10-02, 15:40–16:20 (Europe/Berlin), dattel
How can caring and earthing activities be enhanced through hypernudging? A reflection session on hypernudging’s sustainable and democratic potential to foster regenerative ecological commitment of communities.
Through the medium of a design thinking session, the session is intended to provoke a cooperative reflection on the limits and possibilities of implementing hypernudging to foster regenerative agroforestry practices apt to motivate experimenting the questioning of eco-social interactions.
As we’re constantly immersed in a digital design, we’re structurally nudged, pervasively pushed to digest certain information. Our session aims to problematise the undemocratic yet highly political use of hypernudging. We will reflect with the audience on how to extrapolate hypernudging’s advantages to democratically sustain the ecological transition.
Cambridge Analytica exploited Big Data and microtargeting to manipulatively push for Brexit and Trump’s election, fuelling polarisation and fragmented dystopian narratives. Why instead not use Big Data and microtargeting to voluntarily accelerate the ecological transition and promote caring engagement?
We intend to spark ideas on how frame conditions of Hyper Nudges can be designed to steer communities, according to their self-defined interests, towards a holistic and conscious use of natural resources. By establishing a thread with a regenerative agroforestry example, we reflect upon strategies on how local proactive agency can be promoted to tackle climate change. Can the high-tech societal homeostatic transformation find dignity through ecological education and engagement?
I'm Emilio, Italian-German, working at Italy's decarbonisation for a climate think tank. Political science student, philosophy of the digital graduate. On stage with my twin brother, forestry manager.
I'm Martin, currently studying the Master of Forestry System Transofrmation in Eberswalde and researching on Biomass. Graduated in Wood Engineering, and worked on data labelling for neural networks.