For years, people could largely trust, at least instinctively, that seeing was believing. Now, what\u2019s fake often looks real and what\u2019s real often looks fake.<\/p>\n
Within the first week of 2026, that has already become a conundrum many media experts say will be hard to move past, thanks to advances in artificial intelligence.<\/p>\n
President Donald Trump\u2019s Venezuela operation almost immediately spurred the spread of AI-generated images, old videos and altered photos across social media. On Wednesday, after an Immigration and Customs Enforcement officer fatally shot a woman in her car<\/a>, many online circulated a fake, most likely AI-edited image of the scene that appears to be based on real video. Others used AI in attempts to digitally remove the mask of the ICE officer who shot her.<\/p>\n The confusion around AI content comes as many social media platforms, which pay creators for engagement, have given users incentives to recycle old photos and videos to ramp up emotion around viral news moments. The amalgam of misinformation, experts say, is creating a heightened erosion of trust online \u2014 especially when it mixes with authentic evidence.<\/p>\n \u201cAs we start to worry about AI, it will likely, at least in the short term, undermine our trust default \u2014 that is, that we believe communication until we have some reason to disbelieve,\u201d said Jeff Hancock, founding director of the Stanford Social Media Lab. \u201cThat\u2019s going to be the big challenge, is that for a while people are really going to not trust things they see in digital spaces.\u201d<\/p>\n Though AI is the latest technology to spark concern about surging misinformation, similar trust breakdowns have cycled through history, from election misinformation in 2016 to the mass production of propaganda after the printing press was invented in the 1400s. Before AI, there was Photoshop, and before Photoshop, there were analog image manipulation techniques.<\/p>\n Fast-moving news events are where manipulated media have the biggest effect, because they fill in for the broad lack of information, Hancock said.<\/p>\n On Saturday, Trump shared a photo on his verified Truth Social account of the deposed Venezuelan leader Nicol\u00e1s Maduro blindfolded and handcuffed aboard a Navy assault ship. Shortly afterward, unverified images surrounding the capture \u2014 some of which were then turned into AI-generated videos<\/a> \u2014 began to flood other social media platforms.<\/p>\n As real celebrations<\/a> unfolded, X owner Elon Musk was among those sharing what appeared to be an AI-generated video<\/a> of Venezuelans thanking the U.S. for capturing Maduro.<\/p>\n AI-generated evidence has already made its way into courtrooms<\/a>. AI deepfakes<\/a> have <\/a>also fooled officials \u2014 late last year, a flood of AI-generated videos online portrayed Ukrainian soldiers apologizing to the Russian people<\/a> and surrendering to Russian forces en masse.<\/p>\n Hancock said that even as much of the misinformation online still comes through more traditional avenues, such as people misappropriating real media to paint false narratives, AI is rapidly dumping more fuel on the fire.<\/p>\n \u201cIn terms of just looking at an image or a video, it will essentially become impossible to detect if it\u2019s fake. I think that we\u2019re getting close to that point, if we\u2019re not already there,\u201d he said. \u201cThe old sort of AI literacy ideas of \u2018let\u2019s just look at the number of fingers\u2019 and things like that are likely to go away.\u201d<\/p>\n Renee Hobbs, a professor of communication studies at the University of Rhode Island, said the main struggle for researchers who study AI is that people face cognitive exhaustion as they try to navigate the sheer volume of real and synthetic content online. That makes it harder for them to sift through what\u2019s real and what\u2019s not.<\/p>\n The old sort of AI literacy ideas of \u2018let\u2019s just look at the number of fingers\u2019 and things like that are likely to go away<\/p>\n Jeff Hancock, founding director of the Stanford Social Media Lab<\/p>\n \u201cIf constant doubt and anxiety about what to trust is the norm, then actually, disengagement is a logical response. It\u2019s a coping mechanism,\u201d Hobbs said. \u201cAnd then when people stop caring about whether something\u2019s true or not, then the danger is not just deception, but actually it\u2019s worse than that. It\u2019s the whole collapse of even being motivated to seek truth.\u201d<\/p>\n She and other experts are working to figure out how to incorporate generative AI into media literacy education. The Organization for Economic Co-operation and Development, an intergovernmental body of democratic countries that collaborate to develop policy standards, is scheduled to release a global Media & Artificial Intelligence Literacy assessment<\/a> for 15-year-olds in 2029, for example.<\/p>\n Even some social media giants that have embraced generative AI appear wary of its infiltration into people\u2019s algorithms.<\/p>\n