Today's artificial intelligence models are revolutionary — reshaping industries by automating complex business decisions previously left for experts. Success with AI, as many now know, is predicated on data. So, what happens when the data we feed our AI models is inherently biased?
Join WWT Data Scientist Charlene Ulrich and Big Data Consultant Daniel Cholakov as they talk about the growing need for leaders to scrutinize AI and natural language processing (NLP) models for bias. Charlene and Daniel use a recent WWT Research paper on mitigating bias in AI using debias-GAN as a jumping off point for a conversation that includes why de-biasing AI is important, where and how bias can take place and how you can use our findings to to improve your AI strategies.
Learn more about WWT Research, which includes comprehensive research guides and videos, at wwt.com.
