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Misinformation is not a new problem. In the 18th and 19th centuries, American newspapers were openly partisan and filled with rumors, personal attacks, and blatant fabrications. Benjamin Franklin published hoaxes and outright propaganda. The penny press of the 1830s built its business model on sensationalism (clickbait before there was anything to click). Well into the 20th century, publishers like William Randolph Hearst used newspapers to advance their own political agendas with little concern for accuracy. 

What eventually changed over the course of the 20th century was the professionalization of journalism. Reporters and editors developed a set of credibility-building practices: the rigid divide between the news and opinion sections, the practice of the objectivity norm, rules governing anonymous sourcing, editorial review, corrections policies, fact-checking, and so on. These practices were never perfect, but they earned mainstream news outlets a degree of public trust that, for a time, held. Indeed, CBS Evening News anchor Walter Cronkite was once known as 鈥渢he most trusted man in America.鈥� 

That trust has eroded dramatically over the past two decades, in part because of rising political polarization, but also due to a cascade of new technologies. The rise of the internet, followed by social media, followed by the smartphone, and now artificial intelligence (AI), has produced a series of compounding disruptions to our public sphere. Some media scholars initially cheered the way each of one of these new technologies democratized the creation and spread of information. But with such a vast and constant influx of news, information, and claims, it becomes harder to verify it all and more difficult for credible journalism to compete for attention. 

To many, AI is the most alarming of these disruptions, both in terms of scale and persuasiveness of deception. For example, using generative AI allowed one Russia-backed fake news operation to produce 2.4 times more articles per day while broadening the scope of issues it covered. AI tools can generate not just text but convincing deepfakes of audio and video. It can unleash armies of bots that look and sound (and even deliberately misspell) like real people.  

But AI would be nothing without the infrastructure that came before it. Social media platforms provide the many-to-many distribution system that allows false content to travel fast and far. And the algorithmic filtering built into TikTok, YouTube, Instagram, and the rest has fragmented audiences into narrow cultural and ideological niches, making it harder for people to encounter information that challenges what they already believe. A deepfake of a politician doing something dastardly is far more convincing if it matches your pre-existing beliefs about the person. Together, AI provides potent new content on a massive scale, but the platforms are the delivery system and their algorithms target us with precise content we鈥檙e least equipped to treat with skepticism. 

So, now we find ourselves in a time of disbelief. Nearly all of us have recently had to pause and ask: Is that real? Did that person actually say that? Skepticism is healthy, but we have an epidemic of distrust that is corrosive to our capacity as a society to hold reasoned discussions around an established set of facts. Journalism, big tech firms, higher education, and the scientific community, all of which play a role in informing our public sphere, have a lot of work to do to regain the public鈥檚 trust. 

In the meantime, there are things individuals can do to navigate this media landscape. The writer Michael Pollan once distilled an enormous body of nutritional science into seven words of advice: 鈥淓at food, not too much, mostly plants.鈥� In that spirit, here is my advice:  Read real news, not too much, mostly local.

Read real news.

Turn to outlets, like The New York Times, The Wall Street Journal, and The BBC, all staffed by professional journalists who operate under the credibility-building practices that distinguishes serious reporting. Not every person with a Substack newsletter or a podcast microphone is a journalist, and self-appointed experts are not the same as reporters who can be held accountable by editors, institutions, and professional peers.  

Not too much.

Political scientist Eitan Hersh coined a term for how many educated, middle-class Americans approach political news: 鈥減olitical hobbyism.鈥� They consume enormous quantities of national political coverage the way other people follow football, not to become better citizens but for the dopamine hit of outrage and the pleasure of rooting for a team. Research shows that overconsumption of political media might help you win a news quiz, but it also makes you more anxious, more antagonistically partisan, and less likely to do anything useful about the problems in your own community. 

Mostly local.

Between 2005 and 2024, more than 3,300 local newspapers closed in the United States, more than a third of all U.S. papers. Over 200 counties now have no local news source at all, and 55 million Americans have limited or no access to local journalism. When local news disappears, corruption goes unchecked, civic engagement declines, and communities lose the shared information they need to govern themselves. In Saratoga Springs, we鈥檙e lucky to have newspapers like The Times Union, The Daily Gazette, and The Post-Star.

Your local community is where your participation can make the biggest difference. Shifting a little bit of your attention away from national outrage cycles and towards what鈥檚 happening in your town or city will make you a more empowered citizen. 

That鈥檚 my prescription for a news diet. But the other key component, which is at the core of what a liberal arts college education is all about, is learning how to think critically and independently. In a media landscape shaped by social media attention merchants, algorithmic-filtering, and AI-generated misinformation, that skill has never been more necessary or valuable.  

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Andrew M. Lindner '03 is professor of sociology at 麻豆传媒网站 and co-author, with Stephen Barnard (Butler University), of 鈥溾�� (Second Edition).