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<title>The Cash and the Calling LG #46</title>
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<H4>
"Linux Gazette...<I>making Linux just a little more fun!</I>"
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<center>
<H1><font color="maroon">The Cash and the Calling</font></H1>
<H4>By <a href="mailto:bmarshal@agt.net">Brian Marshall</a></H4>
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<P> <HR> <P>
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September 1999<br>
</b>
<p>
<blockquote><i>
This paper analyzes a model of software development in which
closed-source applications make use of open-source artificial
intelligence parts. We begin by observing that AI has a huge
potential but that problems limit the development of
applications. We consider why there will continue
to be closed-source AI applications and note that pure
open-source development is limited by the number of
people interested in starting open-source projects.
We consider the possibility of closed-source applications
based on open-source parts, both in a two-tier and a
three-tier architecture. We look at the pool of talent
available for open-source projects. We conclude that
the use of open-source AI parts may significantly
increase the development of AI applications and that this
may be good for the state of the art of AI.
</i></blockquote>
<p>
<hr>
<p>
<b>Table of Contents</b>
<ol>
<li>Introduction - Potential Applications of AI</li>
<li>Closed-Source and Open-Source</li>
<li>Two-Tier AI: Closed Application, Open AI</li>
<li>Three-Tier AI: Application, Problem-Domain, AI</li>
<li>The Pool of Talent</li>
<li>Conclusion - The Potential of Open-Source AI Parts</li>
<li>Bibliography and Acknowledgements</li>
</ol>
<p>
<hr>
<p>
<h4>1. Introduction - Potential Applications of AI</h4>
There seems to be more potential applications for artificial intelligence
than actual. The untapped market for staff-scheduling alone is immense.
The opportunities in the areas of materials scheduling, process
optimization, expert decision-making and image interpretation seem
endless. The development of AI applications would appear to be a field
with a lot of potential for growth.
<p>
Presumably there is money to be made satisfying some of this potential
demand. Why is this happening so slowly? Why are there so many
potential products that people would pay for but that have not been
developed?
<p>
There are a number of reasons why there are so many potential, as
opposed to actual, applications of artificial intelligence:
<ul>
<li>AI software is expensive and risky to develop. It tends to be
complex and subtle. It generally requires a large investment in
problem analysis. More AI software would be developed if it
were cheaper to do so.</li>
<p>
<li>AI applications tend to require a lot of support and they tend to
have a lot of future-risk. It is particularly difficult for a
tiny software venture to develop and market new AI software.
More AI applications would be developed if getting involved
with them was safer.</li>
<p>
<li>Some problems are sufficiently hard that no known AI technique is
completely satisfactory. More AI would be used if trying to do so
was more likely to be successful.</li>
</ul>
<p>
Artificial intelligence is limited by the expense and risk associated
with trying to take advantage of particular opportunities.
<p>
<h4>2. Closed-Source and Open-Source</h4>
<p>
There will probably always be opportunities to develop closed-source
AI software for rent. Companies identify potential applications, and
where there is sufficient expected demand, they develop new products.
This is expensive because of the amount of analysis and design required.
The development only occurs because rents are expected. The source
is closed to enable capture of those rents.
<p>
As we have noted, however, this sort of scenario is limited by the
expense and risk involved.
<p>
What about open-source? Free should mean less expense. Open-source
reduces future-risk. AI would definitely seem to be a good candidate
for peer-review. Eric Raymond describes these benefits and how they
come about in
<a href="http://www.tuxedo.org/~esr/writings/cathedral-bazaar/">
"The Cathedral and the Bazaar"</a>.
<p>
But each open-source project must be started by someone
who does the initial analysis, design and development. There are
a lot more potential AI projects than people interested in
starting them. Open-source application development isn't likely
to make a big dent in the pile of unexploited AI opportunities.
<p>
<h4>3. Two-Tier AI: Closed Application, Open AI</h4>
<p>
The expensive part of an AI application is not necessarily the AI.
There are a variety of artificial intelligence techniques, tools,
frameworks and engines available. The most expensive part of
developing an AI application can be the problem-analysis and the
design of how the AI is to be used.
<p>
It may well be reasonable for an application, based on expensive
analysis and design, to be closed-source. But what if the
application got its AI functionality from open-source AI parts?
A staff-scheduling system could be based on open-source AI
problem-solving parts. An image-recognition system could be based
on an open-source neural-network.
<p>
In <a href="http://www.tuxedo.org/~esr/writings/magic-cauldron/">
"The Magic Cauldron"</a>, Eric Raymond describes five discriminators
that "push towards open source". The first four discriminators
indicate that AI parts would be a good candidate for open-source:
<ul>
<li>Reliability is a major concern</li>
<li>Verification of design is difficult</li>
<li>AI applications can be critical to business processes</li>
<li>AI parts establish/enable a common computing infrastructure</li>
</ul>
<p>
The fifth discriminator, however, indicates the opposite. Artificial
intelligence is not part of "common engineering knowledge". It is
an area in which one would expect good proprietary techniques be able
to generate good rents.
<p>
In practice, this can be difficult. The customers for software parts
are developers of other software. Convincing a potential customer
of the worth of a secret technique can be a tough sell.
But more importantly, a company will not be interested in having its
product dependent on a secret technique that may not satisfy future
requirements.
<p>
Open-source software parts offer much less risk. They are easier to
judge, they tend to be more reliable and customers always have the
option of making their own changes.
