Responsible AI explained: 5 myths and realities
5 Myths and Realities on Responsible AI
Despite the exponential increase in the amount of AI and machine learning (ML) models in production, fewer companies than should have dedicated the time and effort to ensure these models are deployed responsibly.
Models that reproduce or amplify biases, automated processes that overlook unfair outcomes, and unexpected AI behavior all put these initiatives at risk. But even so, there is still no standard, accepted process for how to practice responsible AI.
Download this white paper to delve into five common myths about responsible AI to bring some clarity about what it does—and doesn’t—mean for your business today.