Ivory Tower Notes: The Methodology
Power users and builders need this: a practical reminder that rigorous methodology prevents wasted effort and bad decisions, especially when AI tools make it too easy to skip critical thinking and produce superficial analyses.
AI Summary
This article from Towards Data Science addresses the problem of AI-generated low-quality outputs ('AI slop') by introducing scientific methodology as a framework for rigorous data and AI projects. Using a practical example of ML platform consolidation, the author walks through the core scientific process—problem definition, hypothesis formation, testing, and conclusions—to demonstrate how to turn vague business questions into testable, measurable inquiries.
Excerpt
A short intro to scientific methodology to combat "prompt in, slop out" The post Ivory Tower Notes: The Methodology appeared first on Towards Data Science.
