Pandemic spawns 'infodemic' in scientific literature
New policies, technologies could help make sense of flood of information


Date:
September 11, 2020
Source:
Carnegie Mellon University
Summary:
The science community has responded to the COVID-19 pandemic
with such a flurry of research studies that it is hard for
anyone to digest them all, underscoring a long-standing need
to make scientific publication more accessible, transparent and
accountable, two artificial intelligence experts assert in a data
science journal.



FULL STORY ==========================================================================
The science community has responded to the COVID-19 pandemic with such a
flurry of research studies that it is hard for anyone to digest them all, underscoring a long-standing need to make scientific publication more accessible, transparent and accountable, two artificial intelligence
experts assert in a data science journal.


==========================================================================
The rush to publish results has resulted in missteps, say Ganesh Mani,
an investor, technology entrepreneur and adjunct faculty member in
Carnegie Mellon University's Institute for Software Research, and Tom
Hope, a post-doctoral researcher at the Allen Institute for AI. In an
opinion article in today's issue of the journal Patterns, they argue
that new policies and technologies are needed to ensure relevant,
reliable information is properly recognized.

Those potential solutions include ways to combine human expertise with
AI as one way to keep pace with a knowledge base that is expanding geometrically. AI might be used to summarize and collect research on a
topic, while humans serve to curate the findings, for instance.

"Given the ever-increasing research volume, it will be hard for humans
alone to keep pace," they write.

In the case of COVID-19 and other new diseases, "you have a tendency to
rush things because the clinicians are asking for guidance in treating
their patients," Mani said. Scientists certainly have responded -- by mid-August, more than 8,000 preprints of scientific papers related to
the novel coronavirus had been posted in online medical, biology and
chemistry archives. Even more papers had been posted on such topics
as quarantine-induced depression and the impact on climate change from decreased transportation emissions.

At the same time, the average time to perform peer review and publish
new articles has shrunk; in the case of virology, the average dropped
from 117 to 60 days.



==========================================================================
This surge of information is what the World Health Organization
calls an "infodemic" -- an overabundance of information, ranging from
accurate to demonstrably false. Not surprisingly, problems such as the hydroxycholoroquine controversy have erupted as research has been rushed
to publication and subsequently withdrawn.

"We're going to have that same conversation with vaccines," Mani
predicted.

"We're going to have a lot of debates." Problems in scientific
publication are nothing new, he said. As a grad student 30 years ago,
he proposed an electronic archive for scientific literature that would
better organize research and make it easier to find relevant information.

Many ideas continue to circulate about how to improve scientific review
and publication, but COVID-19 has exacerbated the situation.

Some of the speed bumps and guard rails that Mani and Hope propose are
new policies. For instance, scientists usually emphasize experiments and therapies that work; highlighting negative results, on the other hand,
is important for clinicians and discourages other scientists from going
down the same blind alleys. Identifying the best reviewers, sharing
review comments and linking papers to related papers, retraction sites
or legal rulings are among other ideas they explore.

Greater use of AI to digest and consolidate research is a major
focus. Previous attempts to use AI to do so have failed in part because of
the often figurative and sometimes ambiguous language used by humans, Mani noted. It may be necessary to write two versions of research papers -- one written in a way that draws the attention of people and another written
in a boring, uniform style that is more understandable to machines.

Mani said he and Hope have no illusions that their paper will settle the
debate about improving scientific literature, but hope that it will spur changes in time for the next global crisis.

"Putting such infrastructure in place will help society with the next
strategic surprise or grand challenge, which is likely to be equally,
if not more, knowledge intensive," they concluded.


========================================================================== Story Source: Materials provided by Carnegie_Mellon_University. Original written by Byron Spice. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Ganesh Mani, Tom Hope. Viral Science: Masks, Speed Bumps, and Guard
Rails. Patterns, 2020; 1 (6): 100101 DOI:
10.1016/j.patter.2020.100101 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/09/200911110806.htm

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