Our research shows there is a need for programs that are designed to support data professionals to cultivate reflexive approaches to navigating the intricate dynamics of highly complex for-purpose data systems.
Our ultimate goal in this multi-year project continues to be to equip data professionals with the necessary tools to mitigate immediate and future harm to data subjects and steer for-purpose data projects toward outcomes that promote human flourishing.
Cultivating reflexivity through systems visibility, for purposeful data decision making#
This report was funded by the Paul Ramsay Foundation and it details our groundwork over a 12-month period in which we developed and utilised our novel cybernetic framework to assess data professionals’ reflexive decision-making within data environments aiming to build interventions for vulnerable communities.
The Paul Ramsay Foundation’s purpose is to help end cycles of disadvantage in Australia by enabling opportunities for people and communities to thrive. The Foundation would like to thank its partners who were involved in this research for their contributions. Any opinions, findings, or conclusions expressed in this report belong to the research team and do not necessarily reflect the views of the Foundation.
Australia and the world are at a pivotal point in the ongoing complex and interrelated systemic challenges of climate change, public health, automation, labour, education and others. With the prevalence of machine learning applications, one sustained effort towards managing these complexities has been the deliberate and concerted effort to utilise complex and linked datasets in solutions to these grand challenges which for Australia, includes entrenched disadvantage.
The 2023 Commonwealth Government’s ‘Data and Digital Strategy’ agrees that extreme system dynamics ‘have supercharged the adoption of data and digital technologies across Australia’ and that data presents a ‘wealth of opportunities’ for delivering ‘services to provide better outcomes for all people’.
At the School of Cybernetics at the Australian National University, we are demonstrating how paying attention to system components and system dynamics can help us optimise decision-making in complex data systems.
Our cybernetics approach to data systems challenges technology-centric views while still recognising the importance of data and technology in finding solutions to today’s challenges. We found a strong willingness among data decision makers to embrace reflexive improvements aimed at fostering safe, responsible, and sustainable data for disadvantage practices. This desire was particularly strong in those data environments in which decision makers have to navigate uncertain political, legislative, and regulatory terrains.
Our findings suggest opportunities for conducting training and awareness workshops to show case how cybernetic reflexivity can promote better definitions of disadvantage, adoption of asset-framed approaches, enhancement of legitimacy and trust, and the optimisation of data system resourcing and access rights.
Cybernetic analysis defines a system as the unit of analysis and it explores how that system interacts with other systems. As humans are taken to be systems too, it gives the opportunity for people to see how they affect the system and how the system affects them.This is critical in disrupting disadvantage, as it allows people to think holistically about data collection, analysis and action, individual context, societal pressures and unintended consequences of policies.
The broad lessons outlined in this report can serve as guiding principles for the design of comprehensive tools that can promote systems awareness and reflexive practices in the data-driven and data-informed for-purpose sector.
- Project Position paper: Do more data equal more truth? Towards a cybernetic approach to data.
What can cybernetics tell us about the Optus and Medibank data hacks?
- Data Science Central: It takes a village to protect and steer data flow
- Enhancing Human Flourishing: The Synergy between Data and a Systems Approach
To learn more about this project, contact Research Fellow Chris Mesiku