AI in Journalism: Can we trust the news anymore?

Introduction

Think about it: How much news do you actually consume in a day?

If you’re like most people, you probably scroll through dozens of headlines before lunch—some from big media outlets, others from random blogs, social media posts, or even viral tweets.

We live in a world where information moves faster than ever. A tweet can become breaking news. A TikTok clip can spark a global debate. A random blog post can go viral and be treated as fact—even if it’s completely made up.

And here’s the scary part: We don’t even know what’s real anymore.

Back in the day, news was curated, fact-checked, and delivered by professionals. You had newspapers, TV anchors, and radio hosts who spent hours verifying stories before sharing them.

Now? Anyone with a smartphone can be a “journalist.”

• There are over 600 million blogs online.
• More than 1,000 news articles are published every single minute.
• And about 60% of people get their news from social media—where misinformation spreads six times faster than real news.

Facts! So… how did we get here? And more importantly, can AI help fix this mess, or will it make things worse?

Journalism then vs. now – from typewriters to AI

The Golden Age of Journalism: When news was slow (but reliable)

Try to imagine this: A smoky 1950s newsroom. Reporters in suspenders clacking away on typewriters. Editors yelling across the room. A single story could take days to research, write, and fact-check before hitting the presses. 

Back then:

• News was limited – Only a few major newspapers and broadcast stations existed, like The New York Times or BBC. These outlets had the power to shape the national narrative, but they also carried the responsibility of maintaining trust. 
• Fact-checking was strict – Teams of editors reviewed every detail. If a reporter got something wrong—like a quote or statistic—it could lead to corrections, public apologies, or even job loss. 
• Journalism was a respected profession – Becoming a journalist required training, internships, and often a journalism degree. There was a strong sense of mission: uncover the truth, inform the public, hold power accountable. 

Now?

• Anyone can publish “news” – All you need is a blog, a Twitter thread, or a YouTube channel. There’s no vetting, no editor, no training. That opens up access—but also the floodgates for misinformation. 
• Clickbait rules – “You won’t believe what happened next…” and “This one weird trick…” dominate headlines. Outlets are rewarded for engagement, not accuracy, so the line between reporting and entertainment keeps blurring. 
• AI-generated fake news is rising – Entire websites now generate articles using tools like ChatGPT or Jasper. These can produce believable-sounding health advice, political rumors, or celebrity news—often based on little or no truth. 

The Digital Chaos: How the Internet Changed Everything

• Print newspapers are dying – Since 2004, more than 2,000 local newspapers in the U.S. alone have shut down. Many towns now live in “news deserts” with no local coverage at all. 
• 60% of people under 35 get news from social media – Instead of tuning in to the evening news or reading a newspaper, younger audiences swipe through TikToks, Reels, and tweets. But these platforms reward speed and virality—not depth or accuracy. 
• AI-generated content is flooding the web – Some major news outlets now publish hundreds of AI-written articles each week. These are often short, data-driven stories with minimal human editing. It’s efficient—but can lead to errors or shallow coverage. 

So… is journalism dead?

Not exactly. But it’s evolving—and AI is playing a huge role in that change.

The AI Takeover – How Algorithms Are Changing the Game

Search engines decide what we see

• Google ranks the news – When you search for “Ukraine conflict,” the top results aren’t necessarily the most accurate—they’re what the algorithm thinks you’ll click on. This ranking system is based on SEO, engagement metrics, and sometimes recency, not necessarily journalistic quality or truth. 
• AI decides which headlines win – Many newsrooms now use AI to test which headlines get more clicks. A headline like “This Shocking Thing Happened in Ukraine” might beat “New Sanctions Announced by NATO”—even if the second one is more informative. This optimization for attention can distort the message. 
• Content is optimized, not verified – Algorithms care about engagement, not truth. An outrageous lie that gets 1M clicks can easily outperform a quiet truth that gets 100. And because engagement often means revenue, the system rewards sensationalism. 

Newsrooms are using AI too

• Automated articles – Outlets like Reuters and Bloomberg use AI to generate earnings reports or sports scores within seconds. These are typically structured, data-heavy stories that AI can easily compile from databases and spreadsheets. 
• Personalized news feeds – AI curates what you see. Two people Googling the same event might see totally different headlines—based on their interests, past clicks, or even political leanings. This creates filter bubbles and confirmation bias. 
• Deepfakes and misinformation – AI can create realistic fake videos of politicians saying things they never said. This isn’t just hypothetical—deepfakes have already influenced public opinion during elections and political crises. 

