We’re in the largest boom in the application and development of AI for science in history.

A world-first report from Australia’s science agency, CSIRO, has found that scientists are adopting artificial intelligence (AI) at an unprecedented rate.

Analysing the impact of AI on scientific discovery, ‘Artificial intelligence for science’ draws insight from millions of peer-reviewed scientific papers published over 63 years and identifies key issues ahead for the sector.

The report found that artificial intelligence is now implemented in 98 per cent of scientific fields, and by September 2022 approximately 5.7% of all peer-reviewed research worldwide was on the topic.

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

AI in science has grown significantly since 1960

The report uses a bibliometric analysis – statistical methods analysing trends in peer-reviewed research – to determine what percentage of the 333 research fields studied were publishing on artificial intelligence between 1960-2022.

Analysing all disciplines of natural science, physical science, social science and the arts and humanities, the report found that only 14% of fields were publishing on artificial intelligence in 1960. Just over a decade later in 1972 that proportion had reached more than half, and at present sits at 98%.

Graph of the number of research fields with artificial intelligence publishing, from 1960 to 2021
Graph of the number of research fields with artificial intelligence publishing, from 1960 to 2021. Adapted from the report “Artificial Intelligence for Science”. Credit: CSIRO

Growth in AI publishing has been greatest in the past 5-6 years, with the relative share of AI publishing rising 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, neuroscience and health professions.

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

“AI is also helping to deliver higher-impact, real-world solutions to Australia’s greatest challenges, like AI to help detect disease, predict bushfires and manage the enormous amount of data we are gathering about our universe.”

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

So, what does the future hold for artificial intelligence?

However, according to the report the pathway to artificial intelligence adoption and capability uplift is challenging; searchers are likely to experience both success and failure as they develop AI systems within their domains of expertise.

The report identifies six future development pathways for researchers and research organisations seeking to upgrade their AI capability for the future – harnessing the benefits while mitigating the associated risks.

  1. Software and hardware upgrades. Purpose-built processors designed for machine learning are speeding up computations, while quantum computing could lead to transformative leaps in computational power.
  2. The quest for better data. The era of “big data” may be transitioning into the era of better data. Recent breakthroughs have been achieved using smaller datasets that are well-curated, fit-for-purpose and provenance assured.
  3. Education, training and capability uplift. Between 2017-2020 the number of university courses teaching AI increased by 103%. Research organisations can take advantage of this to recruit AI talent and uplift capabilities of existing staff.
  4. Toward human centric artificial intelligence. In the vast majority of cases AI will be augmenting, not replacing, the human scientist. Issues of trust, transparency and reliability will be important for scientists and reviewers working on AI systems.
  5. Improving workforce diversity. Improving the gender, ethnic and cultural diversity of the AI research workforce will lead to better science outcomes.
  6. Ethical AI. Research organisations will be challenged to develop capabilities, technologies and cultures that deliver increasingly ethical AI.

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

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

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