Justin Gregg compares diagnostic inference, whereby animals learn to associate a cause with an effect, to causal understanding, whereby humans reason as to why something happens:
If causal understanding is such an obvious advantage over other ways of thinking, why did it take our species 200,000 years before we began using this ability to begin the spread of modern civilization? The answer is that sometimes, being a why specialist leads our species toward unexpected ludicrousness that is so bad for our species (evolutionarily speaking) that it makes you wonder if we’d actually be better off relying solely on learned associations. Justin Gregg, If Nietzsche Were a Narwhal, September 2022
I will agree that, when policymakers attempt to understand why something is happening by looking for 'root causes', this can be a waste of time or an excuse for inaction. There are too many causes of social problems, and they are too various and too variable to be identified - at least by conventional public- or private-sector organisations, with their fixed structures and limited remits. Crime, poverty, war: these have many causes that vary markedly over time and space. It is politically acceptable for governments either address the symptoms of these problems, or to spuriously reduce the number of causes to one and target that: so crime is often attributed to poverty, and climate change to greenhouse gas emissions. But these problems may have no single, fixed cause, and we need to offer incentives that encourage people continuously to explore the many, varying causes of our social and environmental problems. Often, there are suggestive associations between cause and effect, but insufficient evidence for governments to use taxpayer funds to act on those associations. So, unless effect can unambiguously attributed to causes upon which we can act, our problems remain.
What I suggest we do instead is reward the outcomes we want to achieve, regardless of how they are achieved. Provide incentives for people to investigate some or all possible causes or simply to learn by association - as in the animal kingdom - and react accordingly, even without the evidence required to draft a policy. And to bear in mind that doing nothing, in some rare circumstances, might be the optimal approach.
Social Policy Bonds would encourage this type of behaviour, rooted in a humility that recognises that we cannot always identify the causes of our problems, but that we might not need to in order to solve them. How would they do so? They would reward all approaches, however indirect or nebulous, that help solve a targeted problem. Evidence in favour of an approach could be anecdotal, associative or putatively causal: governments cannot act on all such evidence, but holders of Social Policy Bonds can; their sole criterion for backing an approach is whether it promises to be a cost effective way of achieving the goal they target.
What do I mean when I say that doing nothing might be the optimal approach? Take climate change: the evidence that it's actually happening convinces me (currently). The evidence that we can or need to do something about it is a little more contentious. We need a framework in which, if circumstances change, incentives are in place for an appropriate, nimble response. Such circumstances might include, say, a dramatic increase in adverse climatic events (more rapid response required), or in our scientific knowledge, or a supervolcano that threatens to freeze the planet, or an unforseeable (and, admittedly unlikely) reduction in adverse climatic events. In theses latter two events a bond regime would see climate mitigation activities could be attenuated or suspended. The conventional approach would find it difficult to adapt appropriately.
My point, ultimately, is a simple one: if we target outcomes, we do not need to identify root causes to solve our complex social and environmental problems.
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