Enterprise AI in the Cloud

4Designing AI Systems Responsibly

The real problem is not whether machines think but whether men do.

—B.F. Skinner

This chapter grapples with one of the most pressing issues of our time: designing AI systems responsibly. It is even more critical if you are a data scientist, project manager, AI developer, or executive involved in implementing AI. It is not just about developing code or training models but about ensuring that what you develop is aligned with human values, ethics, and safety.

This chapter explores the key pillars of Responsible AI, from robustness and collaboration to trustworthiness and scalability. This chapter also shares the essential pillars of a Responsible AI framework, the four key principles of Responsible AI, and some of the nuances of AI design, development, and deployment. As shown in Figure 4.1, this chapter sets the stage for subsequent chapters for the practical deployment and scaling of AI. Whether you have just started or are trying to refine an existing implementation, this chapter will guide you.

THE PILLARS OF RESPONSIBLE AI

Organizations have a social and humanitarian responsibility to ensure that pre-existing prejudices and biases do not continue to operate in the post AI-deployment world.

Responsible AI is a framework created to protect human principles such as dignity, fairness, and privacy (see Figure 4.2). It is used to design and build AI systems that are ethical, transparent, fair, and socially responsible. Responsible AI basically ...