Organizations can build ethically robust AI systems and gain trust by bridging the gap between high-level principles and the design of AI systems. This is important as technology, including AI, is not value-neutral and the design decisions made during development impart certain values to AI. The cost of being an AI ethics laggard is high, with organizations risking losing trusted customer relationships. The use of AI-powered innovations such as facial recognition is increasing, leading to increased legal and societal scrutiny of the ethics of AI. Organizations should operationalize ethical principles such as transparency and fairness, and evolve their internal practices to build trust with key stakeholders, including customers and employees.
