Fact Checking In The Age Of Generative Content Epublishing

Information disseminated online is increasingly created with the help of artificial intelligence, but such tools are far from perfect. Earlier in 2024, Google Chrome users reported the search engine's AI overview provided them with misleading information -- such as telling them to use glue to keep cheese from sliding off pizza and eat... This is known as an AI hallucination. In addition to text, generative AI tools can produce audio, video and imagery. This AI-generated content can be used in research outlines, social media posts, product descriptions, blog posts and email content -- and all of it should be scrutinized. When used incorrectly, AI can mislead the public -- as with the Google example -- compromise data privacy, create biased or discriminatory content and further erode public trust in new technologies.

While everyone should verify information they find on the internet, it's even more important for content creators who use AI content generators -- such as OpenAI's ChatGPT and Google's Gemini -- for assistance. Double-checking AI outputs against credible sources can prevent the spread of misinformation and disinformation. There are multiple steps involved in fact-checking AI-generated content, including the following: What business teams can do to stop the spread of misinformation In the age of AI, the truth is often hard to find. With ‘fake news’ and false information spreading faster than ever, it’s vital for writers on business teams to spot inaccuracies before they get published — especially when using AI tools.

Fortunately, there are practical steps that writers can take to ensure accuracy and stop the spread of misinformation. In this article, we’ll look at what fact-checking is, why you can’t skip fact-checking AI-generated content, along with how to spot — and correct — misinformation. We’ve also compiled a list of tips to help you improve your own fact-checking. Let’s start with a look at what fact-checking is all about! Typically, we think about fact-checking as it relates to journalism, politics, and academia. But as more brands establish themselves as industry experts and trusted sources of information, fact-checking becomes more important for the marketers and creatives that own content generation.

At the 2025 Milton Wolf Seminar, panel discussions tackled one of the urgent questions of the digital age: How can truth be verified in a world where its boundaries are increasingly blurred? Against a backdrop of widespread disinformation, increasing polarisation and declining public trust, the very notion of truth itself has become contested. In such an environment, fact-checking faces a dual challenge: not only is it harder to agree on what qualifies as truth, but disinformation now spreads with unprecedented speed and scale, outpacing traditional methods of... Amid these challenges, large language models (LLMs) have emerged as both a source of the problem and, paradoxically, a potential part of the solution. LLMs are advanced generative artificial intelligence (AI) systems trained on large amounts of internet data to generate human-like output. On the one hand, LLMs can produce convincing falsehoods rapidly and at scale, exacerbating the spread of disinformation.

On the other hand, its advanced capabilities might also be harnessed to detect, counter and even stop disinformation. This raises a critical question: Could generative AI, despite its risks, become an ally in the fight for truth? The 2025 Milton Wolf Seminar placed a strong emphasis on the dangers posed by AI, such as how it can produce disinformation and mislead individuals. This blog post explores an alternative angle. Instead of viewing AI only through the lens of risk, it asks whether this technology might also serve as part of the solution. In this blog post, I will first discuss the evolution of fact-checking and how it adapted to the changing information ecosystem.

Next, I will examine the challenges fact-checkers face today, especially the scale and speed of disinformation. I will then turn to LLMs, to consider whether this technology can help support the fact-checking process. Finally, I will reflect on how LLMs might strengthen the ongoing fight for truth. Disinformation itself is not new, but social media has profoundly transformed how quickly and widely it spreads. Platforms such as Facebook and X (formerly Twitter) have redefined how citizens consume information. While democratising access, they have also created unregulated and minimally controlled spaces where disinformation can rapidly proliferate (Wittenberg & Berinsky, 2020).

Unlike traditional journalism, where media professionals served as gatekeepers and information had to pass through institutional filters before reaching the public, social media platforms allow anyone to publish and share content instantly, without any... This has given rise to retroactive gatekeeping: a form of fact-checking that involves verifying the accuracy of claims after they have already begun circulating online (Singer, 2023). With the focus on the production of content (written, visual, audio and video) using AI tools and techniques undertaken in Chapters 6, 7 and 8, this chapter moves to the post-production process of strategic... This is a preview of subscription content, log in via an institution to check access. Tax calculation will be finalised at checkout Aljarah, A., Ibrahim, B., & López, M.

(2024). In AI, we do not trust! The nexus between awareness of falsity in AI-generated CSR ads and online brand engagement. Internet Research. https://doi.org/10.1108/INTR-12-2023-1156 Alkaissi, H., & McFarlane, S.

I. (2023). Artificial hallucinations in ChatGPT: Implications in scientific writing. Cureus, 15(2), e35179. https://doi.org/10.7759/cureus.35179 Relying on AI for content?

Make sure it’s spot on! Here’s how to fact-check your AI-generated content and avoid mistakes or misinformation. Imagine you’ve just used an artificial intelligence (AI) tool to generate a blog post for your business. At first glance, the draft seems well-written and ready to go—until you realize several problems. A key statistic is outdated, a historical date is wrong, and one source seems completely fabricated. What seemed like a time-saving solution could now put your credibility at risk if the AI output is not properly reviewed and edited.

This scenario is more common than you might think. In recent years, AI has revolutionized how we create and consume content. However, as its role in content creation grows, so does the need for fact-checking, as inaccurate or misleading information can easily slip in and potentially damage your brand’s reputation. In this blog, we’ll explore the rise of AI-generated content, why it is essential, and practical tips on ensuring that the information you share is accurate and reliable. AI-generated content is incredibly efficient. Tasks that used to take hours—like writing, editing, and revising—can now be done in minutes.

AI tools can write full articles, summarize reports, and even suggest ideas, all while mimicking human-like writing.

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