The emergence of generative artificial intelligence (AI) has brought about transformative possibilities and the potential to benefit how we work, live, and interact with the world. However, it is crucial to recognize the responsibility that comes with such powerful technology.
When I speak to executives today, there is a lot of enthusiasm and excitement to get started with AI—and even more so with generative AI. But they often ask, “How can I do it in a responsible, safe way that delivers the best experience for my customers?” And this is an important question, especially as we see new challenges arise with generative AI.
In this blog post, I will share best practices for responsible AI that emphasize fairness, transparency, accountability, and privacy—and the steps executives, board members, and leaders should consider for building responsibly as they adopt this exciting new technology and embark on innovation.
Responsible AI in the era of generative AI
Generative AI, with its increased power and growing accessibility, presents exciting opportunities for innovation, advancement, and the ability to achieve remarkable outcomes. However, these same exciting opportunities call for greater responsibility to better understand and address potential biases and harms. Just recently, AWS joined the White House, policymakers, technology organizations, and the AI community to advance the responsible and secure use of AI with voluntary commitments – recognizing the need to work together to develop future generative AI models safely and responsibly.
Responsible AI best practices are crucial in promoting the responsible, transparent, and accountable use of AI systems. As AI technologies continue to advance and permeate our lives, it is imperative to establish guidelines and frameworks that promote responsible AI adoption. These best practices should address the potential risks, biases, and societal impacts associated with AI while harnessing its transformative potential to benefit individuals, organizations, and society.
These nine responsible AI best practices extend beyond technical aspects and focus on the organizational and cultural dimensions of AI adoption. They emphasize the need for leadership commitment, cross-functional collaboration, and ongoing education and awareness programs to promote a culture of responsible AI within organizations.
Explore the nine responsible AI best practices.
About the author
Tom Godden is an Enterprise Strategist and Evangelist at Amazon Web Services (AWS). Prior to AWS, Tom was the Chief Information Officer for Foundation Medicine where he helped build the world’s leading, FDA regulated, cancer genomics diagnostic, research, and patient outcomes platform to improve outcomes and inform next-generation precision medicine. Previously, Tom held multiple senior technology leadership roles at Wolters Kluwer in Alphen aan den Rijn Netherlands and has over 17 years in the healthcare and life sciences industry. Tom has a Bachelor’s degree from Arizona State University.