Can we trust anything anymore?

The rise of misinformation

• Fake news spreads faster than real news – A 2018 MIT study found that false news stories are 70% more likely to be retweeted than the truth. Why? Because lies are often more surprising, emotional, or sensational. 
• People trust influencers more than reporters – A 2023 survey showed that Gen Z trusts TikTok creators more than CNN. Not necessarily because they’re more credible—but because they feel “real” and relatable. This shift in trust has major implications for news consumption. 
• Confirmation bias is everywhere – We seek out stories that support what we already believe. Algorithms feed us more of the same, and over time, we stop questioning our sources. This echo chamber effect weakens critical thinking and encourages polarization. 

The role of AI in the future of news

So… will AI save journalism or destroy it?
Honestly, it depends entirely on how we decide to use it.

Let’s break it down:

What AI Can Actually Do Right (when used wisely)

Speed up research and reporting
AI is great at reading a lot of text, fast. Tools like ChatGPT or Claude can scan through reports, documents, press releases, or social media posts in seconds—and summarize what matters.
For journalists, this means they can get to the facts quicker, spot trends across thousands of documents, or instantly pull up background info while covering a breaking story. Think: less time digging, more time storytelling.

Analyze and spot patterns in large datasets
Investigative journalists often work with huge data sets—think leaked files, government budgets, or crime records. AI can help sort, clean, and find patterns in these numbers. For example, tools like Google’s Pinpoint or data journalism platforms can highlight connections or anomalies that would take humans hours (or days) to find.

Support content recommendations (without the doom scroll)
AI-powered systems (like what Netflix or Spotify use) can also suggest news articles based on what you like to read. If you regularly read climate coverage, it might show you new pieces on that topic. This can help keep readers engaged—but only if the system avoids pushing them into an echo chamber. The trick is making the algorithm smart and diverse.

Help with fact-checking and detecting fakes
There’s a whole area of AI being trained to spot misinformation. These tools can:

• Flag suspicious claims or inconsistencies in text
• Spot images or videos that have been manipulated
• Trace the origin of a quote or stat. Tools like Deepware, Hive AI, or even Meta’s deepfake detection efforts are aiming to give journalists a head start in the battle against fake content. 

Assist with accestysibili
AI can auto-generate subtitles, convert articles to audio, or translate content into multiple languages. That opens up access to news for people with disabilities or those reading in different regions. It’s a small thing that makes a huge difference.

Where it gets risky (and kind of scary)

Content overload, and the rise of junk
AI tools can now write hundreds of articles a day on any topic. Most of them? Mediocre at best. Some are riddled with errors. And when you flood the internet with this kind of mass-produced content, the valuable stuff gets buried. Readers might struggle to tell what’s human, what’s AI, and what’s just clickbait.

Replacing real journalists with machines
Some media companies are already experimenting with replacing junior writers or news desk roles with AI tools. Sure, it saves time and money—but it also removes the human judgment, ethical nuance, and creative voice that real journalism needs. AI can write a recap. But it can’t ask tough questions at a press conference, follow a lead, or understand the bigger context behind a story.

Loss of trust, and the “who do I believe?” problem
If AI tools are writing content, creating deepfakes, and even summarizing the news we see—how do we know what’s real? When readers start to doubt everything, including trustworthy sources, we end up with apathy and confusion. That’s the real danger: not fake news itself, but a public that stops caring whether the news is true.

Final thoughts: We need a new kind of literacy

In this age of AI-powered everything, media literacy isn’t optional.

We need to:

• Question sources – Who wrote this? Why? Are they credible? What’s their agenda? Every news story should be evaluated with these questions in mind. 
• Diversify your feed – Follow voices you disagree with. Read international sources. Step out of the algorithmic bubble and seek out different perspectives. 
• Slow down – Don’t share headlines before reading. Don’t assume everything that sounds “true” actually is. Take time to verify and reflect. 

AI isn’t the enemy. But neither is it the solution.
It’s a tool.
And like any tool, it can be used to build—or to break.

The future of journalism depends on how we choose to use it. 🙂

Interested to learn more about AI? Check out our previous blogs!