97 Things About Ethics Everyone in Data Science Should Know

Chapter 36. Ethical Issues Are Front and Center in Today’s Data Landscape

Kenneth Viciana

Director, Information Risk Management, Fiserv

Looking back at my data journey, it’s really amazing how data management has evolved. I began working in the enterprise data warehouse (EDW) era. We were focused on building a “single source of the truth” that a company could rely on for decision-making, analytics, and reporting capabilities. Lots of money was spent on resources and infrastructure in order to rationalize/organize/store data, and to ensure it was deemed to be fit for use.

Fast-forward, and companies switched gears and began embracing Big Data. The model shifted, as companies wanted to quickly analyze large datasets to determine whether value could be captured prior to spending time, money, and resources to organize and store the data. Companies believed that having huge quantities of data alone was a differentiator. They touted the size of their Hadoop clusters and hired armies of data scientists to find value in Big Data. At this juncture, ethics truly became a game changer in this space!

Data innovation efforts were focused on creating hypotheses and use cases to monetize data. But this presented some key ethical concerns about:

• Data ownership

• Data transparency

• Consumer consent

• Data privacy

• Data security

We’ve seen Facebook made the poster child for data privacy, with Mark ...