CHATBOTS UNDER-HYPE: THE NEW FRONTIER TO SIMPLIFY COMPLEX KNOWLEDGE PART 2

Just as a reminder, Complex Knowledge is any combination of regulatory, statutory, legal, tax, tariff, policy and procedure matter, which is primarily found within documents.

USE CASE: HOUSEHOLDER PLANNING PERMISSION 

Setting the scene

The understandings from this particular use case are universal in terms of Complex Knowledge. The initial scene setting for this use case will be typically off-putting as the subject is so dry. However, it is important to persevere as this “current state” is more a reflection of the way Complex Knowledge is traditionally represented, which is a strong signal that a paradigm shift is needed.

The purpose of the use case is to understand the shift from the monologue of a document to the future state of using chatbot dialogue.    

The Monologue

The monologue nature of Complex Knowledge is so dry that generally its left to others to address. It is for this reason, deep rooted systemic risks apply across all public and private sectors. So here goes. The use case involved the Town and Country Planning (General Permitted Development) (England) Order 2015 and the accompanying Department for Communities and Local Government “Permitted Development Rights for Householders – Technical Guidelines”. These two documents consist of 215 pages is used by circa 360 Local Government Authorities.

The Scope

The use case involved a subset of the 215 pages, enabling a deep dive into targeted substance. The scope was limited to a householder or their representative seeking permission for a loft extension – a subject that is relatively easy to understand. The scope involved the following considerations:

1. Include terraced, semi-detached and detached properties
2. Exclude converted, flats / maisonettes and other buildings
3. Outcome 1: Planning Permission Required
4. Outcome 2: Planning Not Permitted
5. Outcome 3: Planning Permitted
6. Knowledge Driven (not data driven, no data integration)
7. Include analysis of the User Decision Journeys

Knowledge degradation at scale

In addition to the receipt of the 215 pages there was also a plethora of other documents provided in context to the scope sourced from one of the 360 Local Government Authorities. This include materials such as process diagrams, procedural documents and web content.  Again, no surprises as this type of documentation is needed for governance, controls, risk mitigation, compliance and meeting quality standards such as ISO.

A review of these additional materials showed they all contained missing knowledge from the 215 page ‘original source’.

Now let’s reflect for a moment. Complex Knowledge consisting of Choices, Pathways and Outcomes are algorithms. By missing out some of the knowledge that is part of the algorithm structure actually weakens the algorithmic structure. Obviously! Yet common sense is not common and in this case it is universally true.

It is for this reason that the additional materials provided were simply too dangerous to use. Therefore, the use case focused on the “original source” of the 215 pages.

It would be reasonable to assume that all 360 Local Government Authorities have reinvented the wheel by producing their own documentation, which has led to an amplification of costs, risks, lower productivity and a sub-optimum “citizen” service.

The lack of a usable “golden source” from the “original source” of national regulatory and statutory documents is knowledge degradation at scale, amplified by the network effect creating a negative socioeconomic impact.

This modus operandi is so pervasive that it has been hard-wired into individual and organisational  “sense-making” frameworks, negatively impacting the very way we work, especially knowledge intensive sectors such as government, health and financial services.

Arguably, this type of Complex Knowledge deterioration at scale is a major influence upon experiencing stagnant productivity since the 1980s, even though there has been a remarkable acceleration of technology advancement. 

Preparing the Complex Knowledge from Monologue to Dialogue

To be continued .. part 3