<p>
<p>
<h4>4. Three-Tier AI: Application, Problem-Domain, AI</h4>
<p>
If open-source general-purpose AI parts are available, an interesting
new product is possible. People can use the general-purpose AI to
develop parts that are specific to a problem domain like
staff-scheduling or courier-dispatching.
This can make for a three-tier architecture -
<ul>
<li>The open-source, general-purpose AI parts</li>
<li>The problem-domain-specific AI parts</li>
<li>The application/interface</li>
</ul>
<p>
Much of the analysis and design goes into the middle tier - the
problem-domain-specific AI. It can be expensive to develop and the
market is much narrower than the market for general-purpose AI.
<p>
A middle-tier AI product might be developed by a company who will use
it to develop an application for sale. In this case, the middle-tier
would likely be closed-source.
<p>
A middle-tier AI product might be developed by a company or individual
with the intention of offering application development services to
narrow markets. The middle-tier might be closed to help capture the
market or open to help sell the service.
<p>
The three-tier architecture provides more ways to take advantage of
AI opportunities. The development of middle-tier AI products is
encouraged by the existence of open-source general-purpose AI parts.
<p>
<h4>5. The Pool of Talent</h4>
<p>
Many programmers are interested in AI. It's an intriguing field -
problem-solving, decision-making, remembering and recognizing...
it's the ultimate challenge - software that thinks.
<p>
The vast majority of these programmers never apply their talents to AI -
they have no opportunity in their jobs and they are not part of the
academic AI community. The Open-source phenomenon provides a number
of ways of tapping this pool of talent.
<p>
Programmers with a calling and/or a desire to make a name for themselves
will do original research, write new open-source software
and start open-source projects. Much unconventional thought will be
brought to bear on various problems in artificial intelligence. Many
thinkers will have a higher opinion of their thoughts than will
later prove to be justified (your present author probably included).
But the effect of the open-source movement on the state of the art of
AI may be the next great thing that happens in the world of computers.
<p>
Open-source projects need participants - people who contribute time
designing, developing, debugging and testing. The open-source culture
that supports this participation is described in Eric Raymond's paper,
<a href="http://www.tuxedo.org/~esr/writings/homesteading/">
"Homesteading the Noosphere"</a>. AI open-source projects should
be particularly good at attracting participants.
<p>
Open-source AI that is used in commercial products should
be particularly attractive to talent. There are a few reasons for this.
One is that the the AI has proven to be useful - it is something worth
working on. Another reason is that the work of the project is
obviously important and the project is therefore an excellent place to
make a name for oneself. A third reason is that money is involved,
there is the possibility of paying work and the possibility of getting
involved in new business ventures. Even people who aren't looking for
work like the idea of acquiring knowledge that can be worth money.
<p>
If a commercial product uses open-source AI, there is the potential
for paying work related to the AI. The product developer pays people to
initially make use of the AI and this use may have to be maintained.
Customers may require consulting, customization and integration
services. The product developer and large customers may fund
projects aimed at improving the open-source AI.
<p>
If money is being made on a commercial product that uses open-source
software, there will be people trying to dream up ways of getting in
on the action. People may start third-party consulting and integration
services. People may launch a venture to develop a competing product.
The possibility of acquiring an equity interest in some new venture
has its attractions.
<p>
<h4>6. Conclusion - The Potential of Open-Source AI Parts</h4>
<p>
Open-source AI parts may significantly increase the development of
commercial AI applications. Such development will become cheaper
and less risky. Small companies that would lack credibility as
developers or purveyors of closed-source AI could have adequate
credibility as users of open-source AI.
<p>
Open-source AI parts may also significantly increase the development
of home-grown AI applications. Many applications of AI in business
are so specific that they will not be developed at all unless they
are developed by, or at least for, an individual company for its own
use. Development that would be too expensive and risky with
closed-source AI products could be feasible with open-source AI.
<p>
As the open-source movement increases the application of AI, more time
and money will be directed at improving the AI. As the state of the
art of AI advances, more time and money will be directed at trying
to apply it.
<p>
The open-source movement could have important effects on the
application of AI.
<p>
<h4>7. Bibliography and Acknowledgements</h4>
<p>
<a href="http://www.tuxedo.org/~esr/writings/cathedral-bazaar/">
"The Cathedral and the Bazaar"</a> - Eric Raymond<br>
http://www.tuxedo.org/~esr/writings/cathedral-bazaar/
<p>
<a href="http://www.tuxedo.org/~esr/writings/homesteading/">
"Homesteading the Noosphere"</a> - Eric Raymond<br>
http://www.tuxedo.org/~esr/writings/homesteading/
<p>
<a href="http://www.tuxedo.org/~esr/writings/magic-cauldron/">
"The Magic Cauldron"</a> - Eric Raymond<br>
http://www.tuxedo.org/~esr/writings/magic-cauldron/
<p>
I owe much of my appreciation for the open-source movement to
the writings of Eric Raymond. There are many good things to read
at his <a href="http://www.tuxedo.org/~esr/">web-site</a>.
<p>
<a href="http://www.agt.net/public/bmarshal/homepage.htm">
Brian Marshall's Home Page</a>
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Copyright © 1999, Brian Marshall<BR>
Published in Issue 46 of <i>Linux Gazette</i>, October 1999</H5>
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