Many people dislike and mistrust backroom deals and old boys networks in government. They prefer open and transparent governance. It makes for better institutions, and a better human condition. I am one of those people. Since you’re reading this, chances are you are, too.
Like many of those people, I watched the global Internet rise and saw an opportunity. I put a lot of work into exploring how Internet-enabled communication could make democracy better and smarter. Most of that work was practical. It consisted of designing and delivering open government projects, first in Italy (Kublai, Visioni Urbane, both links in Italian) and later in Europe (Edgeryders). Since 2006, I have kept in touch with my peers who, all over the world, were working on these topics. Well, I have news: this debate is now shifting. We are no longer talking about the things we talked about in 2009. If you care about democracy, this is both good and bad news. Either way, it’s big and exciting.
Back in the late 2000s, we thought the Internet would improve the way democracy worked by lowering the costs of coordination across citizens. This worked across the board. It made everything easier. Transparency? Just put the information on a website, make it findable by search engines. Participation? Online surveys are dirt cheap. Citizens-government collaboration? Deploy fora and wikis; take advantage of the Net’s ubiquity to attract to them the people with the relevant expertise. We had the theory; we had (some) practice. We were surfing the wave of the Internet’s unstoppable diffusion. When Barack Obama made President of the United States in 2008, we also had the first global leader who stood by these principles, in word and deed. We were winning.
We expected to continue winning. We had a major advantage: open government did not need a cultural shift to get implemented. Adoption of new practices was not a revolution: it was a retrofit. We would use words familiar to the old guard: transparency, accountability and participation. They were like talismans. Senior management would not always show enthusiasm, but they could hardly take position against those values. Once our projects were under way, then they caused cultural shifts. Public servants learned to work in an open, collaborative way. Later, they found it hard to go back to the old ways of information control and need-to-know. So, we concluded, this can only go one way: towards more Internet in government, more transparency, participation, collaboration. The debate reflected this, with works like Beth Noveck’s The Wiki Government (2009) and my own Wikicrazia (2010).
All that’s changed now.
What brought the change home was reading two recent books. One is Beth Noveck’s Smart Citizens, Smarter Governance. The other is Complexity and the Art of Public Policy, by David Colander and Roland Kupers. I consider these two books an advance on anything written before on the matter.
Beth is a beacon for us opengov types. She pioneered open governments practices in a project called Peer2Patents. Because of that, President Obama recruited her on his transition team first, and to the White House proper later. She has a ton of experience at all levels, from theory to project delivery to national policy making. And she has a message for us: Open Government is failing. Here’s the money quote:
Despite all the enthusiasm for and widespread recognition of the potential benefits of more open governance, the open government movement has had remarkably little effect on how we make public decisions, solve problems, and allocate public goods.
Why is that? The most important proximate cause is that government practices are encoded in law. Changing them is difficult, and does need a cultural shift so that lawmakers can pass reforms. The ultimate cause is what she calls professionalized government. The reasoning goes like this:
- Aligning information with decision making requires curation of information, hence expertise.
- The professions have long served as a proxy for expertise. Professionalized government is new in historical terms, but it has now set in.
- So, “going open is a call to exercise civic muscles that have atrophied”.
- When professions set in, they move to exclude non-members from what they consider their turf. Everybody important in government is by now a professional, and mistrusts the potential of common citizens to contribute. And everybody reinforces everybody else’s convictions in this sense. So, you get a lot of “meaningless lip service to the notion of engagement”, but little real sharing of power.
We now take professionalized government for granted, almost as if it were a law of nature. But it is not. Part of Beth’s book is a detailed account of how government became professionalized in the United States. At their onset, the US were governed by gentlemen farmers. Public service was guided by a corpus of practice-derived lore (called citizen’s literature) and learned on the job. But over time, more and more people were hired into the civil service. As this happened, a new class of government professionals grew in numbers and influence. It used part of that influence to secure its position, making bureaucracy more an more into a profession. Codes of conduct were drawn. Universities spawned law and political science departments, as the training and recruiting grounds of the new breed of bureaucrats. All this happened in sync with a society-wide movement towards measurement, standardization and administrative ordering.
Beth paints a rich, powerful picture of this movement in one of my favourite parts of the book. She then explains that new ways of channeling expertise to policy makers are illegal in the United States. Why? Because of a law drafted with a completely unrelated purpose, the Paperwork Reduction Act. And how did that come about? Lawmakers were trying to preserve the bureaucracy from interference and pressure from the regulated. To do this, it relegated non-government professionals in the role of interest representation. In other words, citizens are important not because of what they know, but because of who they speak for. A self-enforcing architecture of professionalized government had emerged from the state’s activities, without an architect .
Wait. Architecture with no architect? That’s complexity. Beth’s intellectual journey has led her to complex systems dynamics. She does not actually say this, but it’s clear enough. Her story has positive feedback loops, lock-in effects, emergence. She has had to learn to think in complex systems terms to navigate real-world policy making. I resonate with this, because the same thing happened to me. I taught myself network math as my main tool into complexity thinking. And I needed complexity thinking because I was doing policy, and it just would not damn work in any other way.
