Our language is constantly changing. But what happens when our computers are stuck in the past?
as artificial as the name may imply — it’s largely based on the human brain.Millions of neurons run up and down the nervous system, through the flow of the spinal cord and nooks and crannies of the brain. These neurons move messages between locations, and they meet at synapses. Synapses transfer the messages between neurons by stimulating target neurons, the next step on a message’s journey.
It’s all remarkably human — too human even, because just like humans, NLP often falls victim to bias.In humans, auditory bias can come in many forms. For example, confirmation bias occurs when we only hear what weto hear, picking out details that validate what falls in line with our beliefs. Anchoring bias occurs when the first piece of information we hear changes how we perceive the rest of the information, like in bargaining when the starting price sets the stage for the rest of the deal.
” studied the accuracy of YouTube’s caption system, which runs on NLP, to assess the presence of bias in the captioning of English dialects. The study took advantage of a popular trend, known as the Accent Challenge, where individuals from different parts of the world read off a list of predetermined words— anything from “avocado” to “Halloween.