Category Archives: Computer science

Covid-19 and time

I can now conclusively answer the question raised at the end of my blog post from December 2019: the 2020s are not a decade of orderly peace. What a strange year. But weren’t years always strange? Time passes not only quantitatively but also qualitatively. A year spent with Covid-19 seems to have passed differently from […]

The year and decade in review. 2020s: orderly peace?

2019 comes to a close, and with it the 2010s. Below are a few thoughts on these periods of time. The most significant book I’ve read in 2019 is probably Hannah Arendt’s The Origins of Totalitarianism. The German title, literally “Elements and Origins of Totalitarian Rule” more closely reflects the contents of this monograph. Arendt […]

Dreyfus and Bostrom. Four AI assumptions and two books.

At first glance, Hubert Dreyfus’ 1992 book What Computers Still Can’t Do (WCSCD, originally published in 1972 as What Computers Can’t Do) seems untimely in the current business climate, which favours massive and widespread investment in AI (these days, often understood as being synonymous with machine learning and neural networks). However, being untimely may in fact […]

Rice fields and rain

Humans primarily live in a world of beings, each of which has meaning. Meaningful beings appear to us interconnected, referencing practices and other beings in a referential totality. Buttons suggest pushing, chairs suggest sitting, a tractor suggests farming. A (Japanese) rice paddy may suggest the heavy labour that goes into the rice harvest each year, […]

AI and the politics of perception

Elon Musk, entrepreneur of some renown, believes that the sudden eruption of a very powerful artificial intelligence is one of the greatest threats facing mankind. “Control of a super powerful AI by a small number of humans is the most proximate concern”, he tweets. He’s not alone among silicon valley personalities to have this concern. To reduce the […]