The proceedings (edited by Ben Goertzel and Pei Wang) from our 2006
AGI Workshop (sponsored by Novamente) has been published. You can purchase
the book or check for the individual papers at the Workshop’s website.
This book contains materials that come out of the
Artificial General Intelligence Research Institute (AGIRI) Workshop,
held in May 20-21, 2006 at Washington DC. The theme of the workshop is
“Transitioning from Narrow AI to Artificial General Intelligence.”
In this introductory chapter, we will clarify the notion of
“Artificial General Intelligence”, briefly survey the past and present
situation of the field, analyze and refute some common objections and
doubts regarding this area of research, and discuss what we believe
needs to be addressed by the field as a whole in the near future.
Finally, we will briefly summarize the contents of the other chapters
in this collection.
1. What is meant by “AGI”
“Artificial General Intelligence”, AGI for short, is a term
adopted
by some researchers to refer to their research field. Though not a
precisely defined technical term, the term is used to stress the
“general” nature of the desired capabilities of the systems being
researched — as compared to the bulk of mainstream Artificial
Intelligence (AI) work, which focuses on systems with very specialized
“intelligent” capabilities. While most existing AI projects aim at a
certain aspect or application of intelligence, an AGI project aims at
“intelligence” as a whole, which has many aspects, and can be used in
various situations. There is a loose relationship between “general
intelligence” as meant in the term AGI and the notion of “g-factor” in
psychology [1]: the g-factor is an attempt to measure general
intelligence, intelligence across various domains, in humans.
