Everything Is Obvious_ _Once You Know the Answer - Duncan J. Watts [92]
Market-based mechanisms like cap and trade do indeed seem to have more chance of working than centralized bureaucratic solutions. But market-based mechanisms are not the only way to exploit local knowledge, nor are they necessarily the best way. Critics of cap-and-trade policies, for example, point out that markets for carbon credits are likely to spawn all manner of complex derivatives—like the derivatives that brought the financial system to its knees in 2008—with consequences that may undermine the intent of the policy. A less easily gamed approach, they argue, would be to increase the cost of carbon simply by taxing it, thereby still offering incentives to businesses to reduce emissions and still giving them the flexibility to decide how best to reduce them, but without all the overhead and complexity of a market.
Another nonmarket approach to harnessing local knowledge that is increasingly popular among governments and foundations alike is the prize competition. Rather than allocating resources ahead of time to preselected recipients, prize competitions reverse the funding mechanism, allowing anyone to work on the problem, but only rewarding solutions that satisfy prespecified objectives. Prize competitions have attracted a lot of attention in recent years for the incredible amount of creativity they have managed to leverage out of relatively small prize pools. The funding agency DARPA, for example, was able to harness the collective creativity of dozens of university research labs to build self-driving robot vehicles by offering just a few million dollars in prize money—far less than it would have cost to fund the same amount of work with conventional research grants. Likewise, the $10 million Ansari X Prize elicited more than $100 million worth of research and development in pursuit of building a reusable spacecraft. And the video rental company Netflix got some of the world’s most talented computer scientists to help it improve its movie recommendation algorithms for just a $1 million prize.
Inspired by these examples—along with “open innovation” companies like Innocentive, which conducts hundreds of prize competitions in engineering, computer science, math, chemistry, life sciences, physical sciences, and business—governments are wondering if the same approach can be used to solve otherwise intractable policy problems. In the past year, for example, the Obama administration has generated shock waves throughout the education establishment by announcing its “Race to the Top”—effectively a prize competition among US states for public education resources allocated on the basis of plans that the states must submit, which are scored on a variety of dimensions, including student performance measurement, teacher accountability, and labor contract reforms. Much of the controversy around the Race to the Top takes issue with its emphasis on teacher quality as the primary determinant of student performance and on standardized testing as a way to measure it. These legitimate critiques notwithstanding, however, the Race to the Top remains an interesting policy experiment for the simple reason that, like cap and trade, it specifies the “solution” only at the highest level, while leaving the specifics up to the states themselves.27
DON’T “SOLVE”: BOOTSTRAP
Market-based solutions and prize competitions are both good ideas, but they’re not the only way that centralized bureaucracies can take advantage of local knowledge. A different approach altogether begins with the observation that in any troubled system, there are often instances of individuals and groups