Public policy based entirely on ideology is flawed. Our objective is often to ensure that our citizens have their needs met, but when we change our course dramatic and capriciously (as often happens after an election), we often fail our citizenry. Through the open government movement, and the open data movement, we have an opportunity to change some of this.
What if we decided on public policy based on what works, rather than our feelings about it? We could take 10 randomly selected public policies, all intended to address the same issue. Apply them as public policy to 10 randomly chosen similar jurisdictions (cities would probably have to collaborate to do this) and use the data collected from those jurisdictions to find out how effective the policies are. We would then discard all but the 3 best performing public policies, and randomly select 7 new policies to replace the ones lost, and rerun the experiment. We could tweak the three policies we’ve chosen (using some random variation on the various aspects of the policies).
Alternatively, once we have enough data collected from enough jurisdictions via the open data and open government movements, we could enter in all of this data into a computer, and run the policy algorithms on a simulation, rather than in the real world. At the very least, this computational approach could narrow down the field to policies which seem effective.
At the very least, the open data movement should allow us to do more effective research on public policy, but it would be interesting to see if any municipalities or governments would be open to an experiment of this kind.
Anonymous says:
You are exactly describing the Zemerge Project ‘a computing project of applying genetic algorithms to social simulations in order to help us derive optimal evidence based social decisions’.
http://zemerge.com/wiki/
I’m also working on a simple simulator that will eventually show this in action:
http://alphazemerge.com/
Cheers!
Tom
November 11, 2011 — 12:03 pm
Anonymous says:
I had the same idea last week, and found your post through Google.
Do you think it could be applied to national governments as well? The paradigm changes in that case, as it is more difficult to test policy variations.
Best,
Steven
—
http://twitter.com/steven2358
February 20, 2012 — 7:41 am
Anonymous says:
This is an immensely intriguing idea, and a rather brilliant one, but I would suggest that a problem arises when it comes to deciding which city/county has performed “best.” How do you weight different measures of societal wellbeing? How do you decide what those measures are in the first place, given the wide ideological differences existing between different groups? I think you might need some less centralized, more flexible method of determining governmental fitness, although I’m afraid I don’t have much in the way of suggestions. One possible method might be to monitor the flux of immigrants to a given city/county, as a proxy for whether people want to live there or not, but I highly doubt that that would be adequate as a fitness measure all on its own.
September 20, 2013 — 8:01 pm
David Wees says:
You can use other measures. For example, if your policy is intended to reduce the number of children who have a particular type of illness (lead poisoning, for example), then your policy could be applied (which remember, you do not know if this policy is effective) could be used in a number of different counties that had similar characteristics, and then you could measure the illness after a number of years to see which variant of the policy had the most effect.
September 20, 2013 — 9:22 pm