This episode focuses on how to use technology to move from paper-based policies and procedures to digitized governance. Digital governance allows progression from point-in-time manual reviews to continuous, real-time monitoring for fairness and bias.
AI governance is about AI being explainable, transparent, and ethical. Given the vast amount of data available to train algorithms, how do you determine which data is captured and reported, which measures are relevant, and ultimately, how a decision was made and what data attributes contributed to that decision?
During this podcast, Kelly Combs, Director of Emerging Technology at KPMG in the U.S., and Rohan Vaidyanathran, Manager of IBM Watson Open Scale, sat down with Samantha Gloede, a Managing Director in the firm’s U.S. Advisory practice, to discuss:
- how AI governance interacts and impacts everything around it, including business outcomes
- the prerequisites necessary to determine metrics that define key performance indicators and key risk indicators
- ways in which machine learning tooling and AI are rapidly evolving to integrate the touch points of the entire AI lifecycle
- why a “human element” remains a vital component in AI governance
- how tooling and dashboards can drive purposeful conversations with regulators and serve as evidence that “we’re doing what we say we’re doing.”