The concept of 'digital twins' has gained traction in urban planning, referring to virtual replicas of physical cities that simulate real-time data to optimize infrastructure. However, critics argue that reliance on such models may exacerbate inequality, as data collection often prioritizes affluent districts, leaving marginalized communities underrepresented. A study by Chen et al. (2023) found that predictive algorithms in digital twins tend to reinforce existing spatial biases unless explicitly calibrated with socio-economic variables. Proponents counter that these tools enable proactive maintenance, reducing costs and environmental impact. Yet, the ethical dilemma persists: who decides which data are relevant, and how can transparency be ensured when proprietary systems govern public spaces? Ultimately, the success of digital twins hinges not on technological sophistication but on inclusive governance frameworks that mandate equitable data representation and community oversight.