Different voices are all ‘normalised’ through answering the same query with a common meaning, although that interpretation may be idiosyncratic ( a Research-Project would be a representation of the degree of confidence/uncertainty)
It provides adjustment for stylistic and presentational differences - such as the loud voice in the room or the communicator by sound bite (Alan Kay) or those sympathetic to or attuned with the question (for example if the question is structure with questions will resonate with writers who naturally use an interrogative tone).
"You can know the name of a bird in all the languages of the world, but when you’re finished, you’ll know absolutely nothing whatever about the bird. So let’s look at the bird and see what it’s doing – that’s what counts. I learned very early the difference between knowing the name of something and knowing something."
Richard Feynman
The challenge in studying Systems Thinking is that so much of the content is trapped in jargon which itself is a matter of fashion. Old books contain ideas and concepts which are valuable today but the language, terminology and style of writing hides meaning. Feynman’s observation is born out - you might recognise the language of cybernetics but struggle with the meaning. AI provides an essential levelling of all the material by allowing a modern essentially synonym expansion in locating content.
When a question is asked which relies on meaning communicated through language - for example Systems Thinking - this relies on the understanding by the ‘person’ of course there is no person here and the author may not have specifically used Systems Thinking in their material. The AI helps to mitigate this challenge by essentially (through term association) projecting the gist of the writing onto a mesh of ordinary language - this provides a source and jargon independent understanding.
The choice of source material for the QSets is mine and relates to my interest in their work and access to specific books and papers. Should the system be adopted by, say, a professional society individual authors may select or choose their oeuvre depending on preference or currency (recency). My observation is that in many ways the old material is as relevant and often is preferable (insofar as it gives a less polished but more honest description of the approach in practice).
Attribution & Authorship
Authorship - do we not mention Oracle (database for data) or Microsoft (Word for formatting) as authors even though they are involved, my use here is as a interface layer to the oeuvre of the authors, it is a semantic definition allowing fuzzy matching (where the fuzzy is language synonym based).
The creative part of STPrism is the structure the composition of queries (or questions) and their juxtaposition - it is like the distinction between notes and music. The instrument - here AI - makes the sound but the composer - here the QSets - makes the music.