Covid 19 from pandemic to infodemic

As if the concern about fighting fake news wasn't enough, there is more and more information (From scientists) about better ways to deal with it . The phenomenon, called "infodemic" by the World Health Organization, has made it very difficult for them (and not only) to fully assimilate rapidly evolving discoveries, rendering some current research obsolete even before it is evaluated by other scientists.

Research in recent months has been very demanding and researchers consider it their duty to publish results that may be useful to clinicians. But there are always conflicts due to the growing scientific literature.

In a opinion article in Patterns magazine, Carnegie Mellon University's Ganesh Mani, investor, entrepreneur and adjunct fellow at the Software Research Institute, and Tom Hope, a postdoctoral fellow at Allen for AI, they issued a distancing call.

"Given the ever-increasing volume of research, it will be difficult for people to keep up," the article said.

They cite in particular the information deluge of research on coronaviruses. By mid-August, more than 8.000 scientific drafts related to Covid 19 were published in online medical, biological and chemical archives. There is not a lot of information about depression caused by quarantine. In the field of virology, the average time used for peer review and publication of new articles decreased from an average of 117 days at the beginning to 60 days.

So it seems more and more attractive and perhaps necessary to combine human know-how with AI to begin to help record results with research that leaps and bounds. Too much information not only leads to the impossible digestion of all, but also to the distinction between useful and suspicious information and results. Artificial intelligence could help evaluate research and classify it appropriately.

"We will have the same discussion with vaccines," said Mani. "We will have a lot of discussions."

Of course, technology alone can not find a complete solution. Mani and Hope are proposing new policies, such as highlighting the negative effects of positive findings, which may be important for clinicians as they discourage scientists from accessing limited or unnecessary research. Other ideas presented in the article include identifying top quality reviews and linking research to relevant literature, recall sites, or legal decisions.

Artificial intelligence could help, but there is still a problem in understanding human language. So the authors state that it may be necessary for researchers to write two editions of research papers, one for humans and one for AI.

"Using such infrastructure will help society in the next big surprise or challenge, which is likely to need as much, if not more, knowledge."

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Written by giorgos

George still wonders what he's doing here ...

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