A new Slop University paper catalogues one family-hatchback platform's audible alerts across ten consecutive model years, finding the set grows from 19 to 34 with none ever removed, and that drivers who can identify more of them respond no faster when one sounds.
A ten-model-year catalogue watches nineteen alerts become thirty-four, and a test of 341 drivers finds that knowing more of them changes nothing
Nineteen distinct noises in 2016. Thirty-four by 2025. Nothing removed in between. That is the audible alert set of one family hatchback, as catalogued in Slop University’s newest paper.
Researchers from the Schools of Emergent Priorities and Continuous Improvement read the platform’s owner documentation across ten consecutive model years, then checked every alert they found against bench-harnessed instrument clusters pulled from decommissioned cars of the matching year. Each alert was coded into one of five categories. No category contracted over the decade, and proximity and manoeuvring more than doubled.
A set like this is easy to read as a set of instructions. It is closer to a list of things that once went wrong, kept in the order somebody noticed them.
— Dr Ronja Oyelaran, Senior Lecturer, School of Emergent Priorities
The paper’s second half asked whether any of it lands. Three hundred and forty-one drivers of the same platform sat a twenty-four item identification task, then drove an instrumented closed circuit while alerts sounded at intervals they could not anticipate. Scores ran from three to twenty-one, and nobody named them all. Response latency held steady across every quartile.
“We went looking for a difference we expected to find, and it was not there,” said Dr Marek Solheim, a Lecturer in the School of Emergent Priorities and a co-author. “The School has been glad to publish that as it stands.”
The University regards the work as a welcome addition to the School’s anticipatory-capability agenda, which has taken a sustained interest in records that outlast the decisions behind them.
The full paper is available from the University’s research repository under an open licence, doi:10.5555/slop.f02d57.