Feral Robotic Public Authoring

Digital methods, such as data mining and mapping, are increasingly used in spatial projects with the aim of enhancing community engagement or civic self-organisation. This project is a collaboration between artists’ studio Proboscis and artist Natalie Jeremijenko, named Feral Robotics Public Authoring. This project enabled people to explore their local environments with electronic sensors that they attached to DIY modifications of toy dogs or DIY built robots that detected air quality, noise and light pollution. This data was then visualised through online tools.

The combination of cheap electronics (such as toy robots) with online tools was aimed at giving  people the feeling that they could learn about their environment in a fun and tactile way, while collecting evidence (through mapping) that, in turn, would instigate action. This project was introduced in robot-building and mapping workshops that took place during traditional community events (village fetes and local festivals), which therefore attracted a lot of local participants. The studio imagined a growing network of hobbyist data collectors, developing over the years after they initiated the project, who would start mapping their own environment and take action to instigate change (Lane et al., 2006). The project, however, never resulted in on-going civic self-organisation nor did it have any other long-term effect, such as the community organising their own workshops to build tools to measure air quality, or to compare the collected data with ‘official’ governmental data.

Link to this project

From my understanding the data that is derived in this project is not given as much importance as the ones who collect it. After all, this project strives to involve local residents in data-collection regarding a public issue. The performance that it is given (+ introducing it in village fetes) is a way to recruit the ‘right’ people. The question however is how to make such endeavour sustainable. Will people feel motivated to keep tracking the data over a longer period of time? Thinking that only then it will gain the same significance and credibility as e.g. governmental data. On what scale should this be done to have an actual impact or even change policy.