Share

Science, technology and innovation policy

OECD workshop on AI and the productivity of science

 

The OECD project on “AI and the Productivity of Science” addresses the critically important issue of the rate of scientific progress, whether this is stagnating, as recently argued by a number of scholars, and how AI could raise the pace of progress in science and discovery. This OECD workshop, a part of the project, brings together technical and policy experts to examine the evidence on a purported productivity decline in science as well as the ways that AI is currently used across different fields of science – from neuroscience to materials science - and across all stages in the scientific process. The workshop will advance the debate on what governments can do to maximise the positive impacts of AI on science, today and in the decades to come. Workshop presentations and expert discussions will become part of a comprehensive publication on the topic, to be released in early 2022. The event is being recorded. 

  ‌

 

DAY 1 | Friday 29 Oct.

12:30 – 18:45

 

DAY 2 | Tuesday 2 Nov.

12:00 – 18:35

DAY 3 | Wednesday 3 Nov.

12:30 – 18:20

DAY 4 | Thursday 4 Nov.

12:30 – 17:30

DAY 5 | Friday 5 Nov.

12:30 – 16:00

Topic 1

The productivity of science: is there a slowdown and if so why?

 
  Topic 2

The current uses of AI in science.

Topic 4

Systemic conditions affecting the productivity of science.

 
Topic 5

AI and the implications for science in the developing world.

 

Topic 6 (continued)

Policy priorities to increase the impact of AI on science. 

 

Topic 3

The current limits of AI in science.

 

Topic 6

Policy priorities to increase the impact of AI on science.

Topic 7

The future: what could AI achieve in science in the next 10 years?

 Please note that times vary from day to day. All sessions are scheduled according to Central European Time (CET) 

 

Might the productivity of science be stagnating?

Claims of a slowdown in science, with many alleged causes, are not new. However, such claims have been given new prominence by Bloom et al., (2020) and others. Various metrics have been cited: the number of researchers needed to maintain Moore’s Law has risen sharply; the number of researchers needed to maintain improvements in crop yields, and lower mortality due to cancer and heart disease, has grown; the real cost of developing a new drug doubles about every nine years; and the share of breakthrough patents may be falling.
The evidence is disputed. But, if true, any slowdown could lengthen timeframes for essential scientific progress. And governments, already under acute budgetary pressures, might have to spend more just to support existing rates of growth of useful science.

Can Artificial Intelligence (AI) help?
Spurred by advances in machine learning, and fed by vast realms of scientific data, AI is being adopted across most stages and fields of science. AI is helping to choose, design and plan experiments; improve measurement and observation (converting low-resolution images – for instance of mitochondria in cells - into high-resolution, low-noise images); discover meaningful relationships in colossal data sets (data flows in some science projects far exceed those of the entire Internet); generate hypotheses; learn scientific rules, such as the rules of chemistry to predict how to make medicines; identify the most suitable patients for clinical trials of drugs; create new capabilities in laboratory robots; summarize research; predict the replicability of research, and even suggest experts to review research proposals.

‌To examine all of these issues, the forthcoming OECD workshop on AI and the productivity of science (October 29th – November 5th), and later publication, will gather scientists, AI researchers, policy analysts and scholars of the economics of science. From multiple vantage points, in presentations and in essays, the experts will assess the evidence on progress in science and examine how AI is contributing to all stages of the scientific processes. The current limitations of AI in science will be considered in detail, along with the impacts of AI on science in the developing world, and the policy implications of current and possible future developments. The workshop will be livestreamed and is open to the public. An OECD publication on these topics will be launched in the second quarter of 2022.

 

Related Documents