I was honored to address students at the National Law University, Delhi this past week about privacy in the US and global privacy trends and issues. The talk included a Q and A session, during which the students engaged in a spirited conversation about US policies regarding surveillance and privacy. I enjoyed the session thoroughly. The students asked challenging questions in particular about telecommunications policies and the idea of safety versus privacy and achieving proper balance.

The World Privacy Forum’s recent public comments to the White House regarding Big Data focus on using a foundation of Fair Information Principles to address issues connected to bias, error, and privacy regarding big data as applied to vulnerable populations. The comments also discuss large medical research data sets, and stress the importance of applying

The World Privacy Forum submitted comments to the Securities and Exchange Commission today requesting that the SEC do more to protect the privacy of consumers’ asset information. Asset information — the financial information attached to mortgages, car loans, and other consumer borrowing activities– is very attractive to the consumer data industry. We would be happier with the current SEC proposal if it were practical to keep all sensitive asset-level data under the direct control of the Commission or, perhaps, the Consumer Finance Protection Bureau. Direct involvement by a federal agency, while no guarantee of a better outcome for data subjects, would provide better and clearer accountability for maintenance of the data as well as the possibility of meaningful enforcement.

To score is human. Ranking individuals by grades and other performance numbers is as old as human society. Consumer scores — numbers given to individuals to describe or predict their characteristics, habits, or predilections — are a modern day numeric shorthand that ranks, separates, sifts, and otherwise categorizes individuals and also predicts their potential future actions. This new report by Pam Dixon and Robert Gellman explores this issue of predictive scores and privacy.

This op ed was originally published Wednesday, March 19 2014 in IAPP for the FTC Alternate Scoring Conference.

In our modern sea of data, the resources to examine all relevant information regarding a decision is no longer feasible, so we use shortcuts. Consumer scores built using predictive analytics and fed by large datasets are the modern-day shortcuts to understanding individual consumer behavior. That’s why new and unregulated consumer scores abound. They are used widely in today’s world to predict consumers’ behavior, spending, health, fraud, profitability, and much more. These scores rely on petabytes of information coming from newly available data streams, and some old ones.