Navigating Misinformation

an interview with Matthew Facciani

Hi! Tell us a bit about your background and your work.

I'm a social scientist who studies how social factors influence how we evaluate information. For example, if someone belongs to a group, they may be biased to evaluate information about that group more positively. I also study how people interact with artificial intelligence. For example, I studied what factors make the answers from an AI chatbot more or less trustworthy.

How do you define misinformation? What are the key differences between misinformation and disinformation?

Misinformation is a broad, umbrella term that refers to any false or misleading information regardless of intent. Disinformation is also false or misleading information, but there is an intention to deceive others.

Can you explain how cognitive biases might make us more susceptible to believing and spreading misinformation?

When we strongly identify with a group, and that identity boosts our self-esteem, we are motivated to interpret information in ways that support and protect that group. For example, as passionate fans of a sports team, we may perceive referee decisions as unfairly biased against our team. This same bias applies to other identities, such as political affiliations. Ideally, having a diverse range of identities can help prevent us from becoming overly attached to defending any single one.

What role do algorithms play in shaping the way misinformation is spread online?

Algorithms can amplify misinformation by prioritizing engaging, sensational, and polarizing content to maximize user attention. This process can create echo chambers that reinforce biases and it allows false information to spread faster than corrections.

What strategies do you recommend for verifying the accuracy of information found online?

If we see a claim online, it can spread very quickly and get many views, but we should verify that across several reputable media outlets. We should also be mindful of who is making this claim, and if the media outlet has any biases that can affect what type of content they produce or how they report on current events.

Are there any red flags or warning signs that indicate we may be encountering a deepfake (an AI-generated image or video)?

Deepfakes often show unnatural facial movements, mismatched lighting, blurry details, or distorted features like eyes, hands, or mouths. If something feels off, look for inconsistencies and use reverse image search or fact-checking tools to verify authenticity. Deepfake technology is constantly evolving so it is very challenging to keep up to date. We should be mindful of our own biases and consider why we may want to believe something is true before we verify it.

Can AI be used to help detect or combat misinformation?

AI can help spot if an image has been manipulated from its original source. It can also share fact-checks at scale, but humans should always be involved with these processes to make sure the AI is not making mistakes.

Have you come across any examples where the spread of misinformation was effectively countered or reduced? What lessons can we learn from those cases?

Yes, media literacy lessons have been shown to help people better identify false information online. While formal classes can teach critical evaluation skills, shorter interventions, like online games, can also be effective. For example, Bad News is a game designed to improve media literacy. Our team developed Gali Fakta, a media literacy game for an Indonesian audience, and found that players became better at recognizing false headlines.

What can individuals do to challenge misinformation when they see it in their social networks?

It depends on the type of misinformation. If a clearly false claim comes from an anonymous account with few followers, it may be best to ignore it, as it could be a fake account. Engaging with false content, even to dispute it, can boost its visibility in algorithms, potentially exposing more people to the misinformation. However, if a friend shares something inaccurate, a better approach is to reach out to them privately and kindly let them know the information is incorrect.

How do you foresee the battle against misinformation changing over the next few years, especially as technology advances?

AI will likely flood social media with noise, as fake accounts generate well-written but false information at scale. This could further erode trust and fuel cynicism toward institutions and even each other. As technology evolves, understanding the human element becomes even more critical. We must recognize how our biases shape what we want to believe and stay vigilant against misinformation.

Connect with Matthew Facciani

To learn more from Matthew Facciani, you can sign up for his Substack, visit his website, or follow him on Threads or Bluesky.

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Critikid is building a mock social media feed to give kids a chance to practice spotting misinformation, clickbait, and logical fallacies in a safe and controlled environment before they face the real thing. Learn more.

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