Shashikala Patil

The fast nature of the spread of AI-based products in the sectors has reshaped the way organizations design, deliver, and scale digital innovations. Nevertheless, this growth has also increased ethical, social, and governance issues associated with algorithmic bias, lack of transparency, threats to privacy, and absence of accountability. Current strategies of AI ethics are significantly based on post-hoc audits, regulatory compliance, or reactive governance systems that are not always effective to combat ethical risks that occurred at the stage of product design and development. This chapter contributes to ethics by design as a proactive model to instill responsibility all over the life cycle of developing an AI-assisted product. By following the approach of conceptual synthesis, the research synthesizes information on AI ethics, responsible innovation, and product development literature to create a full set of ethics-by-design. The framework illustrates that the ethical aspects can be properly incorporated at major phases, such as ideation, data governance, model development, testing, deployment, and post-deployment monitoring. The chapter emphasizes the ways organizations can reduce ethical risks without jeopardizing innovation and competitive advantage by transforming ethics as an externality to an internal design capability. The chapter makes contributions to theory by establishing ethics as a design science in AI innovation, and to practice by providing practical advice to AI product teams. Policy impact focuses on supplementing regulation with design-based responsibility in promoting trustworthy, ESG-aligned, and sustainable AI innovation.