Don't let your annotation project bury you. Whether you call it "content analysis," "textual data labeling," "hand-coding," or "tagging," a lot more researchers and data science teams are starting up annotation projects these days. Many want human judgment labeled onto text so they train AI (via supervised machine learning approaches). Others have tried automated text analysis and found it wanting. Now they're looking for ways to label text that aren't so hard to interpret and explain.

Your customers have specific experiences with your products and services, and they describe them in their own ways. No chatbot is going to understand your customers' concerns right out of the box. With TagWorks, hundreds of thousands of customer interactions can be intricately analyzed in only a few months. Then, you'll be able to train your chatbot so it can actually understand your customers and guide them to success, get started today.

If robots can do backflips and cars can nearly drive themselves, why can't Siri and Alexa carry their side of a simple conversation? And how come there's no artificial intelligence (AI) able to read through all of our news and policy discussions to solve our social and economic problems? The answer is simpler than you might think. As it happens, human languages create very noisy data. Our ambiguous words, metaphors, and idioms make for beautiful poetry, but computers were built to compute math and logic on unambiguous numbers and categories.