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How to stop the spread of misinformation even before sharing

How to stop the spread of misinformation even before sharing


Crowdsourcing from a group of 1,128 users, the researchers were able to determine whether the articles were false in groups of as few as 10 people online, as well as professional fact-checkers. Complemented with algorithms, such a system could be trained to identify the speed and scale at which fake news spreads.

Furthermore, accessing these verification methods in an open manner, so that they are sufficiently easy to understand and transparent, can help alleviate bias and censorship claims. The initial attempt at this can be seen on Twitter Birdwatch, which the community uses to mark misinformation tweets; the system is new and imperfect, and it is clear which modes can be played (the problem with any verification system), but the first attempt is important.

Who determines the truth?

Each of these three interventions requires someone, somewhere, to decide what is true or what is of high quality. This “basic” truth is a critical piece of the puzzle, but it’s an increasingly difficult idea to deal with.

Controlling the narrative will always be contentious, and any system that attempts to resolve misinformation will be attacked in order to achieve partisan bias. In fact, extreme partisanship is directly linked to the sharing of fake news. It seems that social media is particularly effective when it comes to drawing partisan struggle issues around even more problems, though the issues are not inherently partisan.

But this is a new manifestation of a long-standing problem: How do we verify knowledge? And how can we be trustworthy? Who do we trust to establish the truth in society? Here we are entering an intricate epistemological territory, but one that has a precedent.

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Let’s take a look at some of the other services we use to check events regularly, the perfect but powerful systems we’ve relied on. Google and Wikipedia have created a reputation for helping people find accurate information effectively. In general, we trust them because they have verification and sourcing systems embedded in their design.

The frictionless design of the current social network has undermined the necessary condition for democratic functioning: shared truths.

Implicit in our three recommendations is trust and faith in the basic journalism process of verification. Journalism is far from perfect. The New York Times it sometimes goes wrong. As all media entities struggle with the selective interpretation of events, along with the editorial influence on the tone and tenor of the stories. But the inherent value of validated information is a critical infrastructure weakened by social media. Social media is not a news article, even though it has resembled our news feeds. Verification of new information is a key element of any democracy that works and we need to recreate the friction that the journalistic process previously provided.

There are new technologies on the horizon that will allow for decentralization of social networks and extreme encryption, in the face of any moderation. As these new tools reach a large scale, viral rumors will become even more difficult to dismantle, and the problem of misinformation and misinformation supply will only get worse. We should discuss how these tools can be designed to balance the flow of accurate information before losing the ability to do so.

That responsibility, at least in part, lies on our shoulders as a person. We need to be vigilant in identifying inaccuracies and finding well-known and well-known academic sources as well as journalists. Institutional skepticism is too toxic for our shared reality. We can redouble our efforts to find ways to find the truth carefully and compassionately. But platforms can and should help guide the design of our shared spaces to verifiable events.

Data visualizations by Tobias Rose-Stockwell


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