RiverEYE or RiverSPY - Citizen Science & ANT

Project Details

Understanding Actor-Network Theory and Why it was used to evaluate RiverEYE

Actor-Network Theory (ANT) is a sociological theory that helps us understand how people and objects interact to shape and influence the world around us. It looks at how different actors, such as individuals, organisations, or even non-human things like technology or animals, work together and form networks of relationships. In ANT, an actor can be anything that has the ability to act or influence a situation. For example, within the RiverEYE pilot then the river, the citizens, the phones, the agencies involved and the data itself were all considered actors.

ANT sees the world as a series of interconnected networks made up of these actors, where each actor has the ability to influence and shape what happens. These networks are made up of human actors and include non-human entities like technology. It emphasises that people and things are not separate, but they are connected and work together to produce different outcomes. A central ANT idea is that actors are not always equal in terms of power or influence. Some actors may have more power and play a more significant role in shaping the network, while others might have less power and be more influenced by others. It also suggests that the actions of one actor can have consequences that ripple through the entire network, affecting other actors and the overall outcome.

Overall, ANT helps us understand how different actors come together, form networks of relationships, and co-produce the social world we live in. It highlights the idea that everything and everyone is connected and that understanding these networks is crucial to understanding how society works. By applying ANT to the RiverEYE tool it was possible to evaluate how technology was informing human behaviour and vice versa - critically ANT provided a framework to evidence how this means of data collection could be a disruptive influence and how organisations would have to adapt to make the best use of this form of data collection.