We are the world

Our starting point was, that we would co-create with the neighbourhood a research question on a public safety need and how AI could play a meaningful role here. Thus, our first step was to connect with citizens in the context of a community evening and to offer our public safety research services. Yet, it was clearly not as easy as this and our idea about “let’s start giving” turned out to be painfully naïve. We quickly realised that no one was waiting for us. There had been many researchers before us, and residents felt that little or nothing had been achieved. We also received clear feedback that public safety is not perceived as such a complicated issue that another study would be needed. After all, there are already enough cameras to catch all the people who do not behave. In the eyes of the members of the neighbourhood we talked to it is the police or the municipality who would need to step up their job using this surveillance material smartly, and there was not a strong feeling that the neighbourhood should take up a bigger role there than they already had through all their initiatives.  

After this rather disillusioning experience, we followed the advice of a community worker for a while to just listen and, above all, join existing initiatives in the neighbourhood. Our project team split up to participate in the 'cleaning gang', the 'unwise mothers', the 'neighbourhood watch team', and one of our PhDs used the neighbourhood community house as her workplace as much as possible. This approach led to good contacts and meaningful conversations. A key player was the 'neighbourhood concierge'. He rides his scooter around the neighbourhood, talking to people, attending meetings and interacting with everyone. He was willing to share his views with us, and the issue of 'trash' came to the fore as one of the main bottlenecks in the neighbourhood. Based on our conversations we asked neighbours to ‘surveil’ their neighbourhood and take photos of places they considered 'safe' and places they considered 'unsafe'.  

In subsequent conversations with neighbours, where we used AI tools together to integrate different perspectives and needs, we got a clearer idea of how to create “brighter day” in neighbourhoods. It turned out that places that are perceived as unsafe are mainly places that are messy, dirty and disorganised. And places that were considered safe were mainly places where there was greenery, flowers and animals. It seemed that the small things, such as maintaining greenery and picking up litter, made a huge difference to how neighbours felt about their immediate environment. Yes, “there is a choice we are making”.  I learnt how important it is to tailor the methodology in co-creation processes and really take enough time to co-create the problem definition. I also realised again how co-creation affects me as a person beyond my role as a researcher, as I now also pick up litter in front of my own house.