Realistic AI-generated images and voice recordings may be the newest threat to democracy, but they're part of a longstanding family of deceptions. The way to fight so-called deepfakes isn't to develop some rumor-busting form of AI or to train the public to spot fake images. A better tactic would be to encourage a few well-known critical thinking methods — refocusing our attention, reconsidering our sources, and questioning ourselves.
Some of those critical thinking tools fall under the category of “system 2” or slow thinking as described in the book Thinking, Fast and Slow. AI is good at fooling the fast thinking “system 1” — the mode that often jumps to conclusions.
We can start by refocusing attention on policies and performance rather than gossip and rumors. So what if former President Donald Trump stumbled over a word and then blamed AI manipulation? So what if President Joe Biden forgot a date? Neither incident tells you anything about either man's policy record or priorities.
Obsessing over which images are real or fake may be a waste of the time and energy. Research suggests that we're terrible at spotting fakes.
“We are very good at picking up on the wrong things,” said computational neuroscientist Tijl Grootswagers of the University of Western Sydney. People tend to look for flaws when trying to spot fakes, but it's the real images that are most likely to have flaws.
People may unconsciously be more trusting of deepfake images because they're more perfect than real ones, he said. Humans tend to like and trust faces that are less quirky, and more symmetrical, so AI-generated images can often look more attractive and trustworthy than the real thing.
Asking voters to simply do more research when confronted with social media images or claims isn't enough. Social scientists recently made the alarming finding that people were more likely to believe made-up news stories after doing some “research” using Google.
That wasn't evidence that research is bad for people, or for
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