2023-03-06, 15:30–16:00, 01.S.21 (1st floor)
Python and Artificial Intelligence techniques, including deep learning and convolutional neural networks, can be used to improve demographic modeling in times of crisis or rapid change. Using the crisis in Venezuela as a case study, I demonstrate the utility of this approach in informing response efforts and decision-making.
In this talk, I will present a case study on the use of Artificial Intelligence and Python to more accurately estimate population dynamics in crisis situations, using the situation in Venezuela as an example. Traditional methods of demography, such as statistical modeling and survey data, are often insufficient in situations of rapid change or crisis. However, by using AI and deep learning techniques, including convolutional neural networks (CNNs), to analyse satellite imagery, it is possible to gain a more nuanced and up-to-date understanding of population movements and demographics. I will demonstrate how this approach can be used to inform decision-making and aid in crisis response efforts, and discuss the potential for it to be applied in other contexts.