Why this project? Why now?

Since 2017, I have been researching ways to develop young people’s understandings of personal data and privacy. Rather than a didactic, top-down approach I’ve worked with colleagues – namely, Neil Selwyn at Monash University and Lourdes Cardozo Gaibisso at Universidad de ORT (Uruguay) – to develop digital methods for developing what we have loosely called ‘critical data literacies’ – or a critical understanding of the way data works in the digital economy. It’s not easy work! The digital economy is complex and evolving, with much of it obscured from view.

In the most recent project, we worked with developers and grade 5 students at Bellbrae Primary School to design an educational chat app called FriendSend. The app appears as a regular chat app, but is able to collect and process the data generated through chat and present the insights to users via a dashboard on an associated web app. Using Google APIs the chat, image and geolocational data are processed, mimicking the personal data profiling that takes place on most mainstream apps today – but without the commercial implications. You can read more about this project and download the resources here. As with my previous research into young people’s digital practices, we found participants have a sense of the digital infrastructure and the role that personal data play. But this is complex stuff, not least because personal data generation is now entangled with everyday life.

What we found to be most effective in developing understandings of personal data was perhaps the most simple part of the app – materialising geolocational data on a map. For the kids, being able to see personal data being ‘made’ – as you were walking around the school or driving home – was powerful. It was then I realised that any project that seeks to develop critical data literacies must start by making data material. We might aim to be data literate, but if we cannot identify the ‘text’ then we won’t get very far.

This project aims to investigate new and creative ways to materialise data as a text for critical analysis. It is a part of a two year Alfred Deakin Postdoctoral Fellowship. The complexity of this question requires an interdisciplinary approach. Over the next two years I will be working with an artist and software developer to think critically and creatively about what data is and isn’t. My mentor throughout the journey is Prof Julian Sefton-Green.