What a case study of systemic risk with CrowdStrike outage... that a few bits in the wrong place can brick ~1 billion computers and all the 2nd, 3rd order effects of it. What other single points of instantaneous failure exist in the technosphere and how do we design against it.

Civilization VII was announced today. The Civ series is sort of like Ender’s Game, but for management rather than murdering aliens. Business school students who were good at Civ V also turn out to be better planners, organizers, and problem-solvers, in this small experiment.

**New DataViz Project** Curious about academic impact? Tired of rankings? Today we are introducing Rankless (rankless.org/) a new data exploration platform that can help you explore the academic impact of thousands of universities. All universities produce impact that is specific to certain topics and geographies, but rankings flatten that information. Rankless wants to change that. Consider a comparison between the University of Utah and the University of Vienna, two universities ranked similarly in the Shanghai ranking. These universities differ in their geographical and topical footprint. The University of Utah specializes in Neuroscience and Medicine whereas the University of Vienna specializes in Physics, Astronomy, and Environmental Sciences. Their geographic impact is also quite different. Utah receives a large fraction of citations from medical centers in the U.S., Canada, and Israel, whereas Vienna receives many citations from technical institutes in Austria, Germany, and Hungary. These differences are easy to explore in Rankless but hard to see in rankings. Rankless was developed by a talented team at the Center for Collective Learning at Corvinus University (@uni_corvinus). It was brought to life by Endre Mark Borza (@endremborza), a Hungarian economist and data engineer at CCL with the help of Máté Barkóczi, a Hungarian designer form MOME, and Veronika Hamar executive director at CCL. By moving beyond rankings, Rankless offers a fresh perspective on how universities influence each geography and topic, emphasizing diverse forms of impact and providing a richer understanding of academic influence. To learn more visit Rankless.org

Do algorithms learn to internalize network effects? And how do they deal with multiple equilibria? Is Q-learning in fact optimal as a pricing algorithm? @evankats and I address these questions in our latest article. doi.org/10.1007/s10660-024-0…