What does governance look like in a fast-paced, agile computing world where artificial intelligences can, will always, and perhaps necessarily will find hacks to achieve goals in unintended ways?
Can the objective functions these systems optimize for be well defined enough to produce trustworthy results, or will they always surprise us?
Mentions: corporate mortality, Charles Stross, David Runciman, agile governance
I’m excited to be speaking & hosting a workshop (November 30) at this year’s R Gov Conference (@rstatsai) along with many others on December 1-2! Join us in-person or virtually online for a fun filled event! Get your ticket now at rstats.ai/gov #rstatsgov | #rstats
A good, evidence-based chart brings clarity to complex situations. The New York Times frequently finds that sweet spot.
Click through to the interactive version of this chart, being updated daily, on the NYTimes website.
https://www.nytimes.com/interactive/2020/03/21/upshot/coronavirus-deaths-by-country.html
The COVID-19 pandemic presents an opportunity for a number of both natural and public policy experiments, which should—albeit are unlikely to—inform public policy going forward.
Does human activity impact the environment? Yes.
Can that effect be mitigated? Yes.
https://www.forbes.com/sites/jeffmcmahon/2020/03/22/video-watch-from-space-as-air-pollution-vanishes-over-china-during-coronavirus-lockdown-then-returns/
To amend the Elementary and Secondary Education Act of 1965 to strengthen elementary and secondary computer science education, and for other purposes.
https://beta.congress.gov/bill/113th-congress/house-bill/2536
Infographics have a way of bringing issues into focus (… thus “INFOgraphics”, I suppose!). American education reform seems to be stuck in a pattern of finding fault, then believing that more of the same policies that created the faults are the solution.
