This is how to stop spreading misinformation before even sharing

Crowdsourcing from a group of 1,128 usersThe researchers were able to categorize small groups of up to 10 people online that could accurately determine whether the article was false or about a professional fact-checker. Complemented by algorithms, a system like this can be trained to detect fake news at the speed and scale at which it spreads.

Furthermore, these methods of verification can be open-sourced so that they are monitored and easily understood in a transparent way to help facilitate bias and censorship claims. Its initial efforts can be seen on Twitter Birdwatch, Which provides the community with flags for posting false information; The system is new and incomplete and there are definitely ways to make it playable (problem for any verification system) but this is an important first attempt

But who diagnoses the truth?

Each of these three interventions requires someone, a determination to decide which one is true or higher. This “baseline” is a critical part of the true puzzle, but it is a growing misconception to address it.

Controlling the narrative will always be controversial, and any system that seeks to correct the chaos will be attacked for biased bias. In fact, Extreme bias is directly linked to sharing fake news. Social media seems to be particularly effective in drawing the line of war on more and more issues, even if Things are not inherently biased.

But this is a new manifestation of an old problem. How do we verify knowledge? And how can we speed it up to be reliable? On whom do we rely in society to establish the truth? Here we are divided into disguised epistemological regions, but one example of this.


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Let’s take a look at other services we regularly use to verify information erf is incomplete but we have come to rely on robust systems. Google and Wikipedia have built a larger, built-in reputation to help people make accurate information more effective. We generally believe in them because they have verification and sourcing systems embedded in their designs.

The frictionless design of the current social web has eroded democratic effectiveness: the necessary prerequisite for shared truth.

Our three recommendations include a belief and belief in the process of early journalism of verification. Journalism is far from perfect. New York Times Sometimes it can be wrong. All media entities struggle with the editorial influence on the tone and tenor of the story, as well as the chosen interpretation of events. But the underlying value of verified information is the critical infrastructure that has been undermined by social media. Social posts are not news articles, even if they resemble our news feeds. Verifying new information is a key part of any functioning democracy, and we need to recreate the friction previously provided by the journalistic process.

There are new technologies on the horizon that enable both decentralization and end-to-end encryption of social media. Resistant to any restraint. As these new tools get in shape the viral rumors will become more difficult to cast and the problem of delivering errors and isolation will get worse. Before we lose our skills we should look at how these tools may be designed to balance the right information flow.

This responsibility falls on our shoulders at least as individuals. We must be vigilant about identifying inadequacies, and established, reputable sources of knowledge-both academic and journalistic. Excessive institutional skepticism is toxic to the reality of our partnership. We can redouble our efforts to find ways to dedicate the truth together, carefully and with compassion. Platforms, however, can and certainly help to lean the design of our shared spaces towards verifiable information.

Data-visualization by Tobias Rose-Stockwell

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