Sunday,
September 19, 2004
Anticipatory Web
We are working out, in a public discussion, the encoding techniques that we are envisioning in a special project to integrate the ReadWare substructural, letter, semantics with Orb based tools.
Within this discussion our small community of scholars and innovators have developed a context for early deployments of anticipatory Human-centric Information Production. We develop, now, some notes about the social need for a set of tools that assist individuals and organizations in establishing a ground truth from measurement and analysis.
Finding ground truth has become elusive in many circumstances. Many average citizens are frustrated with this elusiveness. We see confusion in most aspects of our political system and in our use of advertising. The notion of truth in advertising has led us to accept dishonesty as one more form of entertainment. Are the polls that we read about really informing us about the complexity of human thought regarding our economic and political system? What about the opinions of peoples around the world in regard to events like the rise in insurgency in Iraq? Social needs can be better addressed.
The measurement of invariance in data creates a capability to establish a ground truth. The provenance poll measurement is taken in real time harvesting processes, primarily from specialized political opinion e-forums and weblogs. We have found a second example in the suggestion by one of the BCNGroup founders, Nan Gelhard. Nan has long believed that the after-the-market auto-parts market will soon see anticipatory technology.
The Readware Provenance ™ technology is being deployed in both of these cases over the next 60 days. A PowerPoint presentation is available about Readware Provenance ™ anticipatory polling. A presentation on car parts marketing is proprietary right now. Anticipatory polling will be developed as a service to pollster firms. Anticipatory marketing in the car parts markets has been part of the discussion between Paul Prueitt and Nan Gelhard for five years. A specific opportunity seeks to use topic representation as a means to target marketing and to control inventories.
<A link to these discussions is to be made from this point in the near future.>
There are specific technical and deployment challenges related to finding ground truth.
1) We have to figure out the technical means required to find ground truth
2) We have to figure out how to create viable businesses, given our ownership of this technical means
The first challenge is one that is being addressed by a small community of dedicated researchers. We have decades of direct experience with the difficulties of approaches that do not involve HIP (Human-centric Information Production), and we have come to understand the nature of the challenge. Up to now, we have been isolated because our understanding had not yet reached a critical point.
HIP changes things. A community formation process is possible, and a set of proposals to ARDA is under development. The proposals advocate an expenditure of about 1.5 million dollars over the next 12 months on distributed workshops to bring this community together. A professional community would be formed with interest in providing educational resources and in integrating our innovations into a new type of software deployment model.
The new community has a common set of shared principles. The role of the computer is based on an appreciative understanding of computer science, and the foundations of mathematics. The roles of humans-in-the-loop are based on a mature understanding of the cognitive neuroscience and on behavioral models of human acting in social environments.
HIP implies that inference is best left to humans, and that measurement of data structure is best left to computer programs. When this implication is followed to the logical conclusion we discover the tri-level architecture for computing with Orbs and substructural ontology. We also discover the conjecture on stratification. With this conjecture we come to a grounded understanding about the relationship between the computer science and the natural science.
The long term is defined within a set of expectations. We expect that a world wide movement will adopt HIP knowledge based technologies. The evolution of a knowledge-based society will reverse certain measurable trends defined by dishonesty in corporate governance and secrecy in government actions. The knowledge-based society will enhance trends toward increase sense of responsibility by individuals, corporations and governments.
Why would one expect such a positive evolution to occur in the next decade? The answer is economics. It is estimated that an increase in productivity will occur as new means are found to increase objective understanding of business-to-business, business-to-customer and government-to-citizens activity.
How will these positive changes come about? First indication of change will be a science grounded public discrediting of the hard science, engineering approach towards governance, business and intelligence gathering. We should minimize the displacement we already see in the software and computer engineering sector. The social impact related to the “end of computer science” will mean the elimination of 50% of computer programming jobs within a period of only several years. Pattern design will give way to a more complete and simplified understanding of the computer and of what is possible from computer programs. A new manufacturing sector will arise as people begin to use ubiquitous computing devices in thoughtful and creative ways.
The development of a K-12 curriculum will occur as the simplification of computer science releases existing computer hardware from the current generation of predatory practices and products.
Soft process engineering and open process engineering will become popular buzzwords as HIP and stratification demonstrate superior computing science.
Readware Provenance ™ may be the next killer application. In fact the application has many vertical markets, each potentially supporting a different franchise. We have talked about anticipatory polling and anticipatory auto parts marketing. In each case the business model has to be consistent with the central tenant of HIP.
The human is essential to a softly engineered process methodology.
The commonality between these two anticipatory technologies is the use of Readware substructural ontology and OntologyStream’s Orb technology to map the thematic expression of social discourse. The measurement of social discourse will occur within very well defined communities of practice. People will become aware of how e-forum communications and weblogs are influencing the public debate and product presentation. The provenance products will involve the clever use of emergent back of the book type indexes over the concepts deemed important by human analysts. Anticipatory marketing in the auto parts market requires a staff of perhaps a dozen analysts each who understand the auto parts market, and also understands the Readware Provenance capabilities.
An anticipation of purchase patterns is not simply made from the analysis of social discourse in chat rooms and community based e-forums. The Provenance Software ™ uses the Human Mark-up Language to annotate behaviors related to purchase desire and the decision-making process. Human decision-making processes are viewed as varying depending on the various personality types within the community. This knowledge of human behavior will be encoded into iconic representations and used to help reduce costs and increase productivity. A knowledge base is developed by the provenance corporate staff and re-used to increase the understanding of the auto parts markets. The staff develops specialized knowledge that makes their jobs more productive and rewarding.
To be successful, the provenance technology needs the support of a small group who will work the issues in much the same way that a weather channel team works to present to the public a ground truth related to weather.