TUM is aiming to build a map of poverty. This involves a regression problem, rather than a classification problem – which means that the AI is used to predict a number rather than a classification.

Data about poverty, for example from a census, is mapped onto satellite imagery. The AI can then make predictions about how this will change over time, or how this might extend into different locations.

This brings in lots of ethical implications – they are looking into this at TUM. For example – are you putting refugees at risk by mapping where their settlements are? There are positives to this but also it could be problematic if the data is used by adversaries.

There is also the question of bias. For example, if an electricity company commissions a company to use AI to find out where to provide electricity, they will be looking for a return in their investment – so will inevitably be biased towards places where there are people who will be able to pay for the electricity.

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• Xiaoxiang Zhu

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