The hiring test is broken
Traditional coding interviews and behavioral panels were built for a world where the candidate worked alone. That world ended.
Research, data, and notes on hiring for AI literacy. Grounded in published work, and cited in full.
80+ sourced figures on AI adoption, demand for AI skills, and the value of AI literacy.
Announcements and short, data-tied notes on AI and hiring.
The research Acta is built on, and how it thinks about measurement.
Why hiring's broken, and why fixing it starts with what AI changed.
Traditional coding interviews and behavioral panels were built for a world where the candidate worked alone. That world ended.
Banning AI from the interview measures the absence of the job. Three years in, the data on what AI-free interviews actually predict is in, and it is bleak.
The academic backbone for measuring AI literacy at work.
AI literacy is not a single number. AICOS, the AI Competency Objective Scale, sets out the sub-competencies that constitute it, and how to measure each one without self-report.
A high overall AI score with a low calibrated-trust coefficient is the worst kind of hire. Acta reports calibrated trust separately because the radar can hide it.
What the numbers mean, and the case for measuring AI collaboration.