David Colander and Roland Kupers start from complex systems science. Their question is this: what would policy look like if it were designed with a complex systems perspective from the ground up?
They come up with fascinating answers. The “free market vs. state intervention” polarization would disappear. So would the dominance of economics, as economic policy becomes a part of social policy. The state would try to underpin beneficial social norms, so that people would want to do things that are good for them and others instead of needing to be regulated into them. Policy making agencies would be interdisciplinary. Experiments and reversibility would be built into all policies.
As they wrote, Colander and Kupers were not aware of Beth’s work and viceversa. Still, the two books converge on the same conclusion: modern policy making is a complex systems problem. Without complexity thinking, policy is bound to fail. I resonate with this conclusion, because I share it. I started to study complexity science in 2009. For four years now I have been in a deep dive into network science. I did this because I, too, was trying to do policy, and I was drawn to the explanatory power of the complexity paradigm. I take solace and pride in finding myself on the same path as smart people like Beth, Colander and Kupers.
But one thing is missing. Complexity thinking makes us better at understanding why policy fails. I am not yet convinced that it also makes us better at actually making policy. You see, complexity science has so far performed best in the natural sciences. Physics and biology aim to understand nature, not to change it. There is no policy there. Nature makes no mistakes.
So, understanding a social phenomenon in depth means, to some extent, respecting it. Try showing a complexity scientist a social problem, for example wealth inequality. She will show you the power-law behaviour of wealth distribution; explain it with success-breeds-success replicator dynamics; point out that this happens a lot in nature; and describe how difficult it is to steer a complex system away from its attractor. Complexity thinking is great at warning you against enacting ineffective, counterproductive policy. So far, it has not been as good at delivering stuff that you can actually do.
The authors of both books do come up with recommendations to policy makers. But they are not completely convincing.
Beth’s main solution is a sort of searchable database for experts. A policy maker in need of expertise could type “linked data” into a search box and connect with people who know a lot about linked data. This will work for well-defined problems, when the policy maker knows with certainty where to look for the solution. But most interesting policy problems are not well defined at all. Is air pollution in cities a technological problem? Then we should regulate the car industry to make cleaner cars. Is it an urban planning problem? Then we should change the zoning regulation to build workplaces near to homes to reduce commuting. Is it an labour organization issue? Should we encourage employers to ditch offices and give workers groupware so they can work from home? Wait, maybe it’s a lifestyle problems: just make bicycles popular. No one knows. It’s probably all of these, and others, and any move you make will feed back onto the other dimensions of the problem.
It gets worse: the expertise categories themselves are socially determined and in flux. Can you imagine a policy maker in 1996 looking for an expert in open data? Of course not, the concept was not around. Beth’s database can, today, list experts in open data only because someone repurposed exiting technologies, standards, licenses etc. to face some pressing problems. This worked so well that it received a label, which you can now put on your resumé and can be searched for in a database. Whatever the merits of Beth’s solution, I don’t see how you can use it to find expertise for these groundbreaking activities. But they are the ones that matter.
Colander and Kupers have their own set of solutions, as mentioned above. They are a clean break with the way government works today. It is unlikely they would just emerge. Anyone who tried to innovate government knows how damn hard it is to get any change through, however small. How is such a full redesign of the policy machinery supposed to happen? By fiat of some visionary leader? Possible, but remember: the current way of doing things did emerge. “Architecture with no architect”, remember? Both books offer sophisticated accounts of that emergence. For all my admiration for the work of these authors, I can’t help seeing an inconsistency here.
So, where is 21st policy making going? At the moment, I do not see any alternatives to embracing complexity. It delivers killer analysis, and once you see it you can’t unsee it. It also delivers advice which is actionable locally. For example, sometimes you can persuade the state to do something courageous and imaginative in some kind of sandbox, and hope that what happens in the sandbox gets imitated. For now, this will have to be enough. But that’s OK. The age of innocence is over: we now know there is no easy-and-fast fix. Maybe one day we will have system-wide solutions that are not utopian; if we ever do, chances are Beth Noveck, David Colander and Roland Kupers will be among the first to find them.
Photo credit: Cathy Davey on flickr.com
Really interesting, thanks.
My question to you is not directly related to complexity.
Beth’s professional database looks a lot like LinkedIn and their project for a skills’ graph.
It’s worth noting that the most complete collections of data about people interests and competencies is owned by (US) private corporations. Add to this data on social networks, search engine queries, preferences on all sort of topics. They build world-level “policies” on their own while the govs are just starting to build a data driven system.
How is going policy making to be mixed with a so powerful data capitalism?
Hello Piero, I may not be the most qualified person to give answers on Beth’s candidate solution. The book quotes extensively a project called Aristotle (abandoned). Based on that, it looks like it might start out as a silo; she mentions the needs of the Food and Drugs Administration to quickly reach WITHIN THEIR OWN RANKS for experts on certain molecules that need vetting. This would already improve FDA’s efficiency. Then, such a system could be opened up to non-employees and scaled up. But I may well be wrong in this.
Thank you 🙂