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, Carnegie Mellon University's Ganesh Mani, investor, entrepreneur technologyand adjunct fellow at the Institute for Software Research and Tom Hope, a postdoctoral researcher at the Allen Institute for AI, issued a call to distance themselves.
“Δεδομένου του συνεχώς αυξανόμενου όγκου της έρευνας, θα είναι δύσκολο για τους people να συμβαδίζουν”, αναφέρουν στο άρθρο.
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. 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 increasingly attractive and perhaps necessary to combine human expertise with AI to start helping recorded results with leaps and bounds research. Too much information not only leads to impossible digestion of everything, but also to distinguishing between useful and suspect information and results. THE 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."
