
Bias Starts Before the Interview
1 min read
A lot of bias arrives dressed as a sensible brief.
By the time a shortlist exists, the process has already made a series of quiet decisions about who will feel right. The role description has been written. Somebody has decided what gravitas sounds like. Somebody else has used "cultural fit" when they really mean "familiarity". A hiring manager has asked for a safe pair of hands, and nobody has stopped to ask, safe for whom?
I am spending more time than I expected looking at language.
That is partly because language does more than describe a role. It signals what a business rewards. It tells potential candidates whether difference will be welcomed or merely tolerated. It also tells you a great deal about the assumptions sitting inside the hiring team itself.
I saw this recently. A brief came across for a senior commercial role. Strong business case for broader thinking. A genuinely open sponsor. Real appetite for change. But the role description read like a portrait of the last person who held the job. Every requirement pointed backwards: specific sector tenure, a narrow band of previous titles, and language that rewarded familiarity over range. The best candidate in the market for that role would have been screened out by the document meant to find them.
That is not unusual. It is closer to the norm.
This is one reason I have become wary of how casually people talk about merit. Merit stops being a clean idea when the process underneath it is loaded.
Better technology helps. Better data helps. But so does simple discipline. Be explicit about what the role actually needs. Challenge lazy language early. Listen carefully to the words recruiters and hiring managers use, not just the candidates. Stop treating the brief as neutral when it so often carries the first layer of bias.
Most organisations do not intend to narrow the pool. They do it anyway, often before the first conversation has even happened.
Read the TechCrunch article →

James Nash
James is the founder of inBeta. He has spent fifteen years working with boards and senior leadership teams at global and publicly listed companies on succession, talent, capability, and leadership governance. He holds executive education from Saïd Business School, University of Oxford, in Artificial Intelligence (including Audit and Ethics), Executive Leadership, Strategic Innovation, and Executive Finance. He founded inBeta because he kept watching boards make their most important decisions on instinct, narrative, and incomplete information, and believed the evidence base existed to do it differently. James is a certified AI Auditor, AI Ethicist, and AI Professional (CAIA, CAIE, CAIP; Oxethica), and a certified practitioner in CliftonStrengths (Gallup), Hogan (including PBC 360), FIRO-B, and Cultural Intelligence (CQC).
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