Scientific and technical work is always shaped by underlying paradigms — frameworks that define what counts as valid knowledge, evidence, and success.
In AI evaluation, these paradigms risk becoming self-reinforcing: models are trained and assessed within the same conceptual loops.
This post introduces the idea of paradigmatic closure — how reasoning itself can become trapped within its own assumptions — and outlines the idea for an experimental method, Conventional Paradigm Testing (CPT), designed to surface such blind spots.
The tests are educational, not validated: they aim to make hidden assumptions visible rather than to produce quantitative results.
Epistemic status: Exploratory. Early-stage conceptual work; low confidence in specific formulations but moderate confidence in the general problem framing.
How can I persuade him to stop these thoughts?
I am trying to think of, what a helpful comment in your situation woud be. I noted the way you phrased, what seems to be your key objective -"to persuade him to stop these thoughts". First of all I think it would be better to try to convince him, because this will probably longer lasting effects, than mere persuasion. Also "stopping these thoughts" seems also a difficult, if not impossible task. After all, we don't really control our thoughts as such - they come up from we don't know where, even though it is possible to train our cultivate certain though patterns and cognitive... (read more)