Communications of the ACM
Machine Learning Won't Solve Natural Language Understanding
Recognizing the technical difference between language understanding and mere language processing will show that data-driven and machine-learning approaches, while suitable for some NLP tasks, are not relevant to NLU.
It is time to rethink our approach to natural language understanding (NLU).
The 'big data' approach to NLU is not only psychologically, cognitively, and even computationally implausible, but is also theoretically and technically flawed. This pseudo-scientific method is a waste of time and resources, corrupting a generation of young scientists by luring them into thinking that language is just data—a path that will only lead to disappointments and hamper any real progress in NLU.
From The Gradient
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