Policy-making 2.0

How can we anticipate future financial crisis? How can we make sense of terabytes of data owned by government? How can we extract knowledge from thousands of social media comments? How can we remake a decision making structure based on nineteenth-century representative models, and make it fit for the network society of the 21st century?

The environment in which policy-makers work is becoming more challenging by the day. The world is increasingly unstable, complex and interconnected, as the financial crisis has shown, and the tools are inadequate. At the same time, many citizens reject collective action through traditional parties and look to take an increasingly personal and active role in policy decisions, mirroring their personalised, simple and relational experiences using web-based technologies and social media.

Policy-making 2.0 refers to a blend of emerging and fast developing technologies that enable better, more timely and more participated decision-making. These applications include:

  • Open and big data, 
  • Visual analytics, 
  • Modelling and simulation,
  • Collaborative governance and crowdsourcing, 
  • Serious gaming,
  • Opinion mining.

These technologies are being increasingly applied in the public governance context, with promising results.

The existing research and practice about Government 2.0 and Open Government focussed mainly on open data and collaborative public services. New models of open, networked governance take these conversations wider and make them richer. "Open" in this context does not mean passively open like a door, but actively open like a shop, seeking out people to come and join in. As Web 2.0 turned the web into a environment that was experienced socially, Policymaking 2.0 should turn government into a more social and participative experience.

This is a positive shift, in line with societal trends and pointing towards more flexible and personalised approaches to government. However, mainstream research and practice on policy modeling remains focussed on linear models, based on the assumption that humans are perfectly rational, average, atomized. 
For us to make the case for policy making that fits this century rather than the last, we have to champion, advance and experiment with models that recognize human beings for what they are: complex, connected and diverse. More than that, we have to make the case in public for these new approaches, and give credit to those who are leading in the direction we want others to follow.

For more information have a look at the Research Roadmap.

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