Why athletes need a ‘quiet eye’

The concept of quiet eye originates with the personal experiences of a kinesiologist called Joan Vickers. As a student in sports science – and a keen athlete herself – Vickers always had been interested in how our athletic talents vary so much from day to day.

While playing on the university basketball team, for instance, she once scored an extraordinary 27 points within the first half of a match. Another time, she had a stunning winning streak while serving for the university volleyball team. But both miraculous performances were one-offs – each time, her magic touch disappeared the next day.
“It kept on running around my head – how could I have done that? Physically I didn’t change,” she says. On the other hand, why were the elite athletes she envied not only so good, but also so consistent?

Embarking on a PhD at the University of British Columbia, Vickers began to suspect the secret lay in the way that elite athletes see the world. She hooked a group of professional golfers up to a device that precisely monitored their eye movements as they putted their balls. She found an intriguing correlation: the better the player (as measured by their golfing handicap) the longer and steadier their gaze on the ball just before, and then during, their strike. Novices, by contrast, tended to shift their focus between different areas of the scene, with each fixation lasting for shorter periods of time.

BBC – Future – Why athletes need a ‘quiet eye’

After Surgery in Germany, I Wanted Vicodin, Not Herbal Tea – The New York Times

I recently had a hysterectomy here in Munich, where we moved from California four years ago for my husband’s job. Even though his job ended a year ago, we decided to stay while he tries to start a business. Thanks to the German health care system, our insurance remained in force. This, however, is not a story about the benefits of universal health care.

Thanks to modern medicine, my hysterectomy was performed laparoscopically, without an overnight hospital stay. My only concern about this early release was pain management. The fibroids that necessitated the surgery were particularly large and painful, and the procedure would be more complicated.

I brought up the subject of painkillers with my gynecologist weeks before my surgery. She said that I would be given ibuprofen. “Is that it?” I asked. “That’s what I take if I have a headache. The removal of an organ certainly deserves more.”

“That’s all you will need,” she said, with the body confidence that comes from a lifetime of skiing in crisp, Alpine air.

I decided to pursue the topic with the surgeon.

After Surgery in Germany, I Wanted Vicodin, Not Herbal Tea – The New York Times

The Dark Secret at the Heart of AI – MIT Technology Review

Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of artificial intelligence. The car didn’t follow a single instruction provided by an engineer or programmer. Instead, it relied entirely on an algorithm that had taught itself to drive by watching a human do it.

Getting a car to drive this way was an impressive feat. But it’s also a bit unsettling, since it isn’t completely clear how the car makes its decisions. Information from the vehicle’s sensors goes straight into a huge network of artificial neurons that process the data and then deliver the commands required to operate the steering wheel, the brakes, and other systems. The result seems to match the responses you’d expect from a human driver. But what if one day it did something unexpected—crashed into a tree, or sat at a green light? As things stand now, it might be difficult to find out why. The system is so complicated that even the engineers who designed it may struggle to isolate the reason for any single action. And you can’t ask it: there is no obvious way to design such a system so that it could always explain why it did what it did.

The mysterious mind of this vehicle points to a looming issue with artificial intelligence. The car’s underlying AI technology, known as deep learning, has proved very powerful at solving problems in recent years, and it has been widely deployed for tasks like image captioning, voice recognition, and language translation. There is now hope that the same techniques will be able to diagnose deadly diseases, make million-dollar trading decisions, and do countless other things to transform whole industries.

The Dark Secret at the Heart of AI – MIT Technology Review