Read the following passage carefully and answer the question that follows:
Recent administrative reforms in urban governance have increasingly relied on automated algorithmic systems to allocate municipal social welfare benefits and infrastructural maintenance funds. Proponents argue that algorithmic decision-making eliminates human bias, streamlines bureaucratic delays, and optimizes resource distribution based on objective data inputs. However, empirical assessments of these systems reveal a subtle structural paradox. Because the algorithms are calibrated using historical administrative data, they inherently internalize and perpetuate pre-existing socio-economic disparities. Furthermore, the opacity of complex predictive models deprives citizens of transparent recourse, as administrative officers frequently defer to algorithmic outputs without exercising discretionary evaluation. Consequently, while procedural speed improves, systemic inequities are formalised under the guise of technological neutrality. Crucially, where municipal frameworks mandate human oversight, administrative personnel often exhibit automation bias—accepting algorithmic recommendations uncritically to avoid procedural liability. Thus, the integration of algorithmic allocation without robust independent audit mechanisms does not eliminate administrative bias; rather, it codifies historical inequalities while insulating decision-makers from public accountability.
Based on the passage, which of the following statements can be strictly inferred regarding algorithmic allocation systems in municipal governance?
- AThe implementation of mandatory human oversight inherently guarantees that administrative personnel will override biased algorithmic recommendations.
- Algorithmic allocation systems can perpetuate historical socio-economic disparities while simultaneously diminishing the administrative accountability of decision-makers.Answer
- CMunicipalities should completely dismantle automated allocation systems and return entirely to manual bureaucratic evaluation.
- DAdministrative officers lack the technical training required to understand the mathematical foundations of predictive models.