The Algorithm Picked My Career. It Was Right. I Hate It

The aptitude test said I should leave teaching for data analysis. I fought it for a year. Then I did it, and I am good at it, and my life is objectively better, and I have never been so sure that something important was lost.

The test was part of a career service the government subsidized. It measured my skills, my temperament, my salary history, and the market. It was not wrong about any of the data. I was a fine teacher with mediocre pay and a temperament the test described as better suited to structured problem-solving.

I fought it. I loved teaching. I loved the kids, the chalk dust, the feeling of a room full of people getting it. I told the test it was wrong. The test, which has no ego, agreed that I was free to disregard its recommendation, and then it showed me the projections: stagnant pay, burnout risk, a skills gap growing in the market.

I did it. I trained. I got the job. The data analysis job pays almost twice as much. The hours are better. My back does not hurt. My friends say I look healthier. I am objectively, measurably better off, and I have stopped being able to say what I lost.

I know what I lost. I lost the chalk dust. I lost the Tuesday when a kid who never raised his hand raised it, and the answer was right, and the room cheered. The test did not account for that, because it cannot be accounted for, and I do not know how to argue with the numbers.

The test was right, and being right is the worst part. If it had been wrong, I could have gone back. It was right, and my life is better, and I am ungrateful, and I am grieving, and I have started taking the long way home from work, past the school, where the lights are on and someone else is teaching. I am good at my job. The numbers say so. The numbers are always right, and the numbers do not know what the chalk dust was worth.