5 ms·
This is called risk selection, and is already a common practice [1] that doesn't require much in the way of "health data" [2]. I suspect that 80% of the effect
by tqi 6y ago
This is called risk selection, and is already a common practice [1] that doesn't require much in the way of "health data" [2]. I suspect that 80% of the effect can be achieved via "simple" methods like advertising on health and fitness related sites or keywords, partnering with gyms to advertise to members, etc. ACA has some provisions to help address these incentives [3], though it's unclear how effective they are.
The Privacy / Big Tech angle is attention grabbing, but is grossly missing the point. In my opinion, the reality is we need to decide if this type of discrimination is something we as a society want to regulate or not.
[1] https://www.nber.org/papers/w19198 https://www.nber.org/papers/w19198
[2] https://www.federalreserve.gov/econresdata/feds/2015/files/2015101pap.pdf https://www.federalreserve.gov/econresdata/feds/2015/files/2...
[3] https://www.kff.org/health-reform/issue-brief/explaining-health-care-reform-risk-adjustment-reinsurance-and-risk-corridors/ https://www.kff.org/health-reform/issue-brief/explaining-hea...
- rapind 6y agoI’m not sure it’s missing the point though. I think the specificity and scale that big tech brings can change the impact of these practices significantly. Some thing’s are not be a big risk to society until they get amplified.
- tqi 6y agoAgree that is possible, but from what I've seen for the most part big data and predictive ML has been incremental (at best) to more naive methods.
- disgruntledphd2 6y agoYup, yup. The real efficiencies in insurance come from data, not models. This is mostly true because the models which can be used are massively regulated, and must be explained to regulators (which sounds like a fun job).