Implicit bias draws on associations people absorb over time about gender, ethnicity, age, disability, class, accent and much else. In hiring, it can show up as warmer reactions to candidates who seem familiar, harsher readings of employment gaps for some groups, or assumptions about who suits a role. Because the assessor is not aware of it, good intentions alone do not prevent it.
Training raises awareness, but process changes tend to do more to limit implicit bias in hiring decisions. Structured interviews with the same questions for every candidate, scoring rubrics with clear anchors, removing irrelevant details from early screening and monitoring outcomes by group all reduce the room for unconscious judgement. Automated tools need the same scrutiny, since they can learn patterns from biased historical data.