Why Businesses Need Ethical, Responsible AI To Thrive

Mohanty is an award-winning AI leader & entrepreneur. She is an Applied Science Manager at Amazon & Vice Chair of IEEE Women in Engineering.

With AI applications already in everything from business to science and ecology to society, businesses need to realize that it’s not about adopting AI faster than your competitors but about adopting it more wisely. Leaders need to ensure that when integrating AI, they start with ethical foundations and move forward with responsible practices, ultimately gaining trust—both internally and externally.

What Is Ethical And Responsible AI? What’s the Difference?

Although the two concepts are closely related, they aren’t identical. Ethical AI defines the moral compass an institution needs to consider before adopting AI and includes values such as dignity, fairness, human agency, inclusion, privacy and social benefit. Responsible AI, on the other hand, attempts to ensure these values make it into company operations, with practices like accountability, governance, human oversight, monitoring, risk controls, testing and transparency. Essentially, businesses need ethical AI foundations translating into responsible AI practices. The former are the guiding principles while the latter are the steering, brakes and dashboard.

Finally, looking at scientific research on these principles, we see a reinforcement in the same direction. One systematic review of responsible AI principles and practices notes that it’s emerged as a way to ensure protections without stifling innovation while minimizing risks to people, society and the environment. Other research on responsible AI also highlights ethics, explainability, privacy, security, trust and a human-centric approach as essential to trustworthy AI deployment.