Introduction To Machine Intelligence Measurement

How to measure machine intelligence seem to
be
in the fields of computer science, however, the
field is affected by interdisciplinary assumptions
from other disciplines such as social sciences and
biological (neuroscience) sciences. Machine
intelligence measurement would help technology
evaluators and policy makers assay the relevance of
machines that claim intelligence. The technical (T)
evaluators would focus on features that are of no
qualitative meaning to humans. Policy makers would
focus on whether a machine violated any regulation
(O)
during the course of the intelligent actions. End-
users would focus on subtle features parallel
to
human intelligence (P). Coupling T with O and P
with O measures
(using a new calculus) reveals the overall
intelligence. This book concerns consumers of
nduologic systems (intelligent artificial systems
and educational technologies). It shows the
diversity of measures of machine intelligence and
how to use the TOP model. It clarified the
significances of machine intelligence quotient (the
focus of this book) is quite different from those
of
machine intelligence.