Measuring Intelligence
 

Ron Cottam, Willy Ranson & Roger Vounckx

Abstract
 

The concept of ‘intelligence’ has a long and varied history. Most recently it has been widely associated with the adaptive capability of a unified ‘system’ to deal with unexpected contexts. Unfortunately, a problem appears when we carefully examine the nature of a ‘system’, because it is clear that the unification of an artificial information-processing assembly into a ‘system’ is always performed through human intervention. A high-level ‘system’ always contains life, either through its own living nature or through the inclusion of human cognitive capabilities.

We suggest that a good metric for intelligence may be derived from the relationship between a quasi-autonomous information-processing assembly’s capabilities in dealing with unexpected contexts ‘on its own’ and the ‘help’ we must provide for it to succeed. To achieve this, we propose formulating the operation of a quasi-independent entity as a bidirectional communication channel. The entity must transmit to its human ‘assistant’ sufficient information about its current context (Ic) to enable the human to return sufficient help (Ih) for suitable contextual reaction.

We can define an ‘Apparent Intelligence’ for the entity as the simplest relationship between the two ‘players’ involved:

 
AI=Ic/Ih

This provides reasonable values for the Apparent Intelligence AI, ranging from zero (i.e. stupidity - if the human assistant has to do all the work) to infinity (i.e. genius - if human intervention is never required). The values of Ic and Ih may be derived from parametric descriptions of the information flows in the communication channel.

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