The Importance of Goodhart’s Law
This article introduces Goodhart’s law, provides a few examples, tries to explain an origin for the law and lists out a few general mitigations.
Goodhart’s law states that once a social or economic measure is turned into a target for policy, it will lose any information content that had qualified it to play such a role in the first place. wikipedia The law was named for its developer, Charles Goodhart, a chief economic advisor to the Bank of England.
The much more famous Lucas critique is a relatively specific formulation of the same.
The most famous examples of Goodhart’s law should be the soviet factories which when given targets on the basis of numbers of nails produced many tiny useless nails and when given targets on basis of weight produced a few giant nails. Numbers and weight both correlated well in a pre-central plan scenario. After they are made targets (in different times and periods), they lose that value.
We laugh at such ridiculous stories, because our societies are generally much better run than Soviet Russia. But the key with Goodhart’s law is that it is applicable at every level. The japanese countryside is apparently full of constructions that are going on because constructions once started in recession era are getting to be almost impossible to stop. Our society centres around money, which is supposed to be a relatively good measure of reified human effort. But many unscruplous institutions have got rich by pursuing money in many ways that people would find extremely difficult to place as value-adding.
Recently GDP Fetishism by David henderson is another good article on how Goodhart’s law is affecting societies.
The way I look at Goodhart’s law is Guess the teacher’s password writ large. People and instituitions try to achieve their explicitly stated targets in the easiest way possible, often obeying the letter of the law.
A speculative origin of Goodhart’s law
The way I see Goodhart’s law work, or a target’s utility break down, is the following.
Superiors want an undefined goal G.
They formulate G* which is not G, but until now in usual practice, G and G* have correlated.
Subordinates are given the target G*.
The well-intentioned subordinate may recognise G and suggest G** as a substitute, but such people are relatively few and far inbetween. Most people try to achieve G*.
As time goes on, every means of achieving G* is sought.
Remember that G* was formulated precisely because it is simple and more explicit than G. Hence, the persons, processes and organizations which aim at maximising G* achieve competitive advantage over those trying to juggle both G* and G.
P(G|G*) reduces with time and after a point, the correlation completely breaks down.
The mitigations to Goodhart’s law
If you consider the law to be true, solutions to Goodhart’s law are an impossibility in a non-singleton scenario. So let’s consider mitigations.
Solutions centred around Human Discretion
Pointing out what most people would have in mind as G and showing that institutions all around are not following G, but their own convoluted G*s. Hansonian cynicism is definitely the second step to mitigation in many many cases (Knowing about Goodhart’s law is the first). Most people expect universities to be about education and hospitals to be about health. Pointing out that they aren’t doing what they are supposed to be doing creates a huge cognitive dissonance in the thinking person.
Taking multiple factors into consideration, trying to make G* as strong and spoof-proof as possible. The Scorecard approach is mathematically, the simplest solution that strikes a mind when confronted with Goodhart’s law.
Optimization around the constraint
There are no generic solutions to bridging the gap between G and G*, but the body of knowledge of theory of constraints is a very good starting point for formulating better measures for corporates.
CEV tries to mitigate Goodhart’s law in a better way than mechanical measures by trying to create a complete map of human morality. If G is defined fully, there is no need for a G*. CEV tries to do it for all humanity, but as an example, individual extrapolated volition should be enough. The attempt is incomplete as of now, but it is promising.
Solutions centred around Human discretion
Human discretion is the one thing that can presently beat Goodhart’s law because the constant checking and rechecking that G and G* match. Nobody will attempt to pull off anything as weird as the large nails in such a scenario. However, this is not scalable in a strict sense because of the added testing and quality control requirements.
Left Anarchist ideas
Left anarchist ideas about small firms and workgroups are based on the fact that hierarchy will inevitably introduce goodhart’s law related problems and thus the best groups are small ones doing simple things.
On the other end of the political spectrum, Molbuggian hierarchical rule completely eliminates the mechanical aspects of the law. There is no letter of the law, its all spirit. I am supposed to take total care of my slaves and have total obedience to my master. The scalability is ensured through hierarchy.
Of all proposed solutions to the Goodhart’s law problem confronted, I like CEV the most, but that is probably a reflection on me more than anything, wanting a relatively scalable and automated solution. I’m not sure whether the human discretion supporting people are really correct in this matter.
Your comments are invited and other mitigations and solutions to Goodhart’s law are also invited.