Ethical Applications for Workplace of the Future.

• Position: DATA SCIENCE

We increasingly place our trust in algorithms, whether applying for a mortgage, a new job, or making personal health decisions, but what about the security system that uses facial recognition and locks out a 55-year-old office custodian from her night shift, or the groups of people automatically cropped out of photos on social media? These are the unintended, and often unfair, consequences of data science tools amplified across millions of users. They also are highly preventable.

This is the lesson that M. Elizabeth Kams embeds in every course she teaches in the Department of Statistics and Data Science at Cornell University, Ithaca, N.Y Her students will be deciding how to use data in the future, and while bad decisionmaking in business is not new, Kams says it is the accelerated and aggregated effect of today's data science applications that is so dangerous: individual, team, or even a whole company's worth of decisions instantly can affect the lives of millions of people.

Moreover, the torrent of new technologies is moving faster than our regulatory systems, leaving a gap in accountability. Even data scientists themselves often do not know exactly what is happening inside their algorithms.

'This little magic box [the algorithm] is determining our life choices, often without any transparency, due process, or a way to appeal," says Kams. 'That is why ethics is so important. We don't have to further marginalize certain groups and individuals should not have to worry about their safety because of poorly and unethically conceived data applications."

Kams begins her courses with an overview of macro-level data science issues of fairness, justice, safety, and privacy, then shifts focus to individual choices. Those choices, says Kams, are rooted in virtue ethics--the personal values or virtues that drive our behavior. She guides...