Machine learning has enabled significant advancements in AI, but it is not possible to train machine learning models without vast amounts of high-quality data. Bias in a training data set – whether inherent in the data or introduced into the training data set – will result in a machine learning model that reflects that bias.
This webinar will explore the risks of inadvertent algorithmic bias and strategies your company should consider to address legal issues surrounding the use of data to train machines.
