The Economist has commented on the irony that machine learning helps school teachers relax after work by choosing what movie to watch, but helps none in determining how to assist their students. In my fellowship this summer, I tried to change that. At DSSG, I worked with the Tulsa Public Schools to do identify which students are at risk of being made to repeat 3rd grade. Using machine learning techniques we were able to predict 95% of the second grade students that would require intervention before the Reading Sufficiency Act destined them to do the year over.
At Data Fest 2016 I gave a fuller yet concise explanation, watch the video below.… Read the rest
I didn’t like the Dyson Airblade at first. Its slick futuristic form with neon yellow striping gives the visual indication that it will instantly dry your hands, which it doesn’t. It takes 12 seconds. Still, I claim this represents a revolution. The watch-a-microwave-tick-down waiting time is a small price to pay for leaving the tiled room with hands truly free of water, rather than the less-wet state my whole life prior to this invention taught me was normal.
To understand why the Airblade represents such a leap forward in hand-drying technology, we have to understand the past that Dyson was trying to escape.… Read the rest
Searching through my draft blogs I find that the earliest is un-annotated, but prophetic collection of quotes I compiled in 2011. They are from Walter Isaacson’s Steve Jobs biography, that too-strong dose of propaganda that turned me off of the mystique of supposedly messianic technology. (Perhaps I don’t give enough weight to the fact that it was the first and last book that I read entirely on a laptop). I admit I was – and still am – wooed by the allure of technolust, but at that moment, I stopped seeing computational progress as a deliverance and started seeing it blunt tool, often overdressed.… Read the rest