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AI and NLP – a fundamental approach

(the downfall of the evolution theory as the assumed origin of intelligence and language)

Download the fundamental document (updated: February 8, 2016):
AI and NLP – a fundamental approach.pdf


Introduction

Around the year 1956, the field of Artificial Intelligence (AI) and knowledge technology was started. However, there are four reasons to believe that the current approach to AI and knowledge technology has a fundamental problem:

1. Intelligence and language are natural phenomena. Natural phenomena obey laws of nature. And laws of nature are investigated using (basic or) fundamental science, while the field AI and knowledge technology is researched using (behavioral or) cognitive science. This cognitive approach delivers a simulation of behavior, while a fundamental approach would deliver an artificial implementation of natural intelligence.

To illustrate: The current approach to AI and knowledge technology delivers a flight simulator (user experience) rather than an airplane (transportation). A flight simulator moves pixels on a screen and the cones of the speakers. But it doesn't leave the room, because it doesn't obey the laws of physics regarding to aviation. In the same way, the current (cognitive) approach to AI and knowledge technology will never “leave the room”, because it doesn't obey the laws of nature regarding to intelligence;

2. In addition, a science has a foundation in nature, which leads to generic solutions. But even 60 years after its start, the field of AI and knowledge technology has no foundation in nature, nor a definition based on nature. So, this field is baseless, left to engineer specific solutions to specific problems. It is engineering rather than a science;

3. Knowledge technology is based on applying smart algorithms to keywords, by which the natural meaning of non-keywords is ignored. Non-keywords provide information to our brain about the structure of the sentence. By ignoring the self-organizing function of non-keywords in knowledge technology, this field got stuck with "bags of keywords" and unstructured texts.

4. A science integrates its disciplines. However, the field of AI and knowledge technology fails to integrate (automated) reasoning and natural language. In other words, this field has a blind spot:
• Reasoners (like Prolog) are able to reason, but their results – derived knowledge – can't be expressed in readable and automatically constructed sentences;
• Chatbots and Virtual (Personal) Assistants may well produce understandable sentences, but they are unable to reason logically. Moreover, they are only able to select a human-written sentence in which they fill-in a user-written keyword;
• Controlled Natural Language (CNL) reasoners are limited to sentences with verb “is”, and don't accept words like definite article “the”, conjunction “or”, possessive verb “has/have” and past tense verbs “was/were” and “had”.