IBPS PO 2025 · Question 126 of 200

Who is the other person that visits the doctor in the same month as Karan?

1. AManoj
2. BOm
3. CSunitaCorrect
4. DPriya
5. ELeela Read the passage carefully and answer the questions that follow. Algorithmic hiring tools, once heralded as an antidote to human prejudice in recruitment, are now facing intensifying scrutiny for reproducing the very biases they were designed to eliminate. Proponents originally argued that software, unlike a fatigued or distracted interviewer, would evaluate every candidate against a fixed and impartial rubric, thereby stripping decisions of the subconscious associations that skew human judgment. Yet a growing body of research suggests that these systems, trained on historical hiring data, often inherit and even amplify the discriminatory patterns embedded in that data, effectively automating exclusion under a veneer of statistical objectivity. The difficulty is not merely technical but definitional: many of these tools are trained to identify candidates who resemble previously successful employees, a criterion that quietly encodes whatever demographic skew already existed in the workforce. If an organisation's past hires were overwhelmingly drawn from a narrow set of universities or backgrounds, the algorithm learns to treat that narrowness as a marker of merit, penalising equally capable candidates whose profiles simply look different on paper. Regulators in several jurisdictions have begun demanding audits of these systems, but auditing itself remains contested terrain. Vendors frequently resist disclosing the inner workings of proprietary models, citing competitive concerns, which leaves auditors to infer bias from outcomes rather than mechanisms. Some scholars contend that outcome-based audits are sufficient safeguards, since what ultimately matters is whether qualified candidates are being unfairly filtered out, regardless of the algorithm's internal logic. Others insist that without visibility into the underlying mechanism, organisations cannot reliably distinguish a genuinely fixed problem from one that has merely been disguised. What is rarely disputed is that algorithmic hiring, left unexamined, does not represent a neutral upgrade over human judgment; it represents a different, and sometimes more opaque, vector for the same old inequities to persist.