Can you tell the difference between an AI-generated face and that of a real person?<\/p>\n
Major advances in artificial intelligence are powering hyper-realistic deepfake<\/a> images, video and audio, making it challenging to distinguish what is authentic and what is artificial.<\/p>\n These false depictions, as we have seen at schools<\/a> and in a first-of-its-kind case involving high-profile victims<\/a>, present major hazards.<\/p>\n Know the news with the 7NEWS app: Download today Arrow<\/a><\/p>\n \u201cDeepfake fraud is a real and growing problem,\u201d UNSW Sydney IDeA Lab director Dr James Dunn told 7NEWS.com.au.<\/p>\n \u201cAI-generated faces can make fake profiles, romance scams and misinformation campaigns appear more credible, and Interpol<\/a> reports that synthetic images are already being used in social-engineering schemes worldwide.\u201d<\/p>\n About one in four Australians say they have come across a deepfake scam in the past years, according to a study from the Commonwealth Bank<\/a>.<\/p>\n Amid the ongoing battle against deepfake fraud, a team of researchers led by the Australian National University (ANU) Emotions and Faces Lab say they have successfully trained people to identify what is real and what is fake when it comes to a person\u2019s visage.<\/p>\n \u201cTraining on visual artifacts, like looking for a sixth finger or odd earrings, has had limited success, partly because the AI is getting too good, and fraudsters may avoid using pictures with obvious flaws anyway,\u201d lead researcher Associate Professor Amy Dawel said.<\/p>\n People in the study were asked to consider six perceptual qualities rather than hunt for a \u201csingle giveaway\u201d sign. <\/p>\n Dunn explained each of them below:<\/p>\n Symmetry: \u201cAI-generated faces are often a little too symmetrical. Real faces usually have small natural asymmetries \u2014 a slightly uneven smile, one eyelid sitting lower than the other, or other subtle quirks. If a face appears almost perfectly balanced, it\u2019s worth taking a closer look.\u201d<\/p>\n Proportionality: \u201cThis relates to how facial features are sized and positioned. While AI can sometimes produce unusual proportions, it more commonly creates faces with very balanced, conventionally proportioned features. Natural human variation is often greater than what AI tends to generate.\u201d<\/p>\n Attractiveness: \u201cAI-generated faces frequently appear unusually attractive or polished. This is a subjective characteristic, but many AI faces have a broadly appealing, idealised look that feels almost \u2018too perfect\u2019.\u201d<\/p>\n Distinctiveness: \u201cConsider what would make the face memorable or recognisable in a crowd. AI-generated faces often gravitate towards average-looking features, making them seem more generic and less individually distinctive.\u201d<\/p>\n Expressiveness: \u201cAI faces often display relatively muted or restrained emotions. They may smile or frown, but the expressions can lack the subtle emotional cues and complexity that are common in genuine photographs.\u201d<\/p>\n Memorability: \u201cClosely related to distinctiveness, AI-generated faces are often surprisingly difficult to remember. Because they tend towards average features, they don\u2019t leave as strong a mental impression as many real faces.\u201d<\/p>\n Because AI-generated faces have become so convincing, Dunn said it is \u201coften the overall impression that matters rather than one obvious flaw\u201d when trying to pick them.
<\/p>\n \u201cOne important point we emphasised is that these characteristics are intentionally somewhat overlapping and subjective,\u201d he said.
<\/p>\n \u201cThere is rarely a single \u2018tell\u2019 that identifies an AI-generated image. Instead, the goal is to become familiar with the patterns AI tends to produce and develop an overall sense of when something feels slightly off.\u201d<\/p>\n Researchers say all participants in the study improved, and high performers could spot a fake almost every time.
<\/p>\n \u201cIt was amazing to see the dramatic improvement in people\u2019s ability to detect AI faces,\u201d Dawel said.<\/p>\n \u201cWe\u2019ve shown our training is effective for some of the most convincing fakes available.<\/p>\n \u201cWe are also working on how to optimise the training \u2013 making it shorter and ensuring the benefits last over time.\u2019\u2019
<\/p>\n The research was replicated by a team at the University of Victoria in Canada, which showed \u201cthe findings weren\u2019t a fluke\u201d.<\/p>\n The study comes amid a major shift in the landscape for artificial intelligence in Australia<\/a>.<\/p>\n On Wednesday, Prime Minister Anthony Albanese announced he would oversee an Office of AI within his department, as the government prepares to introduce new legal standards for AI and data centres.<\/p>\n The standards will set rules for large data centres, including an obligation to underwrite their own power supply, pay their full share of connection costs so energy bills are not impacted, reduce power when needed, and be water efficient.<\/p>\n The government has also made big promises to artists and creators, with the shift to ensure their copyright is not infringed upon by AI companies.\u00a0<\/p>\n \u201cThis world-leading framework is about Australia choosing to shape the future rather than letting the future of AI shape us,\u201d Albanese said.<\/p>\n \u201cThis framework is about protecting our national interests and ensuring certainty for growth, jobs and investment.\u201d<\/p>\n RMIT University distinguished professor Lisa Given, co-founder of the Centre for Human\u2013AI Information Environments, said Australians have a wide range of concerns around AI, from energy and water-guzzling data centres near residential neighbourhoods to potential job losses and copyright infringements.<\/p>\n \u201cAddressing such varied challenges, particularly when AI technologies are evolving at such a fast pace, warrants the coordinated approach this office will take,\u201d Given said.
<\/p>\n \u201cGiven the known risks posed by generative AI technologies like deepfake images that mislead customers or hallucinated content that misinforms chatbot users, Australians need government intervention to protect them from harm. <\/p>\n \u201cThe creation of this office marks a significant shift in the government\u2019s overall approach to governing AI, towards being more hands-on and proactive.\u201d<\/p>\n A big Meta miss<\/p>\n Change strategist and trends broadcaster Michael McQueen told Sunrise this week that Australians had embraced AI at a remarkable pace<\/a>, with many naming their chatbots and even assigning them genders.<\/p>\n \u201cIt\u2019s so familiar now in a way that\u2019s unthinkable two years ago,\u201d he said.<\/p>\n But some boundaries remain, as Meta found out when privacy concerns forced it to ditch an AI tool it had just launched this month.<\/p>\n Muse Image allowed users to generate images using public Instagram accounts, with the tech giant saying its \u201cintent was to provide a useful creative tool and to give people control \u2060over whether their public content could be referenced in this way\u201d.<\/p>\n \u201cWe\u2019ve heard the feedback that \u2060this feature missed the mark, so it\u2019s no longer available,\u201d Meta said.<\/p>\n SAG-AFTRA, the \u2060union representing actors and other media professionals, welcomed the about-face.
<\/p>\n \u201cWith the dangers of non-consensual digital \u200breplicas well \u2060known to all, a feature that encouraged that behaviour is unwise,\u201d a union spokesperson said.<\/p>\n The ANU Emotions and Faces Lab would like to hear from people interested in undertaking the AI face detection training<\/a> or participating in other AI face studies.<\/p>\n <\/p>\n Grandfather loses everything to romance scam<\/p>\n 1 min read<\/p>\n