Introduction
The field of Artificial Intelligence (AI) and Natural Language Processing (NLP) has fundamental problems since its start:
1. Intelligence and language are natural phenomena. Natural phenomena obey laws of nature. And laws of nature are investigated using fundamental science / basic research, while the field AI and NLP is researched using behavioral / cognitive science. A cognitive approach delivers a simulation of behavior. For example, a flight simulator, while a fundamental approach delivers an artificial implementation that obeys the involved natural laws. For example, an airplane;
2. A fundamental science has a foundation in nature, which leads to generic solutions. But due to its cognitive approach, the field of AI and NLP has no foundation in nature, nor a definition based on nature. Without foundation in nature, this field is baseless. And being baseless, this field is limited to the engineering of specific solutions to specific problems;
3. As a consequence, in knowledge technology, artificial structures are applied to keywords, while the natural structure of sentences is ignored. By ignoring the structure that is provided by nature, the field of NLP got stuck in the processing of “bags of keywords”, while scientists are unable, unwilling or forbidden to define the logical functions of even the most basic word types, as described in my scientific challenge;
4. Moreover, a science integrates its disciplines, while in the field of AI and NLP, scientists are unable, unwilling or forbidden to integrate (automated) reasoning and natural language. In other words, this field has a blind spot:
-
Chatbots, Virtual Assistants and Natural Language Generation (NLG) techniques are unable to reason logically. They are limited to select human-written sentences, in which they may fill-in keywords on the blanks;
-
Reasoners like Prolog are able to reason logically. But their output is limited to keywords, unable to express their results in automatically constructed sentences. As a consequence, laymen are unable to use this kind of reasoner;
-
Controlled Natural Language (CNL) reasoners are able to reason logically. And they are able to write their results as readable sentences, by which laymen are able to use this kind of reasoner. However, CNL reasoners – other than mine – are limited to sentences using verb “is/are” in the present tense. And they don’t implement for example conjunction “or”, related to the logical XOR (Exclusive OR) function.
