AI (Artificial Intelligence) Governance: How To Get It Right AI (Artificial Intelligence) governance is about evaluating and monitoring algorithms for effectiveness, risk, bias, and ROI (Return On Investment). But there is a problem: Often not enough attention is paid to this part of the AI process. “AI projects are rarely coordinated across a company and data science teams are often isolated from application development,” said Mike Beckley, who is the CTO of Apprine. “And now regulators are starting to ask questions businesses don’t know how to answer.” Keep in mind that AI introduces unique problems. Training data is often flawed, such as errors, duplications, and even bias. Then there is the issue with model drift. This is when the AI degrades over time because the algorithms and data do not adequately reflect the changes in the real world. The result is that a company may make bad decisions or miss revenue opportunities. Even wor...
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