Addressing the Challenge of Misinformation with AI
Misinformation is a growing global concern, influencing public opinion, shaping campaign outcomes, and eroding trust in institutions. The rapid spread of misleading information, whether through social media, news headlines, or manipulated data, has significant consequences for society. In this blog, we explore real examples and impact of spreading misinformation and how it might be combatted through the use of artificial intelligence.
Real Consequences
An example of misinformation was during the Covid-19 pandemic when falsehoods about vaccines and lockdown policies fuelled distrust, contributing to the vaccine hesitancy and public unease. Likewise, a claim made during the Brexit referendum, which suggested that leaving the EU could potentially make £350 million per week available for the NHS, had a lasting impression on public perception despite being later discredited.
Similarly, in 2021, misinformation about an alleged fuel shortage led to UK-wide panic-buying, causing real disruptions despite no genuine supply issue. This incident highlighted how quickly misinformation can lead to tangible consequences.
The Role of Social Media
Social media platforms amplify misinformation through algorithms that prioritise engagement over accuracy.
Many users share content without verifying its credibility, allowing false narratives to spread rapidly. This has contributed to declining trust in news sources, with data pointing toward a 10-year trend of disengagement from online news.
Addressing the Issue
Combatting misinformation requires collaboration between governments, tech companies, media outlets and individuals. Social media platforms must improve content moderation, while education on digital literacy is crucial to fostering critical thinking.
At SAS Innovate in Orlando this May, our Butterfly Data team will present their winning 2024 SAS Hackathon AI solution that helps improve data transparency. Their project represents a step toward curbing misinformation and restoring public trust by using Natural Language Processing and Large Language Models to analyse news sources and assign a trustworthiness score.
While misinformation remains a persistent issue, proactive measures and technological advancements can help create a more informed society.
