Unlocking the Potential of Responsible AI in the Era of Generative Technologies

• Validity and reliability
• Safety
• Security and resilience
• Accountability and transparency
• Explainability and interpretability
• Privacy
• Fairness with reduced bias

To explore how businesses are embracing responsible AI, MIT Technology Review Insights spoke with 250 leaders. The results showed that a large majority, 87%, see responsible AI as a significant priority for their organizations.

In fact, 76% believe that focusing on responsible AI could give them a competitive edge. However, only 15% felt fully prepared to implement these practices effectively. This gap indicates that while the importance of responsible AI is recognized, action often lags behind.

Implementing responsible AI in today’s generative landscape involves several best practices. Companies can start by cataloging their AI models and data. They should also set up governance measures. Regular assessments, testing, and audits can help manage risks and ensure compliance. Additionally, training employees and making responsible AI a leadership focus is crucial for lasting change.

As Steven Hall, chief AI officer at ISG, puts it, “AI represents a significant shift in technology, yet there is a disconnect. Everyone wants strong governance, but the resources and structure for responsible AI are lacking.” This highlights the need for better investment in responsible AI practices.

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.