How and Where Data Privatization Can Be Implemented

Written by Drew J. Lipman, PhD, Lead Data Scientist at Hypergiant

Having discussed why data privatization is good for the consumer, how does it benefit corporations? And how can the public leverage enough control to convince major corporations to not keep users’ data? The obstacles here are twofold: (1) getting enough people to go in the same direction when most do not realize that there is a problem and (2) using that mass movement of public opinion to convince corporations that it is in their interest to do something.

Corporate Interests

Out of these two issues, the second is (oddly enough) easier to approach. What are corporations interested in and how can that be used as leverage? At their core, major corporations become major corporations by always having one eye on the bottom line. And, since their interests are easily understood, they are easier to discuss. In order to make data privatization a reality for such enterprises, the collection, storage, and sale of consumer data needs to become less profitable.

Easier said than done. Big Data is a billion-dollar industry and consumer data usage has been a part of corporate Big Data for almost two decades. Google, for example, was founded in 1998 based on its ability to understand what people are interested in and looking for — a service offering that requires access to people’s data.

How do we make an approach like Google’s unprofitable? Well, unless you are in the habit of browsing via VPN or TOR, your Internet service provider (along with Google, Microsoft, or any search engine of your choice) knows what you search for and click on. And, given how irate people get over even the smallest slow down of their regular Internet browsing, VPN and TOR are not ideal tools for affecting a major, cultural change.

Alternatively, we can make it cheaper to not collect, store, and disseminate data. First of all, storing individualized data in the Cloud would not only grant (limited) permission to major corporations, but it would also remove their data storage costs. Second, if the access permissions for a single corporation were broad enough, then the number of calls upon the data would not be a problem either. Lastly, with the advent of Homomorphic Encryption, it may soon be feasible to do large computations directly in the Cloud, without having to decrypt any data sets — another development that would lighten a corporation’s hardware or vendor costs.

Method options certainly exist, but garnering enough interest in privatized data to make them feasible is another challenge entirely. The only way to convince a large group of people to do something, in fact, is to convince them that they want to do it. To paraphrase Locke: a technology only lasts as long as people consent to its usage. Perhaps the best (and only) approach to convincing people to implement privatization in their day-to-day lives is education — an exchange that you are participating in at this very moment. The more people understand data usage, and their options surrounding it, the better we are as a whole.

Mutually Beneficial Privatization

Several applications of privatization stand to better user experience as much as they stand to optimize business processes. Online identity verification is a good example. Rather than your email or cell phone, a properly implemented system of privatized data could be used to verify your identity. As it should be given email’s failings in this department.

Another privatization application relates to education. If data privatization is applied to include educational data, then each individual’s qualifications and certifications become easily accessible in real time. For example, a Computer Science student with privatized data showing his qualifications in JavaScript, C++, and Knowledge Graphs can validate his competencies even without a degree. In other words, his education to date has value — even if he did not complete some line-in-the-sand collection of requirements set by people outside of his chosen employer or industry.

Want to learn more about how machine intelligence factors into your data privacy and that of your users or consumers? Download our full PDF on data privatization here.