Continued Privacy Worries That Could Eradicate Predictive Analytics
Predictive analytics is an extraordinarily sophisticated business practice that is so successful it might just evolve itself to the brink of extinction.
Tech writer Vangie Beal defines the space nicely: Predictive analytics is the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. Predictive analytics doesn’t tell you what will happen in the future. It forecasts what might happen in the future with an acceptable level of reliability, and includes what-if scenarios and risk assessment.
For decades, marketers have been trying to find and exploit patterns in what makes their customers buy, buy again, stay, switch, browse, click, join, sign up, opt in and check out. And while the astonishing science behind the dozens of different strains of predictive analytics is exploding, it’s not even close to keeping pace with the stunningly vast amounts of data being collected and made available every minute of every day, on a healthy percentage of the Earth’s inhabitants.
In many countries, data privacy laws have recently and rapidly grown much more stringent, with the penalties for breaking those laws becoming significantly more onerous with each revision. Take, for example, the $1 million dollar a day fines set forth in Canada’s CASL legislation, and the prison sentences being meted out in places like Hong Kong.
The laws are generally clearly written (with China being a huge and notable exception), consistently enforced and abundantly available for inspection to all concerned. The discourse on these issues is serious, the boundaries are defined, and the apparatus for adjudicating infractions in most countries is known and robust.
What’s less obvious — and to some more worrisome — is the current murky state of data that’s collected and weaved together for use in something referred to as “alternative scores,” which are being churned out in endless complexity and with increasingly specialized purposes through the discipline of predictive analytics.