Arguing with Edward Snowden

A Data Scientist’s take on defending Machine Learning models

Mor Kapronczay
Mar 12 · 5 min read


I’ve recently read Edward Snowden’s Permanent Record during my holiday. I think it is a great book that I highly recommend for basically anyone, however it is particularly interesting for IT-folks for the obvious reasons. It is a great story about a guy growing up together with the internet, starts to serve his country in a patriotic fervour after 9/11, and becomes a whistleblower when he notices the US has gone too far violating privacy in the name of security. Moreover, a paradox I found most interesting is something a Data Scientist can easily relate to.

Model explainability

There is an example in the book about COMPAS, a widely used risk-assessment algorithm in the judicial system of the USA. In this case, the point is that an algorithm made a decision having a substantial effect on someone’s life — and neither we nor the algorithm can even explain why so. I think this is an inherently wrong and ill-disposed point of view.

Advertisements and recommendations

A second argument I did not like in the book was about recommendations in general. The author states that recommendations are just about softly pressuring the customer to buy what others did buy. I think this argument misses the real point here.


In general, I really liked the book. I also admire the bravery of Mr. Snowden that started a discussion about privacy, and the trade-off between privacy invasion and crime prevention. But I also think that the book expresses a negative attitude towards everything in connection with using large amounts of data. Opposing this, I believe that statistical models built on top of massive datasets can greatly benefit humanity — if used for the right purposes, transparently and responsibly.

Starschema Blog

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Thanks to TothBenedek

Mor Kapronczay

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Starschema Blog

Data contains intelligence that can change the world — we help people discover, manage and use this intelligence.

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