Even worse. Many people say they “don’t have anything to hide” because they too haven’t considered the vast consequences regardless of having something to hide. For starters, when the data is inaccurate, you might have something to hide that even you didn’t know about, and it could be responsible for all sorts of events and opportunities in your life both public and private without you even knowing. Things that give you an different life experience than your friends to an unknown degree. This sort of lack of knowledge, control, deprivation of explanation or closure etc. would be the lived experience of chaos and it’s one of the most frightening parts.
Birth certificates. Creditworthiness.
At the age of 54, Sigmund Arywitz was a healthy American success story. He was making $30,000 a year as executive secretary and treasurer of the Los Angeles County Federation of Labor, AFL-CIO, his family was sound, his reputation high on all counts, and he had just finished eight prestigious years in Sacramento as state labor commissioner under Gov. Edmund G. (Pat) Brown. But something was awry. In the space of one year, five Los Angeles department stores refused Sig Arywitz charge accounts, and a major car-leasing company turned him down for credit -- even though he had a walletful of oil-company and other credit cards and had always paid his bills on time....
1970
http://www.thedailybeast.com/articles/2013/06/11/is-privacy-...
See also: Cardinal Richelieu.
Context on the reference: https://history.stackexchange.com/questions/23785/what-did-r...
Imagine you're a pastor at a church and a datadump claims you're an atheist. Maybe you can convince people it's a mistake, maybe you can't.
> Each record contains entries that go far beyond contact information and public records to include more than 400 variables on a vast range of specific characteristics: whether the person smokes, their religion, whether they have dogs or cats, and interests as varied as scuba diving and plus-size apparel.
It might be "comprehensive" but is it comprehensive in a scary way? It's probably just 400 machine learning features that are estimating what people might like, so not necessarily super accurate?