Dance Steps to Understand and Visualise Personal Advertising Algo-Rhythms
Team: Prof Fiona Haines, Lauren Hayden, Matthew Lam, Justin Miller and Fuze Sun.
Mentor: A/Prof Nicholas Carah and Prof Christine Parker
SUMMARY OF IDEA
The team’s idea was called ‘Data Dancing’ – the notion was that researchers and people are ‘dancing’ on their own in the dark when it comes to digital advertising.
They suggested using a set of dance steps to invite people to understand and visualise their own advertising algo- rhythms in relation with each other, and to share them with researchers, regulators, story tellers, artists and journalists.
PRESENTATION
Download a PDF version of the Presentation: Dance Steps to Understand and Visualise Personal Advertising Algo-Rhythms
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
THE TEAM
Credit: Prof Fiona Haines, Lauren Hayden, Matthew Lam, Justin Miller, Fuze Sun, A/Prof Nicholas Carah and Prof Chrisine Parker.
Suggested Citation: Haines, F., Hayden, L., Lam, M., Miller, J., Sun, F., Carah, N., & Parker, C. (2022). Tech for Good: ADM+S Dark Ads Hackathon. Dance steps to understaned and visualise personal advertising algo-rhythms. Australian Research Council Centre for Automated Decision-Making and Society.
CONTACT US
If you are interested in collaborating on this research or speaking with this hackathon team contact adms@rmit.edu.au