Online misinformation is becoming harder to recognize as generative AI makes it easier to produce convincing content at scale. The source argues that this challenge could become especially serious around the 2024 presidential election, when political falsehoods, limited media literacy and rapidly generated material may reinforce one another.
Recognizing unreliable information takes practice
People who grew up with the internet may approach news with skepticism, and media literacy is being taught even to kindergarteners. But that does not mean everyone has learned how to assess what they encounter. The source says 46% of adults report that they were never taught how to judge news stories for bias and credibility.
That gap can make it difficult to spot content designed to look authoritative while serving another purpose. The article illustrates this with product review sites that publish large volumes of thin, generic evaluations. Some appear to be written without hands-on experience with the products, then direct readers to retailers through links that earn commissions.
More credible product reviews can offer observable signs of direct testing, such as photographs of the products together and images of people using them. Regularly refreshed material can also affect how trustworthy a site appears. These signals do not resolve every question, but they show why readers need to look beyond polished language and ask how a site knows what it claims.
Political misinformation has higher stakes
Inaccurate product advice can waste money and may contribute to products being discarded rather than repaired or returned. Political misinformation carries broader consequences because false claims can shape what people believe and how they act. The source points to a rise in misleading or fabricated news during the 2020 election and the COVID-19 news cycle.
When a false claim spreads through social networks, it can reach friends and family quickly, and the source says research has found measurable changes in behavior linked to misinformation. It also cites a House Select Committee report that described individuals involved in January 6th as being provoked by false information about the 2020 election, repeatedly reinforced by legacy and social media.
The article also describes cyberattacks and other activity attributed to foreign government-sponsored hackers, including theft, attacks on journalists, and ransomware and hacks targeting U.S. agencies. These examples show how online threats can involve both fabricated claims and direct attacks on people or institutions.
AI increases the volume and plausibility
Since the 2020 election, generative AI has advanced quickly, drawing major corporate investment and venture capital. The source describes systems that can generate music, audio advertisements, video and fluent written material. It also warns that detection methods cannot reliably distinguish human writing from AI output.
One example in the source makes the point: a paragraph about AI-generated journalism was largely written by GPT-4, and the author says it was difficult to find fault with its wording. A writer seeking to mislead could remove the passage about ethics and oversight, leaving a polished argument that sounds responsible while omitting its caution.
The concern is not simply that one article might be machine-written. AI could make it possible to produce far more content than people can read, including material tailored to many topics. Human oversight remains important for accuracy and ethical standards, but large-scale production can put pressure on the ability to review and verify what circulates.
Why the combination matters before an election
The source frames the risk as a convergence: many people have limited confidence in media, some struggle to identify false news, political actors may be willing to use deceptive tactics, and AI can increase the supply of plausible content. Taken together, these conditions could make it harder for readers to establish what is true before claims are shared further.
To respond, the article recommends learning media literacy and helping others do the same. It points readers to KQED as a resource. It also asks startup founders to consider how their knowledge of technology and AI might help address the flow of false information.
The larger lesson is practical: slow down when a claim seems consequential, consider the credibility of its source, and look for signs that the information is supported. Those habits cannot remove misinformation from the internet, but they can help readers make more deliberate decisions about what to trust and share.