97 Things About Ethics Everyone in Data Science Should Know

Chapter 87. Five Core Virtues for Data Science and Artificial Intelligence

Aaron Burciaga

Global Operations Director, Analytics & Artificial Intelligence, HCL Technologies

Virtues should be digitized. As we speed toward reliance on machines to process more and more information in order to provide cognitive support for all types of decision making, we must consider ways to imbue automated processes, data machinations, and recommender systems with a sense of some of the finest human virtues.

We are at the crossroads of a moral decision in AI—what I call the codification of virtue (or not). We either both address historic biases and impose just standards for reality based on fair data and decision making that seeds an ever-better world, or we fail to jettison anachronistic social norms and business practices that are the antithesis of virtuous intelligence, independent flesh, or silicon.

The Greek philosopher Epictetus said, “One cannot learn what they think they already know.” This is particularly relevant in AI and among its engineers inasmuch as the system, or the human(s) creating the system, must be thoughtful, methodical, and explicit in how they’ve embedded an algorithm. A machine will not, and in fact cannot, do this of its own accord.

This has been a common shortfall I’ve had to address throughout projects I’ve led, in programs and teams I’ve developed, and across solutions ...