Ai Powered Fact Checking Combating Digital Misinformation

Bonisiwe Shabane

-Nov 30, 2025, 8:57 PM

ai powered fact checking combating digital misinformation

Despite being used to create deepfakes, AI can also be used to combat misinformation and disinformation. Image: Gilles Lambert/Unsplash The proliferation of artificial intelligence (AI) in the digital age has ushered in both remarkable innovations and unique challenges, particularly in the realm of information integrity. AI technologies, with their capability to generate convincing fake texts, images, audio and videos (often referred to as 'deepfakes'), present significant difficulties in distinguishing authentic content from synthetic creations. This capability lets wrongdoers automate and expand disinformation campaigns, greatly increasing their reach and impact. However, AI is not a villain in this story.

It also plays a crucial role in combating disinformation and misinformation. Advanced AI-driven systems can analyse patterns, language use and context to aid in content moderation, fact-checking and the detection of false information. Understanding the nuances between misinformation (unintentional spread of falsehoods) and disinformation (deliberate spread) – as is crucial for effective countermeasures – could also be facilitated by AI analysis of content. The proliferation of artificial intelligence (AI) has ushered in a new era of information access, yet it has also presented a formidable challenge: combating misinformation. Ironically, the very tools designed to combat fake news, AI-powered fact-checking systems, are sometimes contributing to the problem. While offering the potential for rapid and automated verification, these systems can inadvertently generate and disseminate inaccurate information, raising concerns about their overall efficacy and potential for misuse.

The core issue lies in the inherent limitations of current AI technology. Fact-checking is a nuanced process requiring critical thinking, contextual understanding, and the ability to discern subtle forms of manipulation, such as satire or misleading framing. AI systems, primarily relying on statistical pattern recognition and keyword analysis, often lack the sophisticated reasoning capabilities necessary to accurately assess complex claims. Consequently, they may misinterpret information, categorize satirical content as factual, or draw incorrect conclusions based on incomplete or biased data. Furthermore, the "black box" nature of some AI algorithms makes it difficult to understand how they arrive at their conclusions, hindering transparency and accountability. The problem is exacerbated by the sheer volume of information online.

The constant influx of news, social media posts, and other digital content creates an overwhelming demand for fact-checking, a demand that human fact-checkers struggle to meet. AI tools, promising automation and scalability, appear to be the perfect solution. However, the rush to deploy these systems without adequate oversight and rigorous testing has led to the inadvertent spread of misinformation. In some instances, AI systems trained on flawed or biased datasets have amplified existing prejudices and misconceptions. In others, malicious actors have exploited vulnerabilities in these systems to deliberately inject false narratives into the information ecosystem. The implications of AI-generated misinformation are far-reaching.

False information can erode public trust in institutions, fuel social division, and even incite violence. In the political arena, AI-powered disinformation campaigns can manipulate public opinion and influence election outcomes. In the health domain, inaccurate information about medical treatments or vaccines can have devastating consequences. As AI fact-checking systems become more prevalent, the potential for harm increases exponentially. Addressing this growing concern requires a multi-pronged approach. First, further research and development are crucial to enhance the accuracy and reliability of AI fact-checking tools.

This includes developing more sophisticated algorithms capable of understanding context, identifying satire, and detecting subtle forms of manipulation. Emphasis should be placed on transparency and explainability, allowing users to understand how AI systems arrive at their conclusions. Second, rigorous testing and evaluation are essential before deploying these systems in real-world scenarios. Independent audits and peer reviews can help identify potential biases and vulnerabilities. AI fact-checking is transforming how we detect and combat misinformation online. Using machine learning and natural language processing, AI can quickly analyze massive amounts of content.

This helps identify false claims faster than traditional methods. These systems are increasingly used by newsrooms, social media platforms, and researchers. AI tools provide real-time verification, helping limit the spread of misleading information. As digital content grows, AI fact-checking plays a vital role in preserving truth and trust. Read More: Reimagining Newsrooms: The Transformative Power of AI in Media and Journalism Misinformation is spreading faster than ever before, amplified by the reach of social media and digital platforms.

From politics to public health, false narratives influence public opinion and decision-making. This rising trend has made it harder to distinguish between reliable facts and fabricated stories. The volume of misleading content continues to overwhelm traditional fact-checking efforts. People are increasingly exposed to deceptive headlines and emotionally charged posts that prioritize clicks over truth. As a result, public trust in information sources has steadily declined, creating a dangerous echo chamber of false beliefs. 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). The proliferation of misinformation poses a significant threat to society, exacerbated by the capabilities of generative AI. This demo paper introduces Veracity, an open-source AI system designed to empower individuals to combat misinformation through transparent and accessible fact-checking. Veracity leverages the synergy between Large Language Models (LLMs) and web retrieval agents to analyze user-submitted claims and provide grounded veracity assessments with intuitive explanations. Key features include multilingual support, numerical scoring of claim veracity, and an interactive interface inspired by familiar messaging applications. This paper will showcase Veracity’s ability to not only detect misinformation but also explain its reasoning, fostering media literacy and promoting a more informed society.

Experts have rated the dissemination of misinformation and disinformation as the #1 risk the world faces Torkington (2024). This risk has only increased with the proliferation and advancement of generative AI Bowen et al. (2024); Pelrine et al. (2023b). Responses to misinformation have up to now been largely centred around platform moderation. As large-scale social media platforms actively eliminate their content moderation teams Horvath et al.

(2025), they pass to the user the personal and social responsibility to assess the reliability of claims and figure out how to make well-grounded decisions in a landscape of uncertain information. In the absence of strong platform-based approaches, solutions that support and empower individuals with tools to validate the information they encounter become essential in dampening the societally corrosive effects of misinformation. Misinformation is particularly dangerous when it influences public health and democratic processes, as seen in the spread of vaccine-related disinformation and politically motivated claims about censorship, both of which have been shown to exacerbate... With the rollback of content moderation efforts and increasing concerns over algorithmic bias on social media platforms, independent, reliable fact-checking tools are more necessary than ever. A promising solution in this area is an AI Steward that helps people fact-check and filter out manipulative and fake information. In fact, AI can outperform human fact-checkers in both accuracy Wei et al.

(2024); Zhou et al. (2024) and helpfulness Zhou et al. (2024). Although there is rapid progress in improving the accuracy of such systems Tian et al. (2024); Wei et al. (2024); Ram et al.

(2024), there is much less research on how to make a high-accuracy system into a helpful and trustworthy one that users can rely on Augenstein et al. (2024). Our AI-powered open-source solution, Veracity, deploys large language models (LLMs) working with web retrieval agents to provide any member of the public with an efficient and grounded analysis of how factual their input text... Moreover, through open-sourcing our platform, we hope to bring a test-bed for the research community to design effective fact-checking strategies. This article was originally published by The Fix and is republished here with permission. Learn about the latest from the world of European media by signing up for their newsletter.

Detecting disinformation is a key skill to have for journalists today. Fact-checking remains a human-led endeavor, but the massive volume of disinformation cannot be tackled by manual capacity alone. Here, AI-powered tools can help. University of Bergen’s Laurence Dierickx, a researcher on AI-driven journalism and fact-checking, says that “several projects are ongoing to provide more AI layers to help fact-checkers speed up a time-consuming process – an inherent... The Fix gathered a range of tools that will help journalists and fact-checkers identify and address disinformation. These tools are categorized into four main categories – tools for text, images, videos, and detecting bot activity.

Ai Powered Fact Checking Combating Digital Misinformation

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