As we have seen in the example of Haakenstad’s claim about chemotherapy, lateral-reading as a fact-checking technique can take us quite far. In this case, we can largely rely on fact-checking carried out by more reliable sources. Based on this, we can say that "the troll cracked" once it came into the public light.

In the next modules, we will take a closer look at the question of why we should have more trust in editorial media and scientific publications, but to conclude this module, we will briefly examine some cases where fact-checking individual claims may fall short.

Examples of more demanding cases

Imagine cases where you are considering sharing a story further. You have already concluded that it matters whether the claims made in the story are true or false. You have also assessed that you do not have enough knowledge about the issue to judge yourself whether the claims are correct. In such cases, you may want to exercise your lateral-reading skills to find more information, but this is not always easy.

Lack of verification: In some cases, you find that the claims cannot be confirmed or refuted because there are no clear references to other sources that justify the claims, or because you do not find assessments made by other, more competent fact-checkers. This is often the case with made-up stories, especially AI-generated posts, so-called "AI Slop", where bots flood the net with multiple variants of an engaging, but false, story. In such cases, you should be very cautious about sharing the story.

Selective presentation: In some cases, you find reliable sources that confirm the claims, but discover that the sender has a clear political agenda or financial interest in the matter. In such cases, you should also be critical and continue searching for presentations that are more balanced and provide a more comprehensive portrayal of the issue.

False balance: Even more challenging are cases where two sides of an issue are presented as equal, but it turns out that one side does not have the relevant professional expertise. In such cases, you can easily get the impression that there is an ongoing scientific debate on questions where there is, in reality, broad agreement within academic scholarship. In these cases, it is not enough to find comprehensive presentations of the issue in the media. The decisive factor is to find reliable sources that confirm what the consensus is among the experts.

Disinformation and false balance

The Wolfgang Wee episode with Haakenstad can be seen as an example of the phenomenon of false balance because it gives the impression that there is a real scientific debate about the treatment value of chemotherapy. The problem with false balance here is therefore not only that misinformation is spread from one side, but that it leaves the impression that the medical knowledge base is much weaker than it actually is.

More historically well-known examples of false balance are related to research on the health effects of tobacco smoking and the causes of global climate change. In these cases, it is well documented that commercial actors have been behind massive disinformation campaigns whose purpose was to sow doubt about the consensus among experts in order to weaken the political basis for regulation.

False balance is an attractive strategy here because it exploits central principles in public discourse about open and balanced presentations. The strategy also exploits scientific experts’ responsibility to contribute to public education, willingness to admit uncertainty, and desire for further research in their field.

Do you want to know more?

Om false balance:

Oreskes, N., Conway, E. M., & Conway, Erik M. (2010). Merchants of doubt : how a handful of scientists obscured the truth on issues from tobacco smoke to global warming. Bloomsbury Press.

Olsen, T., & Lysne, V. (2015). Meningsartikkel - Ta faget tilbake. In Norsk tidsskrift for ernæring (Vol. 13, Number 3, pp. 40–42). Universitetsforlaget. https://doi.org/10.18261/ntfe.13.3.14

Modules: Social media News media 🔒 Academic literature 🔒 Artificial intelligence 🔒