This is the final part of a series The Talent Aperture, in which I explore why organisations demand adaptability—yet design hiring processes that reward rigidity.
Once upon a restructuring, someone in HR declared, "We've eliminated bias by removing names from Org charts and handing hiring over to the algorithm!" There was polite applause, a congratulatory pie chart was served, and nobody asked what, precisely, the algorithm had learned to value. Or from whom it had learnt its values.
Thus began the era of judgement by machine—a charming technological development in which Applicant Tracking Systems (ATS) now preside over recruitment like under qualified vicars, quietly screening out the heretics who failed to list previous job titles in bold type or dared to apply from a suburb not adjacent to the office.
These systems are pitched as neutral. But, what hiring systems are, in fact, is obedient. And their tutors are our historical biases—groomed, polished, deployed at scale, and, most troublingly, run away from the scrutiny of competent human oversight.
And this is the rub: algorithms don't make ethical decisions. They make predictions based on patterns. Whether those patterns reflect justice, growth, or the ghost of organisational prejudice past is none of their concern.
The only thing worse than being judged unfairly is not being judged at all—just quietly filtered into oblivion by a machine who thought your CV wasn't closely enough aligned with the role.
But the real mischief begins not with what these systems see, but with what they miss. The generalist who took a scenic route through three industries. The career-returner with humility, resilience, and just enough cheek to ask better questions. The young candidate with little pedigree but enviable judgment. All quietly cast into the abyss for failing to match 'must-haves' that nobody remembers asking for—or questioned when adding them to the recruitment brief.