[Ailist] RE: Lean and AI

[Roger Davies]

All,

This is actually my second response to the question. My first is still un
sent because it lead me to this, shoter thought.

I believe that there are three major considerations.

1) The type of system being improved (e.g. Six Sigma is far more successful
when applied to linear, mechanical processes with limited human interaction)

2) The perspective of the person leading the project (e.g. if you have past
success with a given method and are comfortable with it you are more likely
to use that tool)

3) The context and environment in which the method is used. All improvements
are carried out within a 'culture' If that culture supports Six Sigma and
has not yet grasped Ai it may be very difficult to sustain an Ai
methodology.

I originally thought the choice would be a simple relationship between
methodology and degree of human interaction and type of problem. As I
continued my thinking I realized there was more than that. 

A great area of study. I'm sure it will reveal that successful, sustained
improvement requires more than one approach and more than one type of
personality that need to be applied simultaneously and not (as so often
happens) sequentially. The more I learn about Ai the more I understand why
it is important not to see it as a process or a method. Ultimately most of
my 'arguments' culmanate in the necessity for an holistic, humanistic
perspective being required for any orgnization to thrive.

Roger



-----Original Message-----
From: 'Marvin Faure' [mailto:marvin.faure at wanadoo.fr] 
Sent: Friday, December 14, 2007 3:18 AM
To: 'Siegel, Steve'; 'Roger Davies'; 'Kat Morgan'; 'Robyn
Stratton-Berkessel'
Cc: ailist at lists.business.utah.edu
Subject: RE: Lean and AI


Steve,

I was interested to see your post that you are doing research in AI and
problem-solving. 

It seems to me that the starting point for AI and for problem-solving is the
same: a situation that is at some level unsatisfactory. At one end of the
scale it is clearly a problem, at the other end it is an opportunity to do
or to "be" better (which is easily transformed into a problem to solve).

The two approaches diverge, of course, as soon as the starting point and
focus for the project have been identified. 

Taking a practical consultant's standpoint (at the risk of sounding
heretical) I think that while there are many situations where better results
will be obtained through AI, there are certain situations that might lend
themselves better either to "pure" problem-solving or to a blended approach
that uses tools from both. Optimising manufacturing processes may be one of
these areas.

It would be wonderful if you were able to set up some really rigorous
research to identify the conditions most favourable to each approach. I'm
not aware of any such research already out there but asking this list is
probably a good place to start!

I'd be very pleased to exchange ideas on this topic as you proceed with your
research.

Kind regards,

Marvin