>> It's not ideal, but basing hiring decisions on real information (even if 'private') strikes me as better than using uninformed prejudice. In the example you give, is it better or worse to have the HR person say "Homoiconic? Sounds gay to me!"? I don't see much increased risk in offering a deeper pool of inherently unverifiable information, even if this information might be used badly.
Paraphrased: "They have poor information sources for their prejudice now, I don't see what harm better information sources driving their prejudice could do."
>> This is a good debate, but for me it's a secondary one. Even if a privacy-safe solution is theoretically possible, I fear the only likely outcome will be that Netflix buries a 'release authorization' somewhere deep within their terms of service and is dissuaded from offering similar data sets in the future.
Paraphrased: "The debate on privacy dangers is secondary, if Netflix refuses to release useful data in the future then that's the primary danger"
>> I also think that for my needs 'anonymize and release' is the only feasible solution. While online systems might be better than nothing, the approaches I'm interested in (kNN on GPU's, massively parallel cross-validations) really require local data and full control over data layout. But perhaps there is indeed a solution that works for everyone.
Paraphrased: "I was working on a project with the data, and the FTC ruling appears to have put a stop to that."