Σαν να μην αρκούσε η ανησυχία για την καταπολέμηση των fake news, υπάρχουν ολοένα και περισσότερες πληροφορίες (Από επιστήμονες) για καλύτερους τρόπους αντιμετώπισης του κοροναϊού. Το φαινόμενο, που ονομάστηκε “infodemic” από τον Παγκόσμιο Οργανισμό Υγείας, έχει καταστήσει πολύ δύσκολο για τους researchers (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, 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 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 drafts of scientific papers related to Covid 19 had been published in online medical, biological and chemistry archives. There is not a lot of information about depression caused by quarantine. In the field of virology, the average time used to review from peers and the publication of new articles decreased on average from 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."
Φυσικά, η τεχνολογία από μόνη της δεν μπορεί να βρει μια πλήρη λύση. Ο Mani και ο Hope προτείνουν νέες πολιτικές, όπως την επισήμανση των αρνητικών αποτελεσμάτων από τα θετικά ευρήματα, κάτι το οποίο μπορεί να είναι σημαντικό για τους κλινικούς γιατρούς καθώς αποθαρρύνουν τους επιστήμονες που έχουν πρόσβαση σε περιορισμένη ή περιττή έρευνα. Άλλες ιδέες που παρουσιάζονται στο άρθρο συμπεριλαμβάνουν τον εντοπισμό των κορυφαίων κριτικών ποιότητας και τη connection των ερευνών με σχετική βιβλιογραφία, ιστότοπους recalls or legal decisions.
Artificial intelligence could help, but there is still a problem in understanding human language. Thus 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."
