AI could help tackle an 'infodemic' in scientific literature that's making it difficult to separate fact from misinformation, scientists claim.
Two American AI experts have blamed the coronavirus pandemic for an intense flurry of scientific studies in the rush to make information available.
By mid-August, more than 8,000 pre-prints of scientific papers containing the words Covid-19 or SARS-CoV-2 had been posted in online medical, biology and chemistry archives.
But this wealth of material is hard for anyone to digest and ranges from the reputable to the unreliable.
A greater use of AI to digest and consolidate research could therefore be the key to sieving fact from theory and ensure reliable information is properly recognised.
AI might be used to summarise and collect research on a topic, while humans serve to curate the findings, for instance.
Reputable scientific publications could also be made more accessible, by not hiding behind a paywall, and the authors of misinformation in papers generally could be forced to be legally accountable, they say.
By mid-August, more than 8,000 pre-prints 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. AI could help sort and fact check an explosion in information (and misinformation)
'The speed of science, especially while solving the recent pandemic puzzles, is causing concerns,' write Professor Ganesh Mani from Carnegie Mellon University and Dr Tom Hope at the Allen Institute for AI in the data science journal Patterns.
'Given the ever-increasing research volume, it will be hard for humans alone to keep pace.
'We believe – especially in light of the rapid increase in research production volume – new standards need to be created around metadata (for indexing and retrieval) and reviews processes made more robust and transparent.'
Even research papers less directly related to the virus, such as on quarantine-induced depression and the impact on climate change from decreased transportation emissions, have been abundant.
AI might be used to summarise and collect research on a topic, while humans serve to curate the findings
At the same time, the average time to perform peer review and publish new articles has shrunk in the rush for a breakthrough – such as in the hunt for a successful vaccine.
In the case of 14 titles in the field of virology, the average time to publication has dropped from 117 to 60 days, for example.
With Covid-19 and other new diseases, there is 'a tendency to rush things because the clinicians are asking for guidance in treating their patients', Professor Mani said.
The surge of information is what the World Health Organisation calls an infodemic – an overabundance of information, ranging from accurate to 'demonstrably false'.
The two also say politicians are adding to 'a maelstrom of misinformation' by touting 'speculative and unapproved treatments' – for example, the Donald Trump-backed medication hydroxycholoroquine.
Hydroxychloroquine is being studied to prevent and treat Covid‑19, but clinical trials have found it ineffective and that it may cause dangerous side effects.
A review of 29 scientific studies on hydroxycholoroquine showed the controversial anti-malarial drug does not save the lives of infected patients, French scientists reported last month.
'We're going to have that same conversation with vaccines,' Professor Mani predicted. 'We're going to have a lot of debates.'
Previous attempts to use AI to digest and