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Collective intelligence refers to the fact that a team of cooperating agents can solve problems more efficiently than when these agents work in isolation. Collective intelligence is used by insects living in colonies, by teams of humans, and even by collaborative robots. 

 

Collective intelligence has added value for everyone - citizens, consumers, media, public actors, industries, information management systems. In fact, modern societies increasingly rely on collective intelligence via peer review, crowdsourcing, open-source intelligence or collaborative filtering. And with the advent of Web 2.0 (or Participatory Web), collective intelligence is leveraged every single day: we use Twitter to explore others’ points of view, Youtube tutorials to repair appliances, Instagram to discover new trends, and Reddit and Wikipedia to learn about a multitude of facts. 

 

For the moment, search engines do not provide access to collective intelligence. They have been tailored for the Web 1.0 and strangely they still are organized around websites, not user-generated content. True, there is a growing trend to use collective intelligence. Google for example lists not only the best sites, but also the most relevant results in Wikipedia and in the media ('top stories'). Google also informs us about users’ related searches ('People also ask', 'People also search for'.) And obviously, the very idea of PageRank is based on the principle of collective intelligence.

 

Yet, collective intelligence is hard to grasp. It does not lie in a single post or website, but rather in the whole of these posts and websites, their diversity, their differences, their oppositions and their convergences. Ranking websites, or presenting the most relevant news articles cannot be the solution. 

 

The solution lies in aggregation. At BUNKA, what we do is that our algorithm does not give you the most relevant websites. We rather aggregate all websites, posts and reviews according to their semantic similarity (i.e. how much they talk about the same thing, they agree on the same issues), and we present you with a map of all these aggregations, with their main topics, their respective popularity, their convergences and their distance from one another. You can then explore, zoom in, zoom out, and access to collective intelligence.

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One domain where collective intelligence and aggregation might be especially useful is the fiability of information, and the diffusion of fake news. One obvious solution is to implement tools for assessing the content of a website or an article. Typical examples are debunking and fact-checking. But fact-checking and debunking have limits. They take time, and are difficult to automatize. Maybe more importantly, debunking and fact-checking adopt a confrontational approach which can backfire. 

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At BUNKA, our approach is different. Rather than evaluating the content of a post, we use collective intelligence to evaluate the context: who are the people who posted it? Who are the people who liked and shared it? Who disagrees with the post? It is through exploration that you get to be able to evaluate the quality of the information.

 

BUNKA doesn't tell people if they are right or wrong. It contextualizes what they are reading: Is it popular? Is it consensual? Is it fringe? Is it close to the alt-right? Is it endorsed by evidence-based websites? Is it shared by the anti-vaccine movement?

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Picturea dapted from Faris et al. (2017)

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Using collective intelligence - what others think - is actually nothing new. Humans, as a species, consume an enormous amount of culturally derived information and, lacking sufficient expertise, constantly need the social context to assess the epistemic quality of this information (source, status of the speaker, popularity of the information, etc.).

 

To take an example from everyday life, if one is looking for a good restaurant for lunch, it is very likely that one will choose to enter an establishment where there are customers rather than an empty restaurant (the busiest restaurant might reflect its popularity and, therefore, the quality of its service). This is what BUNKA does, but on a grander scale, with many more dimensions.

 

Faris, R., Roberts, H., Etling, B., Bourassa, N., Zuckerman, E., & Benkler, Y. (2017). Partisanship, propaganda, and disinformation: Online media and the 2016 US presidential election. Berkman Klein Center Research Publication, 6

 

Lorenz-Spreen, P., Lewandowsky, S., Sunstein, C. R., & Hertwig, R. (2020). How behavioural sciences can promote truth, autonomy and democratic discourse online. Nature human behaviour, 4(11), 1102-1109.

 

Sperber, D., Clément, F., Heintz, C., Mascaro, O., Mercier, H., Origgi, G., & Wilson, D. (2010). Epistemic vigilance. Mind & language, 25(4), 359-393.