Last week’s New Yorker contained this mind-opening piece by Atul Gawande, who argues that muddling through with small-bore trial projects is not a bad response to the crisis in U.S. health care.
“Where we crave sweeping transformation,” he writes, “all the current [Senate] bill offers is those pilot programs, a battery of small-scale experiments. The strategy seems hopelessly inadequate to solve a problem of this magnitude. And yet—here’s the interesting thing—history suggests otherwise.”
The history Gawande refers to here is the transformation of American agriculture in the last century. In 1900, he recounts, 40 cents of every dollar earned went to pay for food and farms were woefully unproductive–a serious brake on economic growth. Other industrializing societies had the same problem. The American solution was to enact no sweeping program or social revolution, but rather to bumble through with ad hoc programs–some to protect farmers from the effects of change and others to find and encourage the spread of techniques that improved efficiency. It had none of the ideological satisfaction or intellectual coherence of a Big Solution. But it worked. Today, food takes 8 cents from every dollar of family income, and our main food problem is obesity.
Gawande is suggesting, I think, that we all need to fight an impulse to think big troubles need proportionately big solutions. In agriculture, big, intellectually coherent, widely-applied and simple solutions– the collective agriculture of Communist regimes — were colossal failures that caused millions of deaths.
Might the same idea apply to other grand challenges, like climate change? Our instincts say no, because it is a global problem, that affects everyone. However, it doesn’t affect everyone equally. And it certainly isn’t caused equally by all people. Maybe it’s not so bad to have a patchwork of responses for a few decades, until we can sort out what works in which situations. The campaign for a coherent and simple global answer, after all, has been better at provoking total denial than it has at advancing long term answers.