Who Decides‪?‬

The choices that shape your life rarely look like decisions.

They arrive as defaults, suggestions, rankings, and scores. A model screens the applicants before anyone reads a resume. A score sets the interest rate. A dashboard gets trusted more than the people who watched the work happen. One small handoff at a time, judgment moves from people to systems, and most of the time nobody notices.

In Detroit, a face match put the wrong man in a cell. In Hong Kong, a video call full of deepfakes moved twenty-five million dollars. Behind failures like these, Kevin Hanegan keeps finding the same pattern. He calls it the Proxy Trap. You cannot measure what you actually care about, so you count something that stands in for it, and the two quietly drift apart. The gap between them is where the harm lives.

Who Decides? asks for neither fear nor faith. It is a field guide to calibration. Which decisions belong to the machine, which belong to you, and where the two need to check each other. At its center is the Automation Trust Check, five questions to run before you let a system decide, simple enough to use in a meeting.

Technology can make you faster. It cannot make you responsible. That obligation stays human.

Kevin Hanegan is a data literacy expert who helps organizations decide how much to trust their machines. Rather than building AI systems, he works with the leaders responsible for deciding when those systems should be trusted, challenged, or overruled. He is the founder of DataIntoWisdom.com and the author of Turning Data Into Wisdom, Data Literacy in Practice (co-authored with Angelika Klidas), and the Data Literacy Fundamentals series.