Existential and catastrophic risk : a landscape perspective

There hasn’t been much added to the notepad over the past year but this is not for lack of activity- a lot has been going on and I hope that over the coming weeks I can start to share progress on the Magnolia research and our work at the Yorkshire Arboretum, as well as an update on the landscape assessments that were carried out of Sheffield highways and some commentary on the recently published 25 Year Environment Plan.

In the meantime, I wanted to share some thoughts on a project that I am contributing to that is run by the Existential Risk Research Network based at the University of Cambridge as it is a departure from the ‘normal’ work of a landscape architect with research interests. The project is being run by Gorm Shackelford with the aim of developing a tool that can process the overwhelming volume of research that is published on the subjects of catastrophic or existential risk: the problem is such that so much work is being carried out in fields that may yield insights that the normal process of literature review inevitably leads to sampling problems and bias that prevent a sound analysis of the global risks. A quick explainer: existential risk describes the probability of the collapse or extinction of human beings whilst catastrophic risk describes the probability of the loss of 10 million + lives. The causes of these events might range from biological threats, to climate change, artificial intelligence, cosmic disasters or war… threats that landscape architects tend to work with to some degree or other but usually only in an abstract or remote sense.

The process developed is almost as interesting as the subject matter and in part, I am contributing to the project to see how his work develops: the idea is that a machine learning tool identifies a vast number of publications that may be relevant to assessing existential risk and that this list is used to create a potential bibliography. Contributors to the project then assess a sample of these publications and feed the results back into the machine learning tool, so that it can better identify potentially useful publications. Fascinating work to keep an eye on that could change the way that we review literature… and in the meantime introducing me to a whole world of literature that I would not ordinarily have knowledge of whether it is theatre in Greenwich Village in the 1960s, assessing the likelihood of flooding hazard in Australia or straight up cheering reading about the biological annihilation that is underway at the moment or nine scenarios for the imminent apocalypse.