The IEEE Standards Association has published a paper that explores the metrics of success for responsible artificial intelligence (AI). The paper provides insights from a dozen industry experts, based on their front-line experiences as responsible AI technologists and AI ethics, ESG (Environmental, Social, and Governance)/metrics, and sustainability thought leaders and practitioners in their organizations.

An extension of IEEE’s paper “A Call to Action for Businesses Using AI,” the new publication provides an introduction and recommendations for how organizations can begin and grow the process of incorporating well-being metrics into creating and maintaining their artificial intelligence systems (AIS).

The paper addresses key questions in three sections:

• Assess: What organizational values are leveraged for Responsible AI metrics?
• Apply: How does an organization implement the principles and metrics of Responsible AI?
• Amplify: How does an organization scale its work to grow and measure the success of Responsible AI metrics?

“We recommend that organizations define what responsible means at the outset of design and throughout the entire life cycle of their AIS by being accountable to expanded key performance indicators (KPIs),” the authors write. “While common business performance metrics focus on financial indicators primarily, organizations risk causing unintended harm when issues of human well-being or ecological sustainability are not prioritized in their planning.”

The paper also recognizes the standard IEEE 7000-2021, IEEE Standard Model Process for Addressing Ethical Concerns During System Design, which provides a clear methodology to analyze human and social values relevant for an ethical system engineering effort.

Access “Prioritizing People and Planet as the Metrics for Responsible AI,” online via IEEE SA.