April 24, 2021•601 words
Data collection, processing and collation can be effective in fighting racism, but it can also be used to further a racist agenda. The Nazi regime ran large-scale censuses in the 1930s, collecting data on Jewish people (and other groups). The data collected was then used to assist in the orchestration of the Holocaust.  The Nazi regime is a good example of how "data-driven" decision making does not excuse the requirement for moral considerations and reflections.
Because of this the German language is quite probably unique in being the only langauge to have a word (Volkszählungsurteil) for the court ruling declaring that a (mandatory) state census is in violation of the constitution.  The ban on the census, handed down by the court in Karlsruhe in 1983 effectively stopped a census from being conducted in Germany. The ruling was not an isolated event – it builds on a general feeling in Germany that data protection is important; Germany was the first country (in 1970) to introduce any form of data protection legislation (in Hessen); in 1978 federal law was ratified, which specified that the state could collect and use data only for the purpose specified, with valid reasons and for limited periods of time.
In more recent times (and this is clearly a completely different case to the Nazi dictatorship) the British Home Office has used data to support its attempts to create a "hostile environment." From collecting data from charities in order to deport rought sleepers , to using data from the National Health Service to locate people that it wishes to deport , data processing in order to oppress ethnic minorities remains prevalent. This is the sort of data processing that half a century of data protection legislation in Germany attempts to prevent (though I suspect that the authors of the legislation were not very concerned with the rights of people from ethnic minority backgrounds).
The use of data is a double-edged sword; of course it can be used to fight racism, but it can also be used to further racist projects. It can be used to drive police reform that means justice for ethnic minorities; it can also be used by police to justify sending officers to neighbourhoods which are predominantly inhabited by people from ethnic minority backgrounds .
When considering how data collection can be used to combat racism, data cannot be considered value-neutral. It can be used to shine a light on racism that we could not otherwise perceive (for example the work of W.E. B. Du Bois), but it can also be used to racist ends. It is important not to forget that modern statistians stand on the shoulders of giants – racist, eugenisist giants (e.g.
Francis Galton, Karl Pearson), and that the privileging of data above all else is hardly a healthy epistemology.
P.S. This isn't to say that Germany shouldn't collect data on ethnic minorities – it's just that advocating broadly for more data processing is not a sensible strategy. Only data processing conducted transparently, for stated reasons, and in a way that does not endanger people's rights can be legitimate (in a state which relies on the consent of its citizens to govern).
 To be fair, however, the German language does words for many things one wouldn't really anticipate including (until recently) the word Rindfleischetikettierungsüberwachungsaufgabenübertragungsgesetz (which was the name of a law changing something about the monitoring of how beef is labelled).
 For more about this see IBM and the Holocaust, Edwin Black
 See Cathy O'Neill's "Weapons of Math Destruction" (can't remember the exact