is puzzling that AI synthesised faces generated by the newer AI diffusion model (DM) were rated as less realistic than faces produced by an earlier model (GAN) - but DM faces were still rated the most trustworthy. Alexis McGuire said: “This finding presents a paradox and thus highlights the possibility that realism and trustworthiness judgements are driven by two different psychological mechanisms.”
She warned of how AI faces generated using the latest DM technology could contribute to an overall erosion of trust in society. “As AI-generated images become more sophisticated and more accessible, as a society, we are increasingly exposed to artificially-generated faces—often in nefarious and exploitative scenarios, such as political disinformation, financial and identity fraud, and catfishing. It is critical to understand the threat this democratisation of generative AI brings as well as developing strategies to mitigate potential harms to individuals, organisations, and democracies.”
The research in the Journal of Vision entitled “AI-Generated Faces are Becoming More Trustworthy” was funded by The Centre for Research and Evidence on Security Threats (CREST) and Security Lancaster... (MORE - missing details, no ads)
EXCERPTS: Psychology PhD student Alexis McGuire said: “Our research shows that people are at risk of being fooled by AI-generated images. These AI models have democratised the online space and they are accessible for anyone without technical skills to create fake faces that can be used for a variety of different harms. It is important to inform the public about the ease of creating such images and the potential misuses, and ways in which they might fall victim, for example, through the spread of misinformation, identify fraud, and catfishing.”
Humans are experts at processing real faces, automatically assessing a face in as little as 100 milliseconds. However, AI-generated faces are highly realistic and are becoming more trustworthy with newer, more sophisticated technology creating fake images that can fool people into thinking they are genuine around a third of the time.
When 169 participants were asked to look at a collection of 96 faces (diverse across race, gender, and age) presented at random and indicate whether each face was real or AI-synthesised, their average accuracy was 58.4% - only slightly better than random guessing (similar to flipping a coin at 50%). Surprisingly, faces generated by the newer AI diffusion model (DM) were rated as less realistic than faces produced by an earlier AI model (GAN).
However, in a follow up experiment, a new set of participants were asked to rate the trustworthiness of 96 faces presented at random on a scale of one (very untrustworthy) to seven (very trustworthy).
Real faces were rated as the least trustworthy with an average trust rating of 4.03. Both types of AI-synthesised faces were rated as more trustworthy than real faces while faces produced by the diffusion model (DM) were more trustworthy than both the real and GAN faces. GAN faces received an average trust rating of 4.36, and diffusion-synthesized DM faces were the most trustworthy with an average rating of 4.70.
Researchers say it is puzzling that AI synthesised faces generated by the newer AI diffusion model (DM) were rated as less realistic than faces produced by an earlier model (GAN) - but DM faces were still rated the most trustworthy. Alexis McGuire said: “This finding presents a paradox and thus highlights the possibility that realism and trustworthiness judgements are driven by two different psychological mechanisms.”
She warned of how AI faces generated using the latest DM technology could contribute to an overall erosion of trust in society. “As AI-generated images become more sophisticated and more accessible, as a society, we are increasingly exposed to artificially-generated faces—often in nefarious and exploitative scenarios, such as political disinformation, financial and identity fraud, and catfishing. It is critical to understand the threat this democratisation of generative AI brings as well as developing strategies to mitigate potential harms to individuals, organisations, and democracies.”
The research in the Journal of Vision entitled “AI-Generated Faces are Becoming More Trustworthy” was funded by The Centre for Research and Evidence on Security Threats (CREST) and Security Lancaster... (MORE - missing details, no ads)
