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The concept of 'digital twins' has gained significant traction in urban planning, referring to virtual replicas of physical cities that simulate real-time data from sensors, traffic systems, and infrastructure. Proponents argue that these models enable predictive analysis, allowing planners to test scenarios such as flood responses or population growth without disrupting actual operations. However, critics caution that over-reliance on simulations may overlook socio-economic inequalities embedded in the underlying data, leading to biased outcomes. Furthermore, the high cost of implementation and data privacy concerns pose substantial barriers, particularly for developing regions. Despite these challenges, digital twins represent a paradigm shift towards data-driven governance, though their efficacy hinges on transparent algorithms and inclusive stakeholder engagement.