Our collective desire to have a space where we are free from observation is increasingly under pressure from modern technology, and our confidence that data that pertains to us will be used fairly is in a deficit mode. At the same time, data are being used to create new knowledge by gaining insights that would not be possible without advanced analytics. There is no question that current privacy law, even relatively newer versions, must be thought about in this continuum. As laws get updated or created, they must not be done so in a manner that kills the golden goose of the digital age, our ability to “think with data.” 

Data driven knowledge creation, thinking with data, learning with data, no matter how one phrases it, is, as some suggest, how America gained a competitive advantage in the digital world.  Data driven knowledge creation has improved processes from individualized medicine to congestion relief.  It has also generated significant economic growth.  This driver of the digital age evolved with technology but was not part of any central economic plan until now as many of the world’s economies see digital innovation being tied to economic and societal growth.  

In the 1980’s a few statisticians began working with the credit bureaus to discover whether one could model the likelihood that a person with a particular credit history would go bankrupt.  These statisticians used old credit histories where outcomes were known.  The outcome of that research was the credit score that plays a significant role in assessing the risk related to loans, insurance, mobile phones, and many other services.  The scoring models are developed based on updating past histories.  Those models then use current data to predict the likelihood that a credit history will predict a specific event, like bankruptcy.  Decisions are then made on whether to grant credit and at what price.  Credit scoring is a classic example of thinking with data and acting with data.

Credit scoring was the beginning of today’s world where predictive sciences are used to understand human behavior beyond what is intuitive.  New knowledge is good.  Knowledge can range from a cure for cancer to personalization that is less intrusive.  Knowledge is created by university scientists and by data scientists inside organizations monitoring clicks on a website.  A significant portion of knowledge creation comes from advanced analytics that makes use of data that was collected or created for other explicit purposes.  Knowledge creation is not the same as automated decision making, even though it could lead to that outcome.  Terms like profiling conflate the two concepts. The knowledge created from analytics is neither good nor bad.  However, the use of that knowledge can create great individual and societal benefits or might lead to bad consequences for both people and society.  The key point is the consequences typically come from the misuse of the knowledge, not the knowledge itself. Laws need to reflect this distinction.

The IAF is not suggesting that data driven knowledge creation is perfect.  It is dependent on the  availability of the data, the quality of the data, and the quality of those interpreting the insights.  But, for the most part, knowledge creation is better than the alternative.

The concern is new privacy laws, particularly those emerging in the U.S., might just stifle new data driven knowledge creation as an unintended consequence in their quest to protect individuals against the application of knowledge.  

Most international data protection and privacy laws require a permission before data is processed in any form or fashion.  Repurposing data for research, whether commercial or academic, must be permitted by the law. Today, in the U.S., for the most part, using data to create new insights is not regulated by the law.  Organizations are free to think and learn with data.  It is only when the data is used that explicit sector specific laws, or general protections against unfair and deceptive practices, kick in.  Some of the applications coming from analytics have increasingly been seen as harmful.  The collecting, mining and using of personal data by technology companies caused Alastair Mactaggart to start the ballot initiative that resulted in the California Consumer Privacy Act.   

The IAF has been a supporter of new and updated legal tools, including a new comprehensive privacy law in the U. S. But as those laws are considered, it should be recognized that the freedom to think and learn with data has been a driver of many desirable outcomes, including access to new products and service and faster economic growth.

There are obligations that all organizations must bear when they both create knowledge with data and apply this knowledge. However, generally, the consequences to individuals are less when knowledge creation is the objective. By extension, the obligations should be different when knowledge is applied,  where it can have a more direct consequence on an individual.  Laws should reflect this.

When the IAF issues its legislative model this Summer, there will be specific provisions that will explicitly make data driven knowledge creation permissible with appropriate accountability safeguards in place.  As the States and Congress consider new laws, the IAF suggests they consider protecting data driven knowledge creation and look for and adjust provisions that, whether intentional or not, make thinking with data much more difficult. 

Please let us know what you think.