There are personal ethics, frequently referred to by ethics professors as “sandbox values” or “Sunday school ethics”; professional ethics, the codes of conduct specified by various disciplines (e.g., lawyers, accountants, doctors, financial advisors, engineers); and institutional ethics, which constitute normative behaviors of an organization or department. Of increasing importance are something known as “cohort ethics” — the assumption that your ethics are the sum of the value sets of your five closest friends.
Special Professor of Law Janis Meyer, who teaches “Legal Ethics” at The Maurice A. Deane School of Law at Hofstra University and “Professional Responsibility” at Columbia University School of Law, recently spoke at the virtual “Responsibility of Information Management” Digital Solutions Gallery at The Ohio State University. (Her remarks start at the 30:15 mark.) There, Meyer explained that there can be a difference between “professional ethics,” as specified for lawyers in state and federal law, and morals, aka personal beliefs and values.
Meyer asked, “Does IT have unambiguously articulated professional ethics?” This is something our profession needs to work on. In the soon-to-be-published The Day Before IT Transformation: Unlocking Digital Transformation for Business Leaders, Cheryl Smith, former CIO at McKesson, West Jet, and Keyspan, argues that without industry- and discipline-accepted “Technology Leadership Practices” it is essentially impossible to articulate professional ethics for IT.
Ethics are much bigger than a set of simple rules — for example, “Don’t lie,” “Don’t cheat,” or “Don’t steal other children’s toys.” Ethics are more than “checking the box” on environmental, social, and governance (ESG) and diversity, equity, and inclusion (DEI) audits.
Ethics drive how we frame and make decisions. How do we protect people’s privacy when AI needs so much data? Imagine you are programming a driverless car. When confronted with a crash scenario, should the car save its single occupant or seven pedestrians? Should the car prioritize saving older people or younger people? When using analytics, on what basis should hospitals allocate scarce beds in the intensive care unit? When screening job applicants, which resumes are rejected and which are reviewed? When deploying police, where should resources be focused? IT is not neutral or above the tough ethical questions organizations are confronting.
Currently the spotlight in tech ethics is split between how organizations treat their IT employees and how to prevent algorithmic misbehavior — for example, how to eliminate bias in training data. There is a movement under way to create a new human right against being subject to automated decision-making.
