A Practical Guide to Building Ethical AI

Author: Reid Blackman

Publisher: The Harvard Business Review

Publication Year: 2020

Summary: The following article describes how failing to account for ethical issues in artificial intelligence (AI) can lead to reputational, regulatory, and legal risks for companies, as well as wasted time, money, and resources if the company is not able to move forward with the AI product due to fallout from poor handling of data. Companies need a clear plan to deal with ethical issues arising from use of AI. Companies should: 1). Identify existing infrastructure that a data and AI ethics program can leverage, such as a data governance board that convenes to discuss privacy, cyber, compliance, and other data-related risks; 2). Create a data and AI ethical risk framework that is tailored to the company’s industry; 3). Change how we think about ethics by taking cues from the successes in healthcare; 4). Optimize guidance and tools for product managers; 5). Build organizational awareness; 6). Formally and informally incentivize employees to play a role in identifying AI ethical risks; and 7). Monitor impacts and engage stakeholders.