Political scientist Markus Prior has long argued that inefficiency benefits democracy. In much of his work studying the effects of media on political knowledge and participation, Prior has found that an inefficient media environment – in which people have little choice over their entertainment options – is actually conducive to improving political knowledge.
In Efficient Choice, Inefficient Democracy?, Prior explains: “Yet while a sizable segment of the population watches television primarily to be entertained, and not to obtain political information, this does not necessarily imply that this segment is not also exposed to news. When only broadcast television is available, the audience is captive and, to a certain extent, watches whatever is offered on the few television channels. Audience research has confirmed a two-stage model according to which people first decide to watch television and then pick the available program they like best.”
That is, when few media choices are available, people tend to tune in for entertainment purposes. If news is the only thing that’s on, they’ll watch that over turning the TV off.
In a highly efficient media environment, however, people can navigate directly to their program of choice. Some people may choose to informational sources for entertainment, but the majority of people will be able to avoid exposure to any news, seeing only the specific programming they are interested in. (I should mention here that much of Prior’s data is drawn from the U.S. context.)
As Prior further outlines in Post-Broadcast Democracy, an inefficient media environment therefore promotes what Prior calls “by-product learning”: people learn about current events whether they want to or not. Like the pop song you learn at the grocery store, inefficient environments lead to exposure to topics you wouldn’t explore yourself.
Interestingly, it seems that a similar effect may take place in the context of group problem solving.
In a problem-solving setting, efficiency can be considered as a measure of communication quality. In the most efficient setting, all members of a group would share the exact same knowledge; in an inefficient setting group members wouldn’t communicate at all.
Now imagine this group is confronted with a problem and works together to find the best solution they can.
As outlined by David Lazer and Allan Friedman, this context can be described as a trade off between exploration and exploitation: if someone in your group has a solution that seems pretty good, your group may want to exploit that solution in order to reap the benefits it provides. If everyone’s solution seems pretty mediocre, you may want to explore and look for additional options.
Since you have neither infinite time nor infinite resources, you can’t do both. You have to choose which option will ultimately result in the best solution.
The challenge here is that the globally optimal solution is hard to identify. In a bumpy solution landscape, a good solution may simply point to a local optimum, not to the best solution you can find.
This raises the question: is it better have an efficient network where members of a group can easily share and disperse information, or is better to have an inefficient network where information sharing is hard and information dispersal is slow?
Interestingly, this is an open research question which has seen mixed results.
Intuition seems to indicate that efficient information sharing would be good – allowing a group to seamlessly coordinate. But, there’s also some indication that inefficiency is better – encouraging more exploration and therefore a more diverse set of possible solutions. The risk is that a group with an efficient communications network will actually converge on a local optimum – taking the first good option available, rather than taking the time to fully explore for the global optimum.