CECAN Fellowship: Evaluating adaptive policy mechanisms for urban drone delivery services under complexity
The current approach used to evaluate drone delivery services and policies uses a prediction-based approach (cost-benefit analysis, traffic modeling, etc.) which does not account for emergent behaviors, feedback, and interactions between sectors. In light of growing drone delivery services, there are emerging policy problems such as airspace congestion, noise pollution, acceptance by the public, privacy issues, safety risks, and unequal distribution of benefits among other problems. These problems interact nonlinearly; for instance, an increase in deliveries per area decreases road traffic but leads to noise pollution in particular neighbourhoods that leads to political feedback and consequently changes in policy. It should also be noted that current policy sandboxes and trials do not account for any complexity evaluation of those policies. Currently, there is a lack of a method to assess the interaction of local drone delivery services and policies with transport, logistics, environment and urban development goals over time.
About Dr. Aldajani
Dr. Aldajani is an information systems researcher working mainly in the domain of evaluating and governing complex socio-technical systems. He is interested in how emerging technologies such as artificial intelligence, autonomous technologies, and digital platforms affect decision-making, public services, and organizational activities. Using complexity science, systems thinking, and computational modelling, he is developing evaluation methods that can assist policymakers and organizations in understanding how their intervention strategies would perform in dynamic environments with emergent outcomes resulting from interactions of multiple entities. One of the important themes of his research is the development of evaluation approaches that go beyond static and purely predictive methods. His research includes the use of agent-based modelling, simulations, and governance tools to study how policies and technologies evolve over time in response to feedback and uncertainty in social, technical, and institutional environments. Research domains include AI governance, digital transformation, urban innovation, and public policy evaluation.
