Where automation breaks recruiter judgment
The study reveals a phenomenon known as "algorithm aversion." Even when algorithms perform well, people are quicker to lose trust in them after a mistake compared to a human making the same mistake.1
Governance pressures around auditing and explainability further reinforce why human judgment remains central in high-stakes decisions.2
Recruiter lens: optimizing only for a score can miss the trust signals that humans look for. The end user is a person who values consistency, narrative, and credibility.
Trust is Fragile
Recruiter lens: manipulation signals are hard to recover from once trust is lost.
Definition: algorithm aversion
Algorithm aversion is the tendency to reject algorithmic recommendations after observing errors, even when the algorithm performs well on average.1