Stay updated with breaking news from Word Mover. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.
Any word embeddings, because they are trained on human input, will have biases. That’s true because no human is free from bias, so any machine learning model trained on that human input will have those biases. We must be aware of those biases in language processing.
This post explores how bias can creep into word embeddings like word2vec, and I thought it might make it more fun (for me, at least) if I analyze a model trained on what you, my readers...
Introduction - Let’s say FDA proposed a guidance document that would change the definition of “low cholesterol” for health claims. Now let’s say that when FDA finalized...