“Data can be either useful or perfectly anonymous but never both” (Ohm, 2009). This sober conclusion encapsulates a realisation we contemplate regularly as a data analysts, scientists, data practitioners and decision makers. Ethical frameworks mean different things and are applied in different ways depending on the contexts in which, and by whom they are applied. So how do we protect peoples' right to privacy while working transparently to address complex and highly-nuanced socio-economic problems? How do we balance this trade-off between useful and anonymous data? What does working with data ethically actually mean and where do you start?

In our first episode of Show Me the Data, we invite partner at GWI, Michelle Teis and the director of Griffith University’s Relational Insights Data Lab (RIDL), Dr. Tom Verhelst to help us define what a data ethics framework is. Michelle is an enterprise information management strategist and her experience in academia, private consultancy and commercial industry enables her to provide insight into these often divergent worlds. Host Rhetta Chappell asks how organisations of all sizes can practically apply ethical frameworks to their decision-making processes and Dr. Verhelst discusses how community organisations and not-for-profits can learn from the different approaches the commercial and academic sectors take when it comes to maximising the use of their data to improve decision making and reduce complexity.

If you have any questions or comments, you can reach us on Twitter at @G_RIDL or by email at [email protected]. Griffith University and the Relational Insights Data Lab (RIDL) are dedicated to building and supporting thriving communities. We believe that the right data, in the hands of the right people, can change lives for the better. We are committed to collaborating and co-designing solutions which address long standing, complex socio-economic problems. If you or your organisation would like to collaborate or learn more about the important work we do, please get in touch. We'd love to hear why data matters to you.

Thank you for listening to Show Me the Data.

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