Philosophy:Goodhart's law

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Short description: Adage about statistical measures
Charles Goodhart, for whom the adage is named, delivering a speech in 2012

Goodhart's law is an adage often stated as, "When a measure becomes a target, it ceases to be a good measure".[1] It is named after British economist Charles Goodhart, who is credited with expressing the core idea of the adage in a 1975 article on monetary policy in the United Kingdom:[2]

Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.[3]

It was used to criticize the British Thatcher government for trying to conduct monetary policy on the basis of targets for broad and narrow money,[4] but the law reflects a much more general phenomenon.[5]

Priority and background

Numerous concepts are related to this idea, at least one of which predates Goodhart's statement.[6] Notably, Campbell's law likely has precedence, as Jeff Rodamar has argued, since various formulations date to 1969.[7] Other academics had similar insights at the time. Jerome Ravetz's 1971 book Scientific Knowledge and Its Social Problems[8] also predates Goodhart, though it does not formulate the same law. He discusses how systems in general can be gamed, focuses on cases where the goals of a task are complex, sophisticated, or subtle. In such cases, the persons possessing the skills to execute the tasks properly seek their own goals to the detriment of the assigned tasks. When the goals are instantiated as metrics, this could be seen as equivalent to Goodhart and Campbell's claim.

Shortly after Goodhart's publication, others suggested closely related ideas, including the Lucas critique (1976). As applied in economics, the law is also implicit in the idea of rational expectations, a theory in economics that states that those who are aware of a system of rewards and punishments will optimize their actions within that system to achieve their desired results. For example, if an employee is rewarded by the number of cars sold each month, they will try to sell more cars, even at a loss.

While it originated in the context of market responses, the law has profound implications for the selection of high-level targets in organizations.[3] Jon Danielsson states the law as

Any statistical relationship will break down when used for policy purposes.

He suggested a corollary for use in financial risk modelling:

A risk model breaks down when used for regulatory purposes.[9]

Mario Biagioli related the concept to consequences of using citation impact measures to estimate the importance of scientific publications:[10][11]

All metrics of scientific evaluation are bound to be abused. Goodhart's law [...] states that when a feature of the economy is picked as an indicator of the economy, then it inexorably ceases to function as that indicator because people start to game it.

The law is illustrated in the 2018 book The Tyranny of Metrics by Jerry Z. Muller.[12]

Generalization

Later writers generalized Goodhart's point about monetary policy into a more general adage about measures and targets in accounting and evaluation systems. In a book chapter published in 1996, Keith Hoskin wrote:

'Goodhart's Law' – That every measure which becomes a target becomes a bad measure – is inexorably, if ruefully, becoming recognized as one of the overriding laws of our times. Ruefully, for this law of the unintended consequence seems so inescapable. But it does so, I suggest, because it is the inevitable corollary of that invention of modernity: accountability.[13]

In a 1997 paper responding to the work of Hoskin and others on financial accounting and grades in education, anthropologist Marilyn Strathern expressed Goodhart's Law as "When a measure becomes a target, it ceases to be a good measure," and linked the sentiment to the history of accounting stretching back into Britain in the 1800s:

When a measure becomes a target, it ceases to be a good measure. The more a 2.1 examination performance becomes an expectation, the poorer it becomes as a discriminator of individual performances. Hoskin describes this as 'Goodhart's law', after the latter's observation on instruments for monetary control which led to other devices for monetary flexibility having to be invented. However, targets that seem measurable become enticing tools for improvement. The linking of improvement to commensurable increase produced practices of wide application. It was that conflation of 'is' and 'ought', alongside the techniques of quantifiable written assessments, which led in Hoskin's view to the modernist invention of accountability. This was articulated in Britain for the first time around 1800 as 'the awful idea of accountability' (Ref. 3, p. 268).[1]

Examples

See also

  • Campbell's law – "The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures"
  • Cobra effect - when incentives designed to solve a problem end up rewarding people for making it worse
  • Hawthorne effect – if people know they are observed, their behavior changes.
  • Gaming the system
  • Lucas critique – it is naive to try to predict the effects of a change in economic policy entirely on the basis of relationships observed in historical data
  • McNamara fallacy – involves making a decision based solely on quantitative observations (or metrics) and ignoring all others
  • Metric fixation
  • Overfitting
  • Peter principle – individuals are promoted based on success in their previous roles, and not the role of the new position
  • Reflexivity (social theory)
  • Reification (fallacy)
  • Map-territory relations — sometimes referred to via the quote "the map is not the territory". It is a type of reification (fallacy), wherein a model of something is treated as if it were exactly like the actual thing being modeled. Goodhart's law addresses a subset of map-territory problems.
  • Specification gaming in artificial intelligence
  • Surrogation

