Imagine the internet as a vast web of information with holes in it. These holes are called data voids – topics or terms for which little or no reliable content exists online. As researchers note, a data void happens when a search query “turns up little to no results,” often because the topic is obscure or brand-new^{1 2}. In plain terms, it’s like looking for a book on a brand-new subject in a library where no one has written that book yet. In that empty space, the first story that comes along (true or false) can dominate.

Why Data Voids Happen

Data voids often arise in everyday situations. For example, breaking news can create an instant void. When an unexpected event occurs – say, a shooting in a small town – people suddenly start searching for information. At first there may be no news articles or reports on that town. As one study found, when people searched for Sutherland Springs, Texas after a 2017 shooting, Google had no relevant news and instead showed irrelevant data (like real-estate listings)². In that gap, various groups poured in content: some honest reporters and many others (including conspiracists) raced to fill the void.

• Brand-new or obscure terms: If someone invents a new word or name (like a made-up hashtag or a little-known figure), search engines have nothing on it. Bad actors can then saturate that term with their own content. As one analysis noted, Russian media even invented a fictitious pilot, “Jepp Hansen,” killed in Ukraine. Because his name had no footprint online, the false story took root quickly³.
• Niche or outdated topics: When a topic falls out of the news or is very niche (for instance, an old political term or a local event from decades ago), new quality information may dry up. Search engines may return old or sparse content, leaving room for someone to slip in a false update.
• Under-covered languages or communities: In languages or regions with little reliable media, even serious topics can be data voids. One report found that AI chatbots struggle most in languages with sparse credible content, because propaganda sites easily dominate the search results in those cases³.

How the Void Is Filled – and Why It’s Dangerous

In a data void, any content that appears first can look authoritative. Malicious actors know this and exploit voids to spread misinformation. They might create blog posts, social media content, or videos stuffed with eye-catching keywords so they rank high in search or recommendations. For example, in the immediate aftermath of the Texas shooting, far-right activists quickly posted videos and tweets claiming the attacker was from “Antifa.” With no other information around yet, search results and social feeds briefly reflected this false narrative². As one researcher put it, when there’s a “spike in search queries,” adversaries “jump on that news story” to shape public perception².

This problem isn’t just about extremist groups. Anyone with an agenda – political operatives, conspiracy promoters, or even marketers – can game data voids. They may coin a catchy term (like a slogan or product name), then flood the web with content using that term. When the term finally hits the mainstream, the top search results are already full of biased or false info. Data voids effectively become echo chambers or rabbit holes. As the Data & Society report warns, manipulators exploit these gaps to “expose people to problematic content” including outright falsehoods¹.

AI and Data Voids: The Reliability Risk

These voids matter even more now that AI chatbots and search tools draw on web content. Generative AI systems (like chatbots) learn from the information that exists online. If the only content on a topic is misleading or false, the AI will absorb those errors. In fact, recent audits show many chatbots “absorb and amplify” falsehoods from shady sources³. Unlike a public post on social media, a chatbot’s answer doesn’t have a visible source to flag or debate. As one security analysis explains, misinformation in AI outputs is “essentially untraceable” – there’s no “post” to review, it just appears as a private chat answer³.

For well-covered events (like major world news), chatbots often give correct, well-sourced answers. But in those low-visibility data voids, they can confidently repeat rumors as facts. Take the “Jepp Hansen” example: after the false story circulated, several AI assistants later answered questions about it by repeating the lie as truth³. One report noted that multiple leading chatbots were “infected by this false information and repeated it as fact”³. In other words, because no reliable information about Jepp Hansen existed, the AI had no choice but to learn the wrong answer from the internet.

This is part of a broader trend: propagandists actually aim to train AIs by seeding data voids. As one regime propagandist bluntly stated, if they flood online spaces with their spin, they can “change worldwide AI” by shaping what these models learn³. The result is that even everyday professionals might someday ask an AI a question and get an answer based on a foreign disinformation campaign, without realizing it.

Staying Critical: How We Can Protect Ourselves

The takeaway for professionals is to use AI and search with a critical eye. Here are some practical tips:

• Don’t trust the first answer blindly. If an AI gives a surprising fact or a claimed expert viewpoint, double-check it against reputable news sites or official sources. Treat it like a colleague’s unverifiable claim: you’d ask for evidence or a reference.
• Cross-check unusual queries. For brand-new events or terms, look for well-known media coverage before believing a summary. If a chatbot’s answer is the only source you find, that’s a warning sign. Right now, search engines may eventually catch up with genuine news on breaking stories, but in the meantime, be skeptical of anything from a data void.
• Look for consensus. If multiple reputable outlets report the same thing, it’s likely real. If only obscure blogs or foreign “news” sites mention a claim (especially one that fits a particular agenda), be cautious. AI tends to pick up whatever is out there, even on fringe websites.
• Add good information when you can. Professionals and experts can help fill voids by publishing accurate content on emerging topics. Even a short article, blog post, or social update that explains a new term or event can drown out the bad actors later. As Data & Society suggests, platforms and creators should “fill (risky data voids) with quality content”¹.

Data voids are essentially invisible traps in our information ecosystem. By understanding them, we can avoid falling into the gaps. When using AI tools, remember that what’s not in the data matters as much as what is. Always question strange answers, verify against trusted sources, and contribute real knowledge where you can. In a world of fast-moving news and powerful AI, a bit of healthy skepticism will help us all stay on the right path.