Protecting Data from Users: Some Thoughts on Guidelines

Statistical software is so easily available, and at so low a cost, that any software user with data can execute assorted analyses by themselves. There may be little or no intervention or analytic oversight guiding the process. A point of great concern, amplified by omnipresent “data science,” is the ease with which software users can torture data through analyses without fully appreciating or understanding the information extracted. There are consequences, risks, affecting conclusions reached and decisions taken. A more subtle way of addressing this concern, has been to suggest building protections into the process. And just to be sure, by “protections” is meant “protecting data from the user”.

Data are meant to be innocent (themselves having no agenda) pieces of information, evidence, then reduced via analysis to some insight or result upon which a decision can be made regarding “next steps”. At issue then is how can data be analyzed, and reported, protecting this information, ensuring a reasonably clear direction for the required decision, reported with an equally clear sense of risk assessment.