Corporate Data Ethics: Data Governance Transformations for the Age of Advanced Analytics and AI

Abstract

Companies today increasingly say that they seek to engage in the "ethical" use of AI and advanced analytics. On one level, this makes sense. Along with their benefits, these technologies pose threats that traditional privacy law is ill-suited to address. To protect consumers and their own reputations, companies need to do more than simply comply with the law. They need to handle data ethically and responsibly.

But what, specifically, does that mean? How are companies drawing the difficult lines between what is “ethical” and fair, and what is not? How are they managing their operations to achieve this end? More fundamentally, if it is true that the law does not require these measures, then how do these companies rationalize investing in them? Much of the existing literature on these questions is normative and abstract. There is little descriptive research on how corporate data ethics manifests itself in practice.

An inter-disciplinary Ohio State research team is seeking to fill this gap. For the past two years, the team has been interviewing Chief Privacy Officers and others to better understand why leading companies are pursuing data ethics, and what this looks like in practice. The team is currently undertaking a second, survey phase of the research.

Given the rapidity with which this field is developing, the researchers decided not to wait for the completion of the survey phase to share this initial report of findings from the interview phase. This Report provides first-hand accounts of the ethical dilemmas that companies encounter, the emerging substantive frameworks that they use to assess them, and the management processes that they employ to pursue data ethics. The researchers then hypothesize why the field of corporate data ethics is developing and why distinct types of companies may approach the task differently. This initial report should provide useful ideas for companies seeking to pursue data ethics. It should also offer insights, and raise questions, for those seeking to improve the law, policy and practice of corporate data ethics.

Keywords: business ethics, data ethics, AI ethics, algorithm, data analytics, big data, artificial intelligence, data privacy, algorithmic bias, privacy management, corporate social responsibility

JEL Classification: L50, L53, L86, M14, M15, M38, O31, O35, O38