High-tech for low-tech
Below is an abstract that myself, Helene Degerman and Olof Mogren got accepted at the International Degrowth Conference 2024.
High-tech for low-tech: Some thoughts on AI-based mitigation of ecological breakdown in anticipation of post-growth
The 2020s are shaping up to become a decade of two major and simultaneous forms of acceleration, one of which is likely to severely hamper the other. On the one hand we have technological acceleration, driven to a large extent by massive innovation and investments within artificial intelligence (AI), coupled with a largely unquestioned belief in the continuation of a growth-based socio-economical global system. On the other hand, more than half a century after the warnings put forward in The Limits to Growth, we are experiencing an ecological acceleration towards a future with a significantly lower carrying capacity for humans and other species. This, in turn, will result in a post-growth global system, be it through societal collapse(s) or more gradual decline(s), which in the best case involves globally orchestrated political efforts. Thus, while the dominant socio-cultural expectation is one where ecological breakdown to an increasing extent will be tackled by energy- and material-intensive high-tech, our biophysical reality suggests a future with less high-tech and instead more low-tech solutions, which are more resilient and long-lasting.
The above begs the question: What are some useful practices regarding high-tech (here with a focus on AI) when it is still available for many, and when assuming a future of drastically reduced availability of said high-tech? Among many possible directions, we call for a high-tech for low-tech research agenda, by which we mean the development of AI methods for improving the use and deployment of low(er)-tech systems and solutions. By low-tech we refer broadly to technologies that require relatively less energy, materials, human specialization and/or complex infrastructure to maintain. An illuminating example of high-tech for low-tech is the use of AI for optimizing the deployment of nature-based solutions, such as green infrastructure in cities, where AI can be used to optimally balance various criteria and assist in decision making processes. Hence, when still in an era of readily available high-tech systems (for many parts of the world), we argue that these should be used to make the most effective use of low-tech. These low-tech ‘mitigation responses’ to ecological and societal disorder, in turn, will continue to be useful even if critical societal infrastructure that is needed to support the high-tech solutions breaks down.
We call on the broader technology research and development communities to join us in contemplating and implementing the above and other suitable responses in anticipation of post-growth.