[temp8964]

This article is totally gibberish. It's a terrible mixture of many unrelated things. Just because those things all have something to do with data (anything can be presented in numeric form), it does not make their issues are about data.

First, the Tony Blair example is not about data. It is a failure of government planning. It's wrong politics and wrong economy.

The G.D.P. example is laughable. G.D.P. is never intended to be used to compare individual cases. What kind of nonsense is this?

And the IQ example. The results are backed by decades of extensive studies. The author thinks picking a few critics can invalidate the whole field. And look! The white supremacist who gave Asians the highest IQ, what a disgrace to his own ideology.

Many more. I feel it's kind of tactic to produce this kind of article. Just glue a bunch of stuff, throw together with somethings seem to be related, bam, you got an article.

[cloogshicer]

Gotta disagree here. This article is acknowledging a pattern, that data is misused in many different areas.

I think the problem goes even deeper, which is a misunderstanding of the scientific method. Good discussion about this topic here: https://news.ycombinator.com/item?id=26122712

[temp8964]

"data is misused in many different areas" is not a valuable / informative point.

There are many wrongs seem to have something to do with data, but in fact they are not.

Like socialist economy planning will eventually fail, but then you would say they misused data. It seems relevant, but misusing the data is not the real cause of their failure at all.

[not2b]

Replace "socialist" with "large company". The companies gather data, establish metrics, and manage to those numbers, and often bad things result. Ever been in a company where some internal support function goes to hell because its top manager's bonus depends on a metric, and they can improve that metric by refusing to support the users (find excuses to close IT support calls without fixing the issue, etc).

[temp8964]

Yes. But then some would say the company fail because it "misused data", but it was not the real cause of the company's failure. Any project involves using data could blame the failure on "misused data" which is an useless conclusion.