Strategy and policy department

Robotics, artificial intelligence, the circular economy: the developments are moving fast. If a society wants to cope well in a changing world, it needs to be agile. Consider, for example, new citizen behaviour, new earning models for companies, and new government policies. The Strategy and Policy Department helps parties with these changes.

Broad perspective

Our clients are the European Commission, the Dutch Ministry of Economic Affairs, municipalities and provinces. Due to the diversity of backgrounds and clients, we look at economic, ecological, legal, cultural and political aspects in analyses. This is how we achieve solid results with an impact on society.

Strategic policy issues regarding innovation

We do not focus on the technical side of innovation, but look at strategic policy issues at the beginning and end of the innovation cycle. We do this from a close-knit department whose members are from a broad range of backgrounds. The department consists of 3 teams:

  • Environmental planning
    • Focuses on strengthening strategic decision-making regarding sustainability and spatial development.
    • Based on research into the interaction between knowledge, people and the environment.
    • Not focused on actual technical measures, but on their organization.
  • Innovation intelligence (iTeam)
    • Analyses the impact of innovation and technology on the economy and on society.
    • Analyses how we can optimally use innovation to achieve societal goals.
    • Is very active in EU context, such as in the digitisation of industry through Horizon2020 projects.
  • Digital society
    • Evaluates and mediates on digitalisation issues.
    • Works on a Privacy Roadweb, which investigates how organisations can develop with users and their privacy being paramount.

Policy on artificial intelligence (AI)

Artificial intelligence (AI) is an example of an impactful development that calls for changes in strategy and policy. The government is already using AI for social problems. Often successfully, but occasionally it goes wrong. It is then difficult to modify the system properly, either because AI is not transparent or expertise is lacking, for example algorithms that stigmatise and disadvantage groups of people.

The general public is often unaware when government deploys AI systems, and which decisions are made based on the resulting data. Transparency and explicability is lacking, and this affects trust in AI. Because citizens are not actively enough involved in AI developments, their interests are not adequately monitored. At the same time, decisions made using AI are increasingly influencing everyday life. This needs to be addressed very soon. In our view, the solution lies mainly in developing transparent and human-centred AI systems, and also in better monitoring.

Inclusive AI systems

What we envision are inclusive AI systems that take the interests of all stakeholders into account. We want to contribute to improvements by experimenting with AI living labs that put transparency and people at the centre. These living labs consist of mixed communities of data researchers, data engineers, policy makers, government officials and the general public. These groups collaborate on the development of AI solutions within the public sector.

Want to know more about our vision for AI solutions in the public sector? Read about it white paper Looking for the Human in AI (pdf) (pdf) or listen to the podcast.

Experimenting with policy in the Policy lab

AI developments also offer new opportunities for policy makers. They are able to gain new insights and respond better to social developments. But how should policy in that area be formulated? Strategy and Policy have developed a methodology for experimenting with this new way of policy-making: the Policy Lab.

The Policy lab is a methodology for conducting controlled experiments for formulating data-driven policies using new data sources and technologies. Policy makers experiment with new policies in a safe environment and then scale up their successes.

3 phases

The Policy lab has 3 phases:

  1. exploring new data sources and technologies and their impact on policy
  2. jointly setting up experiments and involving various stakeholders
  3. implementation, scaling up and monitoring of data-driven policies

This approach can be applied to issues by progressing through the three phases, or by exploring one of the phases in greater depth.

Rotterdam pilot on youth policy

A pilot experiment is currently underway with the Municipality of Rotterdam and the Dutch Ministry of Foreign Affairs (BZK). The ultimate goal is a better policy model regarding the development of social-emotional skills, the prevention of unemployment and the lack of education among young people.

The pilot project investigates which factors determine the social-emotional development of young people. To this end, data sources are linked, and a combination of statistical methods and machine learning explores which factors determine the social-emotional development of young people.

Expertise groups

Get inspired

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Orchestrating Innovation

Informatietype:
Article

Orchestrating Innovation facilitates collaboration on innovation between governments, knowledge institutions, and companies. Check out our learning programme, too.

Mission oriented research and innovation policy

Informatietype:
Article

Mission-oriented research and innovation policy to accelerate finding solutions to societal challenges and increase their impact.

SEL Method: Assessing the societal readiness of innovation

Informatietype:
Insight
6 November 2020
When is an innovation ready to be introduced? TNO is developing a new method for assessing whether society is ready for any particular innovation: the SEL method.