View from an Inter-Disciplinarian

“There’s not one discipline I’m good at!”


Introducing Stefan Tax, inter-disciplinarian.


Research background became consulting years, then;

“A few years ago I decided to specialise as inter-disciplinary.”


“My strength is conceptualising, in visualising.”

“Lots of confusion, different models, different languages.”

“We want a model to work across all disciplines.”


A methodology with data alone misses crucial information: “Evidence based interventions are vital, but you also need the expert view.”


“The heuristic view.” A heuristic is basically human programming.

Experiencing things trains our ‘algorithms’: new information mapped against existing patterns. In a way, Stefan reverse engineers human ‘models’, for cross-methodology fit.


“Information flows between roles…from social sciences to software engineering.”

“It works!”

“I have this abstract structure and I look for the words used in each discipline.”


It’s meta research: he’s looking to incorporate Machine Learning into it.

Any takers?


“I don’t want to tackle commercial problems, but real societal problems.”


“Maybe climate and aid. When people start moving, you need to integrate data from many sources – not very reliable, merge them into one ‘picture’.”


“Get food to areas before it's needed.”

“Something like that.”

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