雅思阅读

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The concept of 'digital twins' has garnered significant attention in urban planning, referring to virtual replicas of physical cities that integrate real-time data from sensors, infrastructure, and citizen behavior. These dynamic models allow planners to simulate scenarios such as traffic congestion, energy consumption, or flood responses before implementing costly changes in the real world. However, critics argue that reliance on digital twins may exacerbate existing inequalities, as data collection often prioritizes affluent areas with better sensor coverage, while marginalized communities remain underrepresented. Furthermore, the predictive accuracy of these models hinges on the quality and bias of the underlying algorithms, which can perpetuate flawed assumptions. Proponents counter that with transparent governance and inclusive data strategies, digital twins could democratize planning by enabling community feedback and iterative testing. Ultimately, the efficacy of such tools depends not merely on technological sophistication but on the ethical frameworks guiding their deployment.