First-school/second-school controversy

 

23 January 2007

 

Appendix to the Resilience Project’s White Paper [1]

 

 

 

One of the core problems in the first-school/second-school controversy is that the founders of the second school make a claim.  The claim is that the first school used status quo to inhibit the development of a competing alternative paradigm to artificial intelligence.  How this was done, and what are all of the long term consequences will be a subject of historians’ work.  From the current vantage the notion that business, and information sector business in particular, has not served the public interest optimally is a notion that is still very novel.  The notion that market forces always work to advance our social values should be regarded as a hypothesis and not a religious principle.  In the current case, the second school claims that market forces re-enforced a poor evolutionary path for modern information technology development and design.  These market forces achieved the current outcome when consumers and suppliers became the same community. 

 

Based on a set of observations, the federal funding decisions over the past thirty years produced a compounding of the error of reductionism. [2] In the first school, intelligence is defined to be a process that has a precise model, located in a specific way. This school is best exemplified by the academic discipline of artificial intelligence where the goal has been to create a replacement for human intelligence.  The current Semantic Web activity has the related goal of producing ontological models, formal models driving computational machines, of natural social complexity.  According to the first school paradigm, systems that are naturally intelligent always use a model to express intention. The more fully a precise model is used, the more intelligent the behavior of the system.   In the Semantic Web activities it is asserted that this model must be produced using the Resource Description Framework standard equipped with an ontology inference layer. [3]

 

How can the great majority of federal funding go towards supporting a paradigm that is in clear opposition to recent developments in natural science?  Our answer is simple and direct.  The basis for asserting the W3C’s definition of the foundation of human knowledge representation is made to develop lines of business.  We claim that these lines of businesses developed without adequate exploration of what types of system properties might be expected when capitalism works without any form of moderating influence. 

 

Important cultural concepts do not consider the formal model to be to the perfect expression of human intelligence.  For example, we see in sports a clear recognition that the best performances occur without a pre-fixed model, and that agility develops when the behavioural expression is allowed to fix the pragmatics of situations in real time.  The natural science contains a great deal of evidence that model building is not the ultimate expression of intelligence; that the there are other elements including a real time perception-action cycle that measures reality and makes real time assessments about consequences of actions.  These measurements drive learning.  Learning does not lead to a precise model that is held onto dogmatically. 

 

Of course, paradoxically the presence of model building activity is vital also.  The point, beyond the paradox, has to do with the origin of the design of that model.  If the user is not designing the model, then the model can be usurped by business simply to increase economic value to the line of business.  Precisely this is what historians will record.  The IT sector became its own costumer, and the normal evolution of a marketplace became blocked. 

 

Model building behavior is clearly important, but is it essential to natural intelligence?  The science is still out.  Business, particularly, information technology and entertainment business over the last half of the last century, have acted as if there is no principled issue that natural science might bring up in opposition to what has been done by the information industry.  The principled issue is the issue of perceptual measurement and human awareness.

 

In an environment where models are built out of software and then owned, the clear danger is that participants in business activities will not engage fully in using the model because the question of ownership has already been established.  The issue is not one of mere preferences but rather one of mechanism.  Ownership and creativity go hand in hand.  Consistent with the first school thinking, individual participation is placed under the thumb of Weberian bureaucracy. [4] We see this with software systems designed to govern administrative and financial services, such as the software developed by the OMB’s e-Gov project.

 

The technical issue compounds legal/social issues.  Current information technology is clearly confused about the difference, observed by natural science, in nature between deductive and inductive inference; and more generally about the neuro-cognitive-quantum reality underlying how human brain systems supports action and perception.  However, this confusion has consequences when coupled by the self-centeredness of industry.  History will see the first school as having been shaped by its subservient role to business interests.  The conflict between businesses’ needs to own and the current needs of science to communicate was subjected to business interests.  These interests have shown a willingness of ignore key aspects to the nature of human communication.  Due to federal funding mechanisms, academic computer science is developed to support an ever increasingly powerful professional computer science, not to focus on the issues of human communication. 

 

Science should deal with the actual nature of reality rather then the imposed assertions, by business processes, which limit science to the production of ownership.  Science must trump business.  Currently business is represented as “living in reality” whereas scholarship is represented as bad for business.  As in other debates, like the debate over global warming, the role of the government is required to shift away from the support of a specific economic sector.  The American democracy is a government by and for the People, not a government by and for the corporate interests. 

 

The Resilience Project will start up by increasing the collective value of our common cultural heritage, demonstrating higher value from natural science due to the separation of business interests and basic science.  Positive value from the natural sciences will not be blocked from public view so that narrow business interests can impose yet one more layer of ownership and un-necessary costs.  National interests in an increasingly competitive world social structure is served by increased transparency. 

 

The Resilience Project may be the instrument through which the American people will balance what is out of balance in our economic, social and environmental systems.  Honesty will be returned to science.  The infrastructure supporting human communication and knowledge sharing will be placed on a responsible footing. 

 

Software ownership is not producing the best tools for our modern world.  One can image easily a world in which ownership of algorithms did in fact drive innovation towards a better kind of computer science.  However, this is not the world we live in.  In our world, the drive to own is coupled with legalized deception, as well as with the confusion that developed at the heart of computer science over the notion of complexity. 

 

Who owns the knowledge gained when an individual human interacts with models of reality?  If the human perceiving the model interprets the model, does not that individual human enjoy some rights of ownership due to individual creativity as part of the act of ownership?  The mechanics of perception involve creative private intentionality.  By blindly allowing business interest to “own” models one truncates the pragmatics that is added in the moment.  The greatest power of human intelligence is blocked at the very point

 

The core principle of the second school is that categorical meaning arises in the moment by an interpretative act of an individual.  This interpretation involves human intentionality.  Natural science suggests that an in “induction” of categorical meanings, always, occurs as part of conscious experience and this experience occurs in the present moment in real time.  The interpretation becomes “owned” in that moment.  If new aspects of ownership are not allowed, by non-disclosure agreements and patents on software, the process of interpretation breaks down.  The process of innovation is warped by undue burdens on human communication.  In this circumstance, it is quite natural that the local economic aspects become the controlling factor in what is reported and what is funded. 

 

The asserted ownership of innovations in the design of software may have acted against the public interest, by bringing to the market those things that are asserted to be owned, while inhibiting the development of collaborative tools and tools that facilitate several aspects of natural human communication.  The history of the e-Gov project provides the perfect setting to examine the role of software ownership. [5]



[1] White Paper, Resilience Project URL:

http://www.ontologystream.com/beads/nationalDebate/ResilienceProjectWhitePaper.htm

[2] We are referring to the paradigm that asserts that all causality is local and that these local reactions can be completely reduced to Newtonian mechanics. 

[3] This is the so called W3C’s OWL (Ontology Web Language) standard

[4] See footnote #9, in the Resilience Project’s White Paper on Max Weber’s viewpoint.

URL: http://www.ontologystream.com/beads/nationalDebate/ResilienceProjectWhitePaper.htm#_ftn9

[5] Fountain, Jane E. (2004) “ Prospects for the Virtual State:  National Center for Digital Government

URL: http://www.j.u-tokyo.ac.jp/coeps/040710.pdf