That may very well be. But not only is it a hypothetical, it would also be a far cry from being 'registered as a drug user'. Don't we have enough hyperboles in the news?
My response to this, is to paint what I consider a likely scenario concerning the misuse of this data.
Suppose, someplace down the line, the dutch govt devides they want to cross reference the telephone contacts of known drug dealers, with the intent to produce webs og association, and thus to profile potential drug rings, syndicates, or cartel associations.
There are people in this database that will false positive, and do so alarmingly often: rehab social workers, case workers, and public defenders.
A very poorly made data analysis tool will not properly vet the associations it concludes likely, and thus those classes of people will get terrorized by enforcement efforts. I have very low confidence that a mid level government worker will do the necessary cross-reference due diligence to trap these false positives and exclude them. (There is often additional oversight and data use restrictions for leveraging another database, such as the contact information of these classes of individual, and in the interests of 'simplicity', 'expediency', and 'cost', that kind of sanity checking will not be done.
I have a higher confidence that what they will do instead, is tell thier badly made data analytics algo to ignore certain phone numbers, which will lead to bitrot on why certain numbers are not weighed, and then to corruption when that list of ignored numbers leaks to actual criminal elements.
Additionally, despite those kinds of "not fit for purpose" false positives (and later, false negatives), and the potential for benign spurrious correlations (small towns suggesting widespread criminal drug activity, when in reality the small town just has a small population, and thus a higher degree of intersocial connectivity as a baseline, tripping up the badly made algo), policy makers will want to use the number and sizes of these relation webs to gauge drug enforcement resource allocation (eg, as an estimated proxy for organized drug crime), leading to internal pressure to never cull spurrious and false results, (nobody wants funding cuts! Just funding increases!) Leading to very poor policy being dictated by bad analytics, on dubious, not fit for purpose data.
Granted, that is nearly pure speculation on my part, but government functionaries I have interacted with in the past have left me with a decidedly pessimist outlook on how they handle and try to use data.
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Topic: Things that made you go "WTF?" today o_O (Read 14570846 times)