Hyperproblems are scientific challenges whose scale, complexity, novelty and interdependence overwhelm traditional research models, requiring new forms of collective intelligence, modeling, coordination and communication.
Shut Up and Prove
My first love was the foundations of mathematics. Or maybe the second love; the first was quantum mechanics. But my first love where I had any kind of technical purchase on the domain of inquiry was the foundations of mathematics. In fact, I think I read a proof of Gödel’s theorem and tried to understand it, and perhaps even rework it, before I was truly fluent in much older kinds of mathematics, like the differential calculus.
Epistrons: Knowledge Artifacts for Hyperproblems
In my introductory post on hyperproblems, I ended with Common Source - open source plus people sharing - as the circulatory system for collective intelligence. I hadn't said what exactly was circulating, but if you look at the practice of science today, we have:
Hyperproblems: New Ways of Doing and Communicating Science
Ten years ago, when the Paris Accords were signed and we agreed (by the way, who's the we?) that we need to keep global temperature rise well below two degrees and ideally no more than 1.5 degrees above the pre-modern average, there was also a sense of urgency, that we need to set major shifts into motion by 2030 in order for the 1.5 degree goal to be met. That was the whole point of the Paris Accords.