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Why might a multi-layer theory of evolution be useful for skill engineering?

We break this into two questions. The first focuses on the problem of building believable theories and simulation models of skills. The second deals with the applicability of such theories and models for skill engineering, especially during the maturation period.

How might a multi-layer theory of evolution help us with a theory of skills?

The first benefit of this approach is that it might help in building models by starting with simpler skills used by species earlier in the chain of evolution. We can then move to more complex skills through normal accrual methods of evolution, i.e. software engineering can follow in the footpath of evolution by incrementing the functionality of skills.

The second benefit is that mechanisms for skills may well be layered, where the output or 'presentation' layer interfaces with action, but also calls on functions from other layers. For instance, computer applications may call on operating system functions. This layering of functions calls may reflect some aspects of the layering of evolution.

The third benefit is that the acquisition of mechanisms for skills is likely layered during the process of maturation and learning. This layering of maturation may well reflect the layering of evolution. In turn, the layering of the skill-in-use may reflect the layering of maturation and learning.

In summary, the multi-layer theory of evolution may help us develop a multi-layer theory of maturation which in turn helps us develop a multi-layer theory of skill-mechanisms.

How might a multi-layer theory of skills be useful for skill engineering?

This research project plans to look at evolution up to the beginning of language in the form of speech, and maybe go as far as stories, but stop short of writing and computers. To the extent that the process of maturation parallels the chain of evolution, that takes us roughly to 6 years of age. For overall skill learning that takes us only one quarter to one third of the way, i.e. eighteen to twenty four. For professional training it is an even smaller fraction.

On the other hand, to the extent that the functionality of skills acquired later is based and founded on the functionality of the earlier skills, the earliest skills may have a disproportunately large influence on the acquisition of later skills. At present educational approaches involve more back-loading in universities than front-loading in daycare and pre-schooling. The present value of the research may therefore consist in raising questions about skill-related experiences during the earliest phase of maturation.

The second benefit is that we can anticipate the evolution of skills for our skill engineering. Using this kind of model we can focus on changes in the skilled behaviour due to evolution-in-progress. For instance, we now have a lot of the world's knowledge on the internet. We can search for bits of knowledge with Google or other search engines. We now can access this knowledge via our smartphones. Soon we will get access via Google glasses. We conjecture that this will take us past speech and writing to a new level of knowledge processing. We can see a similar progression where we are shedding the limits of mathematics to go to more general computer-based data-structures and algorithms.