Why You Need an AI Ethics Committee

Expert oversight will help you safeguard your data and your brand.

by

Reid Blackman

by

Reid Blackman

From the Magazine (July–August 2022) · Long read

Ondrea Barbe/Trunk Archive

Summary.

Artificial intelligence poses a lot of ethical risks to businesses: It may promote bias, lead to invasions of privacy, and in the case of self-driving cars, even cause deadly accidents. Because AI is built to operate at scale, when a problem occurs, the impact is huge. Consider the AI that many health systems were using to spot high-risk patients in need of follow-up care. Researchers found that only 18% of the patients identified by the AI were Black—even though Black people accounted for 46% of the sickest patients. And the discriminatory AI was applied to at least 100 million patients.

The sources of problems in AI are many. For starters, the data used to train it may reflect historical bias. The health systems’ AI was trained with data showing that Black people received fewer health care resources, leading the algorithm to infer that they needed less help. The data may undersample certain subpopulations. Or the wrong goal may be set for the AI. Such issues aren’t easy to address, and they can’t be remedied with a technical fix. You need a committee—comprising ethicists, lawyers, technologists, business strategists, and bias scouts—to review any AI your firm develops or buys to identify the ethical risks it presents and address how to mitigate them. This article describes how to set up such a committee effectively.

Idea in Brief

The Problem

Bias will find its way into AI and machine-learning models no matter how strong your technology is or how diverse your organization may be.

The Reason

There are many sources of biased AI, all of which can easily fly under the radar of data scientists and other technologists.

The Solution

An AI ethics committee can identify and mitigate the ethical risks of AI products that are developed in-house or procured from third-party vendors.

In 2019 a study published in the journal Science found that artificial intelligence from Optum, which many health systems were using to spot high-risk patients who should receive follow-up care, was prompting medical professionals to pay more attention to white people than to Black people. Only 18% of the people identified by the AI were Black, while 82% were white. After reviewing data on the patients who were actually the sickest, the researchers calculated that the numbers should have been about 46% and 53%, respectively. The impact was far-reaching: The researchers estimated that the AI had been applied to at least 100 million patients.

A version of this article appeared in the July–August 2022 issue of Harvard Business Review.

Reid Blackman is the author of Ethical Machines (Harvard Business Review Press, 2022), the host of a podcast by the same name, and the founder and CEO of Virtue, a digital ethical risk consultancy. He advises the government of Canada on federal AI regulations and corporations on how to implement digital ethical risk programs. He has been a senior adviser to the Deloitte AI Institute, served on Ernst & Young’s AI Advisory Board, and volunteers as the chief ethics officer to the nonprofit Government Blockchain Association. Previously he was a professor of philosophy at Colgate University and the University of North Carolina, Chapel Hill.

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Why You Need an AI Ethics Committee

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