There's a theory about this:
https://en.wikipedia.org/wiki/Risk_compensation> "Risk compensation is a theory which suggests that people typically adjust their behavior in response to the perceived level of risk, becoming more careful where they sense greater risk and less careful if they feel more protected. Although usually small in comparison to the fundamental benefits of safety interventions, it may result in a lower net benefit than expected."
There's a book too, with a special emphasis on on financial crises. https://www.theguardian.com/books/2015/oct/12/foolproof-greg...
> "In the run-up to the crash, consumers and even policymakers had come to believe that smart regulators and forward-thinking bankers had made the world of money a much safer place.
> "The fundamental insight of Ip’s new book, Foolproof, is that this very belief was a key factor in the lead up to the crash. When people believe they are safe, they take more risks – they drive faster, in motoring terms – and “speed makes everything worse”. Or as the economist Hyman Minsky, whose work Ip revisits, put it: “Stability is destabilising.”
There are applications in our field too:
- safety features for users might make them behave less safely (e.g. exploding messages)
- better reliability of systems might lead us to put more trust in them, leading to even bigger outages when they occur (e.g. centralising trust in cloud providers)
It's interesting to see things like Chaos Engineering (https://principlesofchaos.org/) introducing intentional "danger" into a system in order to improve system-wide stability. Of course, maybe Chaos Engineering will give us more trust in our systems which may lead us to take even bigger risks...