University of Kwazulu-Natal

From Ai Fact Checks To User Understanding Explaining Misinformation

Bonisiwe Shabane
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from ai fact checks to user understanding explaining misinformation

Falsehoods, fabrications, fake news – disinformation is nothing new. For centuries, people have taken deliberate action to mislead the public. In medieval Europe, Jewish communities were persecuted because people believed conspiracy theories suggesting that Jews spread the Black Death by poisoning wells. In 1937, Joseph Stalin doctored newspaper photographs to remove those who no longer aligned with him, altering the historical record to fit the political ambitions of the present. The advent of social media helped democratise access to information – giving (almost) anyone, (almost) anywhere, the ability to create and disseminate ideas, opinions, and make-up tutorials to millions of people all over the... Bad actors, or just misinformed ones, can now share whatever they want with whomever they want at an unprecedented scale.

Thanks to generative AI tools, it’s now even cheaper and easier to create misleading audio or visual content at scale. This new, more polluted, information environment has real-world impact. For our institutions (however imperfect they may be), a disordered information ecosystem results in everything from lower voter turnout, impeded effectiveness of emergency responses during natural disasters and mistrust in evidence-based health advice. Like any viral TikTok moment, trends in misinformation and disinformation will also evolve. New technologies create new opportunities for scale and impact; new platforms give access to new audiences. In the same way BBC Research & Development's Advisory team explored trends shaping the future of social media, we now look to the future of disinformation.

We want to know how misinformation and disinformation are changing – and what technologies drive that change. Most importantly, we want to understand public service media’s role in enabling a healthier information ecosystem beyond our journalistic output. R&D has already been developing new tools and standards for dealing with trust online. A founding member of the Coalition for Content Provenance and Authenticity (C2PA), we recently trialled content credentials with BBC Verify. We’ve also built deepfake detection tools to help journalists assess whether a video or a photo has been altered by AI. But it’s important to understand where things are going, not just where they are today.

Based on some preliminary expert interviews, a new picture is emerging: 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.

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