HUDSON HOAGLAND 
mind from simple organisms to man and its survival value by 
natural selection. He continues: “‘What is the function of 
mind? Why did it evolve to increasing heights of intensity and 
importance? What is the biological value of the mental aspect 
of life in higher animals? It is now certain that natural selection 
through the differential reproduction of genetical variants is the 
essential agency of directional change in evolution. This being 
so, mind cannot be a useless epiphenomenon. It would not have 
evolved unless it had been of biological advantage in the struggle 
for survival. I would say that the mind-intensifying organization 
of animals’ brains, based on the information received from the 
sense-organs and operating through the machinery of inter- 
connected neurones, is of advantage for the simple reason that 
it gives a fuller awareness of both outer and inner situations; it 
therefore provides a better guidance for behaviour in the chaos 
and complexity of the situations with which animal organisms 
can be confronted. It endows the organism with better opera- 
tional efficiency.”’ 
Ideas about the nature of mechanism have changed from 
those of the nineteenth century. The principle of negative feed- 
back, whereby energy released from part of a system returns to 
regulate and control further energy release by the system, is the 
basic principle involved in cybernetic mechanisms. Examples 
include engine governors, the thermostat that regulates the 
heating of a house, and the guided missile that bounces its own 
radar waves back from the target and uses this feedback to 
regulate its steering and power to make it home on target. 
Computers have a remarkable complex of feedback processes 
including the utilization of information storage and its appro- 
priate retrieval, which corresponds in us to memory and recall. 
Purpose can be defined in terms of mechanisms controlled by 
negative feedback; purpose so defined is built into the guided 
missile and the computer and the thermostat, enabling these 
mechanisms to accomplish ends of varying degrees of complexity. 
Problem-solving computers can play a good game of chess, 
translate one language into another, and improve their capacity 
to discriminate as a result of past experience, i.e. to learn. 
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