"Regrettably, our research suggests that such proactive measures are the exception rather than the rule. While AI ethics is high on the agenda for many organizations, translating AI principles into practices and behaviors is proving easier said than done. However, with stiff financial penalties at stake for noncompliance, there’s little time to waste. What should leaders do to double-down on their responsible AI initiatives?
To find answers, we engaged with organizations across a variety of industries, each at a different stage of implementing responsible AI. While data engineers and data scientists typically take on most responsibility from conception to production of AI development lifecycles, nontechnical leaders can play a key role in ensuring the integration of responsible AI. We identified four key moves — translate, integrate, calibrate and proliferate — that leaders can make to ensure that responsible AI practices are fully integrated into broader operational standards."
