If you get lost - please click away or look at the UI Cheat Sheet.
In general AI techniques offer great potential in searching, revising and reframing content. However the mathematics behind the implementation is one of averaging and popularity. In tricky situations, i.e those we describe as complex, progress often comes from the outliers - the different and the divergent - not from the consensus.
Nobel Prize Winner Albert Szent-Györgyi is noted for his comment that: "Discovery is simply seeing what everyone else has seen - but thinking what no-one else has thought."
In many situations you want to hear from all the differing options not just the majority view. The structure of this site preserves these essential differences.
Dive In
The best way to appreciate how all this works is just to dive in and play!
Learning About the Thinkers
For those with a familiarity with one of the leading thinkers (icon 🧑💻) in a topic start by validating the source materials - the QSets (icon 💬). These are summaries derived for different aspects of the authors writen works (click Voices ). You can click on a particular aspect - for example how the ideas can be used (click How-To) or the jargon used (click Keywords ). Together this gives an introduction to the level and accuracy of the summaries produced as the basis of the creative comparisons described next
Gregory Bateson
For example if you are familiar with the work of Gregory Bateson check the description of his work and the references used to form the QSet profile reference Voices and then see how he interrogates a topic reference How-To or see his work as a process chart reference Nutshell
These QSets are the stable basis on which further analysis is conducted, they capture each authors ideas expressed in a standard form, for example Gregory Bateson did not have a ‘methodology’ or produced process maps of his work. There is more detail on QSets here QSets - Perspectives in Practice
Getting creative
Once the often voluminous and eclectic ideas of the various authors are available as QSets these can be used for a set of questions to compare and contrast (icon 🎭). Whereas the prompts used to form the QSets are standardised and universal the prompts used in analysis are likely to be specific to the analyst and their grouping of authors.
Structured Prompts for Analysis
Some examples of the range (and style) of prompts and the information they produce from working with the QSets, .
Various Examples
- Synopsis
- Can you provide a historical list of all the prompts in this chat? Synopsis on Process Maps on Nutshell
- What are the likely results from the dialectic process and how can these be obtained? Results from the Dialectic Process on Gist
- Can you classify and structure the question and produce a smaller number of catch-all questions? Catch-all Questions on Gist
- Individual Comparisons
- How do the concepts of Roger James compare and draw from the others what is unique in his work? Concepts - Roger James on Keywords
- Group Comparison
- Can you provide a cross tabulation between the different authors and where their ideas are in conflict or in agreement? Cross-tab of the different approaches on What-is-complexity
- Contrasts
- Can you analyse the keywords and identify the structural polarities where concepts contradict or challenge each other (indicating the sources) and where they overlap? Concepts - Structural Polarities on Keywords
- Summaries
- Status report Status report on Gist
- Popularity (including semi-quantitative analysis)
- Can you analyse and structure all the questions into common themes including a quantification of the commonly asked aspects. if possible merge the long list into a shortened list of frequently asked questions? Common Themes - On Chaordic Conditions on Gist (A fuller set of prompts is available at Example Questions List and a shorter list of revealing prompts at 🤯Rogers WOW List)
A Bit of Fun (but learning too)
Take a look at the 🎭Styles section (click Persona ) to see the Voices making their case in the style of different personas. As well as for amusement it is interesting to see the different emphasis and use on material made in the different situations.
Example
Compare the tone and evidence of the - snake-oil salesman with the - academic or researcher.
Want to Learn More
The Implementation section (icon 🛠️) is (for me) the interesting bit but also the part which is most difficult to write (documentation!).
If you want to build you own system (from Open Source components) see Constructors Guide.
If you have the time or interest in the critical mechanism/technique of Semantic Normalisation and Content Levelling or in my musings About - Architecture
A must read is the section on Pollution (see Pollution - My special debt to Dave Snowden or how the initial choice of reference material to form the QSets can be easily contaminated by even small amounts of ‘buzz-word’ compatible material. It is a vivid demonstration of The Linguistic Torpedo