Neil Walker has made an important contribution here. While a good data scientist may think he has made some points that are blindingly obvious, the sad truth is that there is a very large, and potentially very influential, group of people who either don't know it or wilfully ignore it.
The official citation: Walker, N., (2017). All or Nothing: The False Promise of Anonymity. Data Science Journal. 16, p.24. DOI: http://doi.org/10.5334/dsj-2017-024
The seminal point in this paper:
"some researchers and policy makers have conflated the notions of de-identification and anonymity. The former is a process that seeks to mitigate disclosure risk though careful application of rules and statistical analysis, while the latter is an absolute state". As Neil goes on to state in the paper, "The consequence of confusing the process and the state is profound".
He very pointedly includes the International Committee of Medical Journal Editors (ICMJE) among those who have fallen for the fallacy.
For some practicl enlightenment on how to navigate this challenge, see:
The ethics of USE as well as ACCESS will be vital. In particular, when it is or is not (as well as when it might be) adversely discriminating against an individual. Genetic data is an obvious example: just because a person has a genetic disposition to a disease or behaviour, AND it is known, the question remains: SHOULD it be used. The answer is not simple! The same applies to lifestyle behaviour that is revealed from health IoT devices: WHEN can WHO do WHAT with that knowledge? This includes the fringe dwellers in the health information ecosystem such as insurers and developers of government policy, as well as anybody involved in the clinical setting or health research.
The ethics of USE as well as ACCESS will be vital. In particular, when it is or is not (as well as when it might be) adversely discriminating against an individual. Genetic data is an obvious example: just because a person has a genetic disposition to a disease or behaviour, AND it is known, the question remains: SHOULD it be used. The answer is not simple! The same applies to lifestyle behaviour that is revealed from health IoT devices: WHEN can WHO do WHAT with that knowledge? This includes the fringe dwellers in the health information ecosystem such as insurers and developers of government policy, as well as anybody involved in the clinical setting or health research.