Ethical Frameworks for AI Aren’t Enough

Many organizations have adopted a set of high-level principles to ensure that their AI makes decisions in an ethical fashion and causes no harm. But to give the principles teeth, organizations need to have an implementation strategy that includes concrete metrics that can be measured and monitored by engineers, data scientists, and legal personnel. Because there is no one-size-fits-all approach to quantifying potential harms created by AI, metrics are likely to vary across organizations, use cases, and regulatory jurisdictions. But that need not discourage organizations; they can draw from a combination of existing research, legal precedents, and technical best practices.