Developing policy informed by science and technology is now more complex than ever. Policymakers must address supply chains, climate change, inequality, technological breakthroughs, misinformation and more. Using artificial intelligence (AI) to mine the literature could put policymaking on a sounder footing.
Advanced big-data and natural-language-processing models enable decision makers to look beyond conventional indicators and expert discussions. Millions of scientific articles, patents and market reports can be readily analysed to identify megatrends or fading topics, and to provide predictive opportunities (see go.nature.com/31snkp5).
Machine learning can create maps of national competencies and centres of excellence of science and technology. It will find weak signals and potentially disruptive ‘wild-card’ effects, and can perform ‘gap analyses’ to guide legislation. Such applications could help steer more-proactive policymaking.
The COVID-19 pandemic needs coordination between teams with experience in applying AI (see, for example, J. Blumenstock Nature http://doi.org/d28w; 2020). The United Nations Educational, Scientific and Cultural Organization’s Global Futures Literacy Network (see go.nature.com/2nqqfpd) could help. Otherwise, the mismatch between science policy and reality will cost us all even more in the future.
Nature 583, 360 (2020)