The ongoing digital transformation of the global economy has such deep and cross-cutting implications that the design and implementation of public policies to support science, technology and innovation (STI) must also be updated in order to reap benefits from the process, according to the Organization for Economic Co-operation and Development (OECD).

In its Science, Technology and Innovation Outlook 2018 report, the OECD states that government policies need to be modified to address data access issues, to become more agile, and to promote open science, data sharing and cooperation among innovators. It is also crucial to review competition and intellectual property policy frameworks as well as to support innovative entrepreneurship.

This Letter IEDI summarizes three chapters of the OECD report dealing with innovative STI policies. It is argued that new digital technologies, in particular Big Data and Artificial Intelligence (AI) technologies, bring policymakers the possibility of experimenting with new approaches to science, technology and innovation; however, on the other hand, they raise the challenge of anticipating the disruptive changes associated with innovations and of considering their implications for public policy in general.

In the first study, "Perspectives on innovation policies in the digital age", OECD researchers Caroline Paunov and Dominique Guellec argue that, as new technologies advance, the innovation process itself undergoes changes, transforming market structures and business dynamics with consequences on the distribution of gains among companies, individuals and regions, thus requiring the adaptation of government support to innovation.

According to the authors, the main characteristics of the current innovative processes and outcomes induced by digital transformation would be: lower production costs and fluidity of innovative products, data as the main input, "servitisation", faster innovation cycles and collaborative projects and actions.

The new digital context and features of innovation, in turn, require changes in the objectives and instruments of STI policies, which, according to Paunov and Guellec, should contemplate the following principles:

     • Develop data-access policies for innovation.

     • Have quick and agile policy responses.

     • Revisit instruments to support research and innovation.

     • Support the development and diffusion of multi-purpose technologies.

     • Promote open and collaborative innovation.

     • Enable competition and entrepreneurship.

     • Prepare individuals for digital transformation through education and training.

     • Set national innovation policies in view of global markets.

In addition, innovative entrepreneurship is another important element in the new forms of public support, as Carlo Menon argues in the OECD report chapter "Mixing experimentation and targeting: Innovative entrepreneurship policy in a digitised world".

The starting point is a critical examination of the debate on high-growth innovative entrepreneurship, seen as one of the driving forces behind the creation of innovation, employment and inclusion, which is why policymakers consider a fertile entrepreneurial ecosystem very important. However, being new is not enough to ensure these positive contributions: companies must also be fast-growing enterprises.

Thus, the effectiveness of non-targeted entrepreneurship policy has been questioned. In the author's view, better predicting startup ex ante success would enable governments to direct their support to those with the highest growth potential, thus shifting the balance between targeted and non-targeted (e.g. reducing entry and exit barriers) policy approaches.

Venture capital public policy becomes more effective, according to Menon, if these interventions target the "right" startups and entrepreneurs. Big Data and machine learning technologies may help policymakers in this task.

The formulation and implementation of effective STI policies in the face of the ongoing social and technological changes are precisely the topic of Piret Tõnorist’s study "New approaches in policy design and experimentation". In his view, tackling 21st century problems with old tools and methods would certainly be ineffective.

The new technologies profoundly change the way governments operate and interact with the objects of their policies and with their partners. Tõnorist defends the idea that governments need to understand the impacts of technology, as well as the changing expectations of citizens, companies and innovators, by analyzing their user experiences in order to experiment and innovate themselves.

Governments in developed economies are already using new policy tools; indeed, some examples identified by Tõrorist are: design thinking, systems thinking, regulatory sandboxes and real-time data analysis, among others. These tools are useful for analyzing the needs and motivations of researchers, innovators and lead users so as to apply a new technology solution based on user experience.

The full text is available in Portuguese.