My point is that we have the technology to debate over this volume of data and this debate is likely to be more productive than elevating the issues into something that fits the ancient model of sophistic debate. With modern data mining and visualization tools, the public can discuss the details of all of the relevant features of the healthcare debate. We should learn from how learning arises in machine learning from feature selection among a large set of features with diverse measurements. In analogy to neural networks, for example, the same volume of data can be presented to networks of humans each with access to tools empowering them to observe the vast richness of the data and then use debate to mimic forward propagation of accumulating conclusions and backward propagation of derivatives of errors.
If someone wants to cause trouble for the big data owner, they can leverage the known missing data to raise accusations that the big data owner will not have any data to use in defense. The accusations can suggest cheating, fraud, criminal activities, etc that can harm reputations or invoke costly and lengthy investigations that can deny the owner of realizing the potential benefits of the big data analytics.
With the enthusiasm of personal health diagnostic tools that connect automatically (such as through smart phones) to health data vaults there is an tremendous opportunity to undermine HIPAA privacy protections by secretly encoding the individual’s contact information within the measurement data using steganography techniques. The market for cracking HIPAA protections either for private gain…
The enthusiasm for the benefits of big data comes from widely promoted reports of past successes. The promise of big data techniques is that it can provide similar successes in other contexts. Big data involves volume, velocity, and variety. The volume and velocity depend on automated queries and report building. The variety introduces the opportunity for new benefits. The combination of automation and opportunity from variety is what makes re-identification possible or even very likely.
The age of 55 matches the age I used in my discussions of parallel governments where a government of debt service has a minimum voting age of 55 and this government has jurisdiction over that age group. If such a parallel age-distinctive government existed already, it would be natural to have it also maintain a separate health policy for the older age group. The older population is the population most in need of government subsidies for health insurance as evidenced by the current Medicare policies. This proposal effectively replaces Medicare with a policy governing some type of health insurance policy (public or private) that mandates coverage for all adults over 55.
Following a dedomenocracy model of short-lived rules may have avoided these consequences because the guidelines, if issued at all, would probably only have been in place for a few years. Once expired, there would be a return to leaving the dietary choices up to the individual. As I noted above, the decision not to renew the guidelines would have sent a message that the risks are not high and that this was no longer a priority.
The measles example provides a vivid illustration of what can happen with a government that is almost entirely focused on the short term, reacting only to the most recent urgent issues using rules using the most current data that may include preliminary results that are later discredited. This example is an analogy for similar scenarios for other policy areas and with even larger hazards.