The GDPR: An Artificial Intelligence Killer?
With all the excitement regarding the potential of AI, there are concerns. One of the primary ones is how to address data privacy. In no other place is the concern between data privacy and artificial intelligence more pronounced than the European Union’s General Data Protection Regulation (GDPR).
The GDPR, adopted in April 2016 and taking effect this May, is the first change to EU privacy laws in 23 years. The Council of the European Union’s intention is to strengthen and unify data protection for all individuals within the EU. The GDPR aims primarily to give control back to EU residents over their personal data and how it gets processed, and regardless of whether you are based in an EU member nation or not, your organization is still required to adhere to the GDPR if you process the data of anyone residing in the EU.
While many of the data management aspects of the GDPR have organizations frantically working to meet the deadline, the area that covers how AI and GDPR coexist has many rethinking how they will market in the future.
Consider some of the aspects of the GDPR as it relates to the profiling and use of analytics on individuals:
While all these GDPR rules are daunting to organizations that have used “traditional” analytics for years, the use of AI within the realm of profiling and analytics poses even more challenges. Some have even asked, “Is the GDPR an AI killer?”
Artificial intelligence is the science of training systems to emulate human tasks through learning and automation. With AI, machines can learn from experience, adjust to new inputs and accomplish specific tasks without manual intervention. The explosion in market hype around the term is closely tied to advances in deep learning and cognitive science, but AI spans a variety of algorithms and methods. An application doesn’t require the newest technologies to be considered AI.
AI systems extract insights from the data they are fed. And machine intelligence can’t take into consideration factors that exist outside of the data as it is presented. This means that the system is not going to magically comply with GDPR unless humans explicitly program AI systems to prompt, tag and associate consent actions as part of a data management framework. Likewise, algorithmic bias is a reflection of human bias threaded throughout the data that is presented to the machine. A machine will learn bias if the data holds bias; it cannot learn bias from interactions as humans do.
