The pay is $8.57 million an hour, but bulls are involved
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David Biderman at The Wall Street Journal examined the amount of money made per hour in various “unique” sports, including bull riding, playing scrabble, and competitive eating. For those at the top of their game in these activities, the cash flows easily, but there is still a matter of degree. Bull riding comes out on top, at $8.57 million per hour, while Scrabble is at the bottom, at only $62 per hour.
Of course, this is not entirely accurate. For example, a champion bull rider such as Kody Lostroh doesn’t need to stay on the bull for an entire hour; last year, he won by being on a bull for 11 minutes and 24 seconds. But still, taking in over one and a half million dollars for under 15 minutes of work is not too bad. It’s unclear how much practice is required to remain a top bull rider, as compared to a top Scrabble player, for example, where memorizing words helps pay the bills — or a champion competitive eater, where the practice food bill no doubt takes a slice out of the net win.
It’s the 21st century. Knowing how to read a novel, craft an essay, and derive the slope of a tangent isn’t enough anymore. You need to know how to swim through the data deluge, optimize your prose for Twitter, and expose statistics that lie.
I look forward to Liberal Arts 3.0, in which we learn how to best handle our role in the hivemind — and how to avoid the wrath of our squid overlords.
In order to solve this, the lead author persuaded six of his colleagues to be punched by a robot, specifically a production-line quality one. Each subject then rated the intensity of being smacked by a robot. And every time a beating was rated as causing any sort of pain, this robot was in clear violation of Isaac Asimov’s First Law of Robotics: ”A robot may not injure a human being or, through inaction, allow a human being to come to harm.”
Research aside, though, journalists are having a field day with this, because it is quite simply so bizarre and reads like something from The Onion. The headlines included: ”Robots Learning How Not to Hurt Humans, By Punching Them” and ”Robot Beats Up Volunteers.”
Samuel Arbesman is a postdoctoral fellow in the Department of Health Care Policy at Harvard Medical School and is affiliated with the Institute for Quantitative Social Science at Harvard University. He is a regular contributor to Ideas. 
