Researchers develop new way to help machine-generated language systems reduce toxic language
May 15, 2021 at 8:05 am
(AI2 Photo)
A young child’s ability to acquire language is nothing short of astonishing. But occasionally a toddler will pick up an inappropriate word, often with no comprehension of its meaning. Fortunately, with the right guidance, the child can be steered away from using the offensive term.
A similar situation can occur with natural language generation (NLG) in machine learning, even though the process is very different from how people use words. NLG systems like OpenAI’s GPT-3 language model are neural networks that have been pre-trained on a corpus an enormous collection of writings. Using deep learning methods, the model is used to automatically create human-like text from a simple input prompt. The results can be incredibly realistic and at times difficult to discern from something written by an actual person.