Artificial intelligence in LDTs poses a significant challenge as it holds the potential to either reinforce existing social biases or drive positive change. The problem lies in AI’s reliance on data and algorithms, which may lead to disparities and a lack of transparency in urban planning decisions if not managed ethically and responsibly. To address these challenges, the proposed approach involves implementing ethical guidelines for AI usage, focusing on transparency, fairness, and accountability. This approach mandates inclusive participation and the involvement of diverse social groups and feedback loops – human oversight mechanisms should be in place to ensure AI systems support equitable urban development. This MLU introduces approaches of ethical implementation of AI in LDTs by exploring case studies of poor AI application and best practices for responsible AI deployment. Topics include understanding algorithm-based biases, fostering transparency and accountability in AI systems, and the significance of inclusive urban planning. The MLU aims to equip individuals with knowledge to make informed, ethical decisions regarding AI’s integration into city planning.
T4R - Learning journey
Learning with Microlearning Units
AI, Twinning and Agora
FRAMEWORK:
ETHICS, INCLUSION, DEMOCRATIZATION
MODULE:
Trust your city’s twin
EQF 6
EID-106
| EID-106 | third loop |
|---|---|
| AI, Twinning and Agora | Learner understands foundational AI concepts, including the distinction between supervised and unsupervised learning, and recognizes the importance of human responsibility and trust in AI interactions. Learner identifies appropriate AI use cases in LDTs and is aware of potential misuse and bias. Learner is sensitized to respond reflectively to AI ambitions in new project teams. |




