Report assesses impact of artificial intelligence on science

Report assesses impact of artificial intelligence on science

A first global report by Australian science agency CSIRO has revealed that scientists are embracing artificial intelligence (AI) at an unprecedented rate.

Analyze the impact of AI on scientific discovery, “Artificial intelligence for science” draws on millions of peer-reviewed scientific papers published over 63 years and identifies key issues ahead for the sector.

The report revealed that artificial intelligence is now implemented in 98% of scientific fields and that in September 2022, around 5.7% of all peer-reviewed research worldwide was on the subject.

“AI is no longer just the domain of computer scientists or mathematicians; it is now a major driving force in all areas of science, something we experience every day at CSIRO, where digital technologies are accelerating the pace and scale of our research in areas from agriculture to energy through manufacturing and beyond,” says CSIRO Chief Scientist Professor Bronwyn Fox.

AI in science has developed considerably since 1960

The report uses bibliometric analysis — statistical methods analyzing trends in peer-reviewed research — to determine what percentage of the 333 research fields surveyed were publishing on artificial intelligence between 1960 and 2022.

Analyzing all disciplines in the natural sciences, physical sciences, social sciences, and arts and humanities, the report found that only 14% of fields published on artificial intelligence in 1960. Just over a decade later , in 1972, this proportion had reached more than half, and currently stands at 98%.

Graph of the number of research fields with publication in artificial intelligence, from 1960 to 2021
Graph of the number of research fields with publication in artificial intelligence, from 1960 to 2021. Adapted from the report “Artificial Intelligence for Science”. 1 credit

The growth of AI publishing has been the strongest over the last 5-6 years, with the relative share of AI publishing increasing from 2.9% of all publications in 2016 to 5.7% of all publications in 2022. Among the most prolific adopters are the fields of mathematics. , decision sciences, engineering, neurosciences and health professions.

“Human curiosity will always be at the heart of science, but these technologies, combined with a deep understanding of the field, are increasingly helping to open up new frontiers for knowledge discovery,” Fox says.

“AI is also helping to deliver real, higher-impact solutions to Australia’s biggest challenges, like AI to help detect disease, predict bushfires and manage the huge amount of data. that we collect about our universe.”

And there are no apparent signs that this current boom is slowing down.

So, what future for artificial intelligence?

However, according to the report, the path to adopting artificial intelligence and improving capabilities is difficult; researchers are likely to experience both successes and failures when developing AI systems in their areas of expertise.

The report identifies six future development paths for researchers and research organizations looking to improve their AI capabilities for the future – harnessing the benefits while mitigating the associated risks.

  1. Software and hardware updates. CPUs purpose-built for machine learning speed up calculations, while quantum computing could lead to transformative leaps in computing power.
  2. The quest for better data. The era of “big data” may be shifting to the era of best data. Recent breakthroughs have been made using smaller datasets that are well-organized, fit for purpose, and have assured provenance.
  3. Education, training and capacity building. Between 2017 and 2020, the number of university courses teaching AI increased by 103%. Research organizations can take advantage of this to recruit AI talent and improve the capabilities of existing staff.
  4. Towards a human-centered artificial intelligence. In the vast majority of cases, AI will augment, not replace, the human scientist. Issues of trust, transparency and reliability will be important for scientists and reviewers working on AI systems.
  5. Improve workforce diversity. Improving the gender, ethnic and cultural diversity of the AI ​​research workforce will lead to better scientific outcomes.
  6. Ethical AI. Research organizations will be challenged to develop capabilities, technologies and cultures that deliver increasingly ethical AI.

“To get the most out of this technology for Australia, we will need to tackle key issues. CSIRO has one of the largest teams of digital experts in the country, but these are not issues that can be solved by one organization,” says Fox.

“Developing trusted, responsible and ethical AI solutions will be increasingly important globally, and because we have moved quickly to develop deep expertise in the field, Australia has a unique opportunity to lead. in this domain.”

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