Read the passage and mark the letter A, B, C or D on your answer sheet to indicate the best answer to each of the following questions from 1...

Read the passage and mark the letter A, B, C or D on your answer sheet to indicate the best answer to each of the following questions from 1 to 10.

        Once administrative discretion is encoded in software, oversight morphs into what workers experience as the invisible supervisor: scores, prompts, and nudges orchestrating pace and priorities. Hiring funnels are pre-triaged, scheduling is optimized, and productivity dashboards adjudicate attention. [I] Proponents extol scalability and cost efficiency; detractors warn about opacity and mechanistic evaluations that occlude context. In either case, algorithmic management reframes managerial craft as data-intensive coordination, delegating routine judgments while standardizing procedures that previously relied on tacit knowledge and situational feel.

        At the shop-floor edge and in the gig economy, telemetry creates a panoptic vantage: routes logged, keystrokes sampled, deviations flagged in real time. [II] Platforms like ride-hailing or e-commerce warehouses exemplify how metrics orchestrate allocation, incentives, and even termination paperwork. This apparatus can amplify bias when training data embed inequities, and it can unsettle power dynamics by converting managerial discretion into automated triggers. Hence, regulators and standards bodies urge auditable models, meaningful explanation rights, and channels for contesting algorithmic determinations.

        Managers are not rendered obsolete; rather, their roles tilt toward sense-making, exception handling, and ethical arbitration. When metric targets dictate cadence, the space for human discretion narrows, unless organizations deliberately scaffold transparency, reversible decisions, and appeals. [III] New competencies surface: learning to interrogate dashboards instead of gut feelings; communicating limits and trade-offs; and convening cross-functional dialogue about fairness. Done well, augmentation elevates craft by letting humans focus on ambiguity and care; done poorly, it degrades morale and fuels quiet resistance.

        Pragmatic implementation starts small: co-design with frontline staff, pilot under watchful review, and run retrospective audits to recalibrate thresholds. [IV] Governance should specify accountability for harms, data minimization, and sunset clauses; moreover, hybrid oversight  –  a human-in-the-loop with authority to override  –  sustains legitimacy. Over time, institutions that balance efficiency with dignity tend to outperform, because trusted systems elicit candid feedback, richer data, and better adaptation. The lesson is simple: speed matters, but stewardship sustains durability.

(Adapted from Mohammad Hossein Jarrahi, Mareike Möhlmann, and Min Kyung Lee, “Algorithmic Management: The Role of AI in Managing Workforces,” MIT Sloan Management Review, 2023)

Question 1. According to paragraph 1, ______ orchestrate pace and priorities in algorithmic workflows?
A. randomized schedules ensuring equitable breaks and sufficient rest periods for everyone

B. managers walking the floor and adjusting tasks through conversation alone

C. scores, prompts, and nudges from the invisible supervisor control architecture

D. external auditors continuously monitoring every keystroke without managerial involvement