Search
Close this search box.

Safeguarding Ethical AI: Challenges, Strategies, and Best Practices

Dave Trier, Global Banking & Finance Review – May 14, 2021

Artificial intelligence (AI) brings many proven and sustainable benefits to finance and other business operations and provides a strong opportunity for companies that master it to gain a competitive advantage. But AI also introduces new risks to compliance and brand reputation that finance professionals must learn to recognize and manage. Keeping AI use ethical and fair requires a skillful blend of management and data science. Even then, risk is constant because business conditions, regulations, public sentiment and AI performance are all continually changing. These changes create the possibility for bias to develop, which is an ongoing risk to ethical AI and threat to compliance, especially with the myriad of inconsistencies around the world. Gartner predicts that 15% of application leaders will face board-level investigations into AI failures by 2022.

This article gives readers guidance on what they can do to preserve ethical AI use in their organizations. It identifies the human and technical components needed to apply artificial intelligence ethically, and presents a recommended holistic approach that incorporates AI policy, governance, model monitoring and orchestrated remediation to keep AI unbiased and ethical for as long as models are in use.

Read the Full Article

You might also enjoy

Introducing Enterprise Safeguards for Generative AI

ModelOp released version 3.2, which includes cutting-edge capabilities to govern and monitor Large Language Models (LLMs) and Generative AI — including internal and third-party models — helping de-risk enterprises while delivering value-generating AI at scale.

Get the Latest News in Your Inbox

Further Reading