References

  1. ↑ 1.0 1.1 Strathern, Marilyn (1997). "'Improving ratings': audit in the British University system" (in en-gb). European Review (John Wiley & Sons) 5 (3): 305–321. doi:10.1002/(SICI)1234-981X(199707)5:3<305::AID-EURO184>3.0.CO;2-4. https://archive.org/details/ImprovingRatingsAuditInTheBritishUniversitySystem. 
  2. ↑ Goodhart, Charles (1975). "Problems of Monetary Management: The U.K. Experience". Papers in Monetary Economics. Papers in monetary economics 1975; 1; 1. - [Sydney]. - 1975, p. 1-20. 1. Sydney: Reserve Bank of Australia. https://www.econbiz.de/Record/problems-of-monetary-management-the-u-k-experience-goodhart-charles/10002525062. 
  3. ↑ 3.0 3.1 Goodhart, Charles (1975). "Problems of Monetary Management: The U.K. Experience". in Courakis, Anthony S. (in en-gb). Inflation, Depression, and Economic Policy in the West. Totowa, New Jersey: Barnes and Noble Books. 1981. p. 116. ISBN 0-389-20144-8. https://books.google.com/books?id=OMe6UQxu1KcC&pg=PA111. 
  4. ↑ Smith, David (1987). The Rise And Fall of Monetarism. London: Penguin Books. ISBN 9780140227543. 
  5. ↑ Manheim, David; Garrabrant, Scott (2018). "Categorizing Variants of Goodhart's Law". arXiv:1803.04585 [cs.AI].
  6. ↑ Manheim, David (29 September 2016). "Overpowered Metrics Eat Underspecified Goals" (in en-US). https://www.ribbonfarm.com/2016/09/29/soft-bias-of-underspecified-goals/. 
  7. ↑ Rodamar, Jeffery (28 November 2018). "There ought to be a law! Campbell versus Goodhart". Significance 15 (6): 9. doi:10.1111/j.1740-9713.2018.01205.x. 
  8. ↑ Ravetz, Jerome R. (1971). Scientific knowledge and its social problems. New Brunswick, New Jersey: Transaction Publishers. pp. 295–296. ISBN 1-56000-851-2. OCLC 32779931. 
  9. ↑ Daníelsson, Jón (July 2002). "The Emperor has no Clothes: Limits to Risk Modelling". Journal of Banking & Finance 26 (7): 1273–1296. doi:10.1016/S0378-4266(02)00263-7. 
  10. ↑ Biagioli, Mario (12 July 2016). "Watch out for cheats in citation game". Nature 535 (7611): 201. doi:10.1038/535201a. PMID 27411599. Bibcode: 2016Natur.535..201B. https://escholarship.org/content/qt0b05p1j6/qt0b05p1j6.pdf. 
  11. ↑ Varela, Diego; Benedetto, Giacomo; Sanchez-Santos, Jose Manuel (30 December 2014). "Editorial statement: Lessons from Goodhart's law for the management of the journal". European Journal of Government and Economics 3 (2): 100–103. doi:10.17979/ejge.2014.3.2.4299. https://revistas.udc.es/index.php/ejge/article/view/ejge.2014.3.2.4299. Retrieved 8 February 2022. 
  12. ↑ Muller, Jerry Z. (2018). The Tyranny of Metrics. Princeton University Press. ISBN 978-0-691-19126-3. https://books.google.com/books?id=dil2DwAAQBAJ. 
  13. ↑ Hoskin, Keith (1996) (in en-gb). The 'awful idea of accountability': inscribing people into the measurement of objects. 
  14. ↑ Koltun, V; Hafner, D (2021). "The h-index is no longer an effective correlate of scientific reputation.". PLOS ONE 16 (6): e0253397. doi:10.1371/journal.pone.0253397. PMID 34181681. Bibcode: 2021PLoSO..1653397K. "Our results suggest that the use of the h-index in ranking scientists should be reconsidered, and that fractional allocation measures such as h-frac provide more robust alternatives.".  Companion webpage
  15. ↑ Mooers, Arne (2022-05-23). "When is a species really extinct?" (in en). http://theconversation.com/when-is-a-species-really-extinct-182555. 
  16. ↑ Martin, T. E.; Bennett, G. C.; Fairbairn, A.; Mooers, A. O. (March 2023). "'Lost' taxa and their conservation implications" (in en). Animal Conservation 26 (1): 14–24. doi:10.1111/acv.12788. ISSN 1367-9430. https://onlinelibrary.wiley.com/doi/10.1111/acv.12788. 

Further reading



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