• Ira Glickstein's Knols (formerly Google Knols)

Recent Articles

Bayesian AI Advisor – Drill Here, Drill Now?

Bayes Theorem has practical applications. Use it to make real world decisions.

Bayes Theorem is not just an obscure artifact of the statistics of probability handed down to us from centuries ago. You can use it now to make decisions that will affect your financial well-being.

A relatively simple Excel-based tool helps you choose the right course of action in the face of uncertain probabilities and inexact test results. It is available for FREE.

Optimal Span

What is the most effective span for a hierarchical structure? For example, Management Span of Control is optimally between 6 and 7.

Most complex structures are compositional or control hierarchies. An example of a compositional hierarchy is written language. A word is composed of characters. A simple sentence is composed of words. A paragraph is composed of simple sentences, and so on. An example of a control hierarchy is a management structure, where a manager controls a number of foremen or team leaders, and they, in turn, control a number of workers.

Optimal Span Hypothesis:

Optimal Span is about the same, between five and nine, for virtually all complex structures that have been competitively selected.

That includes the products of Natural Selection (Darwinian evolution) and the products of Artificial Selection (Human inventions that competed for acceptance by human society).

The hypothesis is supported by empirical data from varied domains and a derivation from Shannon’s Information Theory and Smith and Morowitz’s concept of intricacy.

Ira G. Glickstein

Visionary Prophet (:^)

I’m a retired system engineer (IBM/Lockheed Martin) with my name on five patents in the area of artificial intelligence and a PhD in System Science. I currently teach an online graduate course in System Engineering at the University of Maryland. My wife and I live in Central Florida, about an hour and a half north of Disney World. Our children and grandchildren love to visit.