Covid 19 from pandemic to infodemic

As if worrying about fighting fake news was not enough, there is more and more information (from scientists) about better ways to deal with coronavirus. The phenomenon, dubbed "infodemic" by the World Health Organization, has made it very difficult for researchers (and not only) to fully assimilate rapidly evolving discoveries, making some current research obsolete even before being 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, Ganesh Mani of Carnegie Mellon University, an investor, technology entrepreneur and associate member at the Software Research Institute, and Tom Hope, a postdoctoral researcher at the Allen Institute for AI, issued a distance call.

"Given the ever-increasing volume of research, it will be difficult for them to keep up", they say in the article.

They cite in particular the information deluge of research on coronaviruses. By mid-August, more than 8.000 drafts of scientific papers related to Covid 19 had been published in online medical, biological and chem. . 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 cannot find a complete solution. Mani and Hope propose new policies, such as thedistinguishing negative results from positive findings, which may be important for clinicians as they discourage scientists who have in 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 the big one." , which is likely to require just 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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