Great post, Jessica and Sean! To be honest, if I had read through this post around the time I graduated from my engineering degree, I would have thought harder before going into consulting (although I did not plan to stay in consulting for long, and ended up leaving after a year or so).
All else being equal, when prioritising between defence layers, prevention is most important (before loss of life), followed by response (to contain the catastrophe), and then finally resilience (the last resort to make sure humanity and civilisation survive). However, the resilience defence layer is often the most neglected of these, which may mean that working in this area could enable you to have an outsized impact.
To me it is unclear which layer is the most important or neglected.
I would say the most important layer is the one which is harder to break. For example, if p(“civilisation collapse”|”global catastrophe”) is lower than both p(“catastrophe”) and p(“global catastrophe”|”catastrophe”), I suppose it is reasonable to say that resilience is the most important.
In terms of neglectedness, I think we should also take into account the resources that would be invested in the event of a catastrophe. Ignoring these will tend to overestimate the neglectedness of resilience. After the catastrophe happens, lots of resources can be directed towards response and resilience, but not to prevention. So we have something like, “resources going to resilience/response” = “resources going to resilience/response now” + p(“catastrophe”)*”resources which would go to resilience/response in the event of a catastrophe”. I tried to make a similar point here.
Thanks for your comment Vasco! There are definitely lots of factors at play here, and the “all else being equal” bit in the part you quoted is doing a lot of heavy lifting and masking multiple assumptions that we could perhaps have laid out more clearly, including the assumption that p(“civilisation collapse”) << p(“global catastrophe”) << p(“catastrophe”), and that equal amounts of resources are going into prevention, response, and resilience.
This is of course not the case, but analysis of this landscape is out of scope for this iteration of the Resources Portal. This page was designed as an introduction for engineers looking into high-impact areas to do work in/start projects in, and hopefully future iterations of our Resources Portal will be able to deep dive these intricacies. Thank you for bringing this to our attention, as it’s something we will look into in the future!
Great post, Jessica and Sean! To be honest, if I had read through this post around the time I graduated from my engineering degree, I would have thought harder before going into consulting (although I did not plan to stay in consulting for long, and ended up leaving after a year or so).
To me it is unclear which layer is the most important or neglected.
I would say the most important layer is the one which is harder to break. For example, if p(“civilisation collapse”|”global catastrophe”) is lower than both p(“catastrophe”) and p(“global catastrophe”|”catastrophe”), I suppose it is reasonable to say that resilience is the most important.
In terms of neglectedness, I think we should also take into account the resources that would be invested in the event of a catastrophe. Ignoring these will tend to overestimate the neglectedness of resilience. After the catastrophe happens, lots of resources can be directed towards response and resilience, but not to prevention. So we have something like, “resources going to resilience/response” = “resources going to resilience/response now” + p(“catastrophe”)*”resources which would go to resilience/response in the event of a catastrophe”. I tried to make a similar point here.
Thanks for your comment Vasco! There are definitely lots of factors at play here, and the “all else being equal” bit in the part you quoted is doing a lot of heavy lifting and masking multiple assumptions that we could perhaps have laid out more clearly, including the assumption that p(“civilisation collapse”) << p(“global catastrophe”) << p(“catastrophe”), and that equal amounts of resources are going into prevention, response, and resilience.
This is of course not the case, but analysis of this landscape is out of scope for this iteration of the Resources Portal. This page was designed as an introduction for engineers looking into high-impact areas to do work in/start projects in, and hopefully future iterations of our Resources Portal will be able to deep dive these intricacies. Thank you for bringing this to our attention, as it’s something we will look into in the future!