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Razi, a Persian scientist, 10th century. Drawing: Louis Figuer's 'Vies des Savants Moyen Age,' 1867. Photo: Hulton/Getty

Ever since science became a formal discipline some five centuries ago, academic research — a fundamental driver of innovation — has, on and off, seemed broken: Scientists have cranked out too many incremental advances, fallen behind on the best research in their field and produced unreplicable work.

Driving the news: Now, some are again rethinking the process, hoping that artificial intelligence could be the long-sought highway to faster and more reliable scientific discovery.

Why it matters: The U.S. government spends billions on academic research each year — and companies toss in billions more. Yet science can appear to be treading water, turning out a similar scale of breakthroughs as when funding was lower and the number of researchers smaller.

One problem: A combination of factors — higher funding, faster computers and far more data — results in researchers spending much precious time sorting through a relentless avalanche of scholarship.

  • They can't read everything that is out there or attend every conference. It’s easy to miss a solution that’s already borne fruit in another field, or even an adjacent sub-discipline.
  • In order to connect the dots and come up with the best possible research path, they can only hope that they have read the rightarticles or heard the right public speaker.
  • "We need automatic techniques to see what’s missing," said Hannaneh Hajishirzi, an AI expert at the University of Washington.

Language is the core of the problem. Papers are ostensibly written for other scientists to read and understand, but the sheer volume of information means the scientists are in serious need of help.

The answer, some think, is simply to do a better job of sorting, cataloging and assessing papers as they are published.

  • We’ve reported on efforts to monitor social media activity to boost the best papers — but the next step is to engage with the text itself.
  • Several databases already link papers based on citations. Now, some are using natural language processing to extract actual meaning from research — a remarkably difficult task.

A first step is to automatically check facts and compare results against previous work.

  • Scite, a new website that catalogs academic papers, uses machine learning to understand the context in which research is cited. For each paper, Scite lists other work that mentions it neutrally, supports it or contradicts its findings.
  • Josh Nicholson, Scite’s co-founder, says he hopes the system incentivizes greater replication of original findings. When AI highlights corroborating or contradicting research, it should create feedback loops that encourage accuracy and reproducibility, he tells Axios.
  • Companies are also using language understanding in the laborious peer review process that precedes publication, reports Douglas Heaven for Nature.

Between the lines: This is the tip of the arrowhead.

  • Scientists imagine a future where research results are fed into a unified database that is constantly being updated with the latest work.
  • Rather than printing numbers in a table, results would go straight into this database — formatted for computers, not people, to read — and immediately be checked against other researchers’ findings.
"The model of referring to a text-based paper for the purpose of communicating experimental results will probably disappear."
— Robert Murphy, professor of computational biology, Carnegie Mellon

But, but, but: This automated utopia is a long way off. Natural language processing is still hard for computers, and a system trained to understand papers in a particular field might fail when reading another field’s work.

  • Academic journals are still kingmakers, and possessive researchers may not be willing to share their work freely.
  • But some fields’ early stabs at solving intractable research issues have convinced experts like CMU’s Murphy that they won’t exist in 10 years.

Go deeper: AI is helping automate science

Go deeper

1 hour ago - World

Sudanese government says it put down coup attempt

Prime Minister Abdullah Hamdok (L) and Sovereign Council Chief Gen. Abdel Fattah al-Burhan. Photo: Ashraf Shazly/AFP via Getty

The Sudanese government announced on Tuesday morning that its military and security services had foiled an attempted coup from within the country’s armed forces.

Why it matters: The apparent coup attempt comes with Sudan’s transitional government — in which power is shared between civilians and generals — facing crises on several fronts two years after dictator Omar al-Bashir was toppled in a popular uprising.

2 hours ago - Health

Johnson & Johnson says booster shot increases efficacy of COVID vaccine

Syringes and a vial of the Johnson and Johnson COVID-19 vaccine in French Polynesia on Sept. 8. Photo: Jerome Brouillet/AFP via Getty Images

Johnson & Johnson said in a press release Tuesday a global study showed that the protection offered by its coronavirus vaccine was strengthened by a booster shot.

Why it matters: While J&J has not formally applied for authorization to offer booster shots to the general public, it said it has shared the results of the study with the Food and Drug Administration and plans to share it with the World Health Organization and other health regulators.

3 hours ago - World

U.K. prosecutors charge third person in poisoning of former Russian spy

Emergency services members in biohazard encapsulated suits encasing the poisoning scene in a tent in Salisbury, England, in March 2018. Ben Stansall/AFP via Getty Images

U.K. prosecutors said they had enough evidence to charge Denis Sergeev, a member of the Russian military intelligence service, in the 2018 Salisbury nerve agent attack against a former Russian spy, according to AP.

Why it matters: Sergeev is the third person to face charges for the nerve agent attack against Sergei Skripal and his daughter, Yulia, both of whom survived.