97 Things About Ethics Everyone in Data Science Should Know

Chapter 74. Framework for Designing Ethics into Enterprise Data

Keri McConnell

Executive Director, Northwestern Mutual Data Science Institute, Northwestern Mutual

If you are leading any enterprise effort to deploy data and predictive models, it’s critical that you design ethics into the process early on. You want your team to be confident that the ethical aspects of their deployment are addressed in a way that contributes to an amazing customer experience, and being proactive can help your project teams plan for the necessary steps and costs to achieve just that. Not sure where to start? Here are four strategic steps to take to enable your enterprise to design ethics into your technology and data science efforts from the start.

Take a Tiered Approach

Institutionalizing ethics may seem like something that should be second nature—after all, you likely have gone to great effort to ensure that you hire employees with a strong ethic. However, to avoid any unintentional interference with that ethic, your teams need to understand why having the principles articulated is critical. You can start by taking a tiered approach to designing the ethical principles, beginning with why you need them. The why is addressed with an aspirational statement and commitment and through articulation of the alignment between the enterprise’s core values and how data and analytics efforts can support those ...