A clarification of misconceptions, myths and desired status of artificial intelligence
It tackles foundational conceptual issues in AI for researchers and practitioners, but is incremental as it builds on existing discussions without introducing new methods or data.
The paper addresses the lack of formal definitions for 'intelligence' and AI goals, which causes confusion in comparing AI to other fields, and presents a perspective to clarify misconceptions and myths about AI's status.
The field artificial intelligence (AI) has been founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed though various stages of popularity and received recently a revival in the form of deep neural networks. Some problems of AI are that so far neither 'intelligence' nor the goals of AI are formally defined causing confusion when comparing AI to other fields. In this paper, we present a perspective on the desired and current status of AI in relation to machine learning and statistics and clarify common misconceptions and myths. Our discussion is intended to uncurtain the veil of vagueness surrounding AI to see its true countenance.