Improved performance methods aren’t too relevant
We’re still leg pressing-
“the presented approach would allow professionals but also their coaches to analyze in detail the athletes’ executions and improve their performances by looking in real time at the measured force and displacement time series or also calculated acceleration, velocity and power properties.”
Charlie Francis, the Jamaicans, Kenyans, Westside Barbell, Arnold Schwarzenegger haven’t needed any of these methods. That’s basically the training methods of all the fastest sprinters, long distance runners, strongest, best body compositions, ever.
- For force they used weight on the bar
- For speed they used a stopwatch
- For range of motion they used their eyes
And that was good enough.
Ninety nine point infinity nines will not care about increased performance beyond the above groups. We know how to get people stronger and faster enough.
The bottleneck with working out / losing weight is not our lack of knowledge with how to get someone stronger / faster / lose fat. It’s getting people to believe these things are worth doing. It’s similar to brushing our teeth. There is unlikely some revelatory brushing method waiting to be discovered, but a hell of a lot more people could brush their teeth consistently.
I’ve yet to see any study showing, or see any indication, AI improves adherence in comparison to a person. In fact, the wearable research would suggest, if anything, it’s detrimental.
Improving performance filtering is a dangerous, superfluous, endeavor
In certain countries it’s not unheard of to be screened by five years old for what you’ll excel at. The Germans, Russians and Chinese are most known for this. One way or another, they look(ed) for e.g. singing / academic / athletic ability; filter the hell out of whatever athletic ability you have into gymnast, sprinter, distance runner, whatever, and so on.
The whole promise of AI is the ability to predict. Despite the fact all the experience, brains, models, computer power we’ve accrued up to this point gives us a considerably lacking ability to predict the stock market aka human behavior, AI hopes to crack this nut.
There is so much variability in a lifetime that trying to filter people by age five is pretty insane. Even at ~20, it can still be way off. See: Tom Brady’s draft status. (The entire NFL draft is generally a crapshoot.)
Ed Sheeran is the biggest musician in the world in 2017. (Adele is quieter right now.) Damn near 50 million monthly listeners on Spotify, had 16 of the top 20 UK songs (not a typo), he’s backed by Elton John, he’s sold out Madison Square Garden three times, Wembley Stadium three times (totaling 240,000 people). He plays with no band. Bass, acoustic guitar, vocals, piano, he does it all.
The dude was born with no ear drum in one ear, which upon being replaced has burst multiple times throughout his life. He says his hearing is 25% in that ear. He had a birthmark so large it had to be lasered off his face…because it was causing glaucoma. He’s a ginger, needed coke-bottle glasses, was born in the music artist factory of east England, and had a stutter requiring speech therapy that didn’t work.
Who the hell would have predicted this guy as the biggest musician in the world in 2017??? Who is going to use genetic engineering -which is heavily based on machine learning right now- to ask for these traits? The most important things to a musician, their ears and mouth -and an argument can be made their looks- were by any measure lacking. (He has songs where he says how bad he is at video games. Even his hands don’t seem to work great.) Yet he’ll tell you without these things he’s not where he’s at.
-> Who would have predicted a guy with cancer in practically his entire body would be the most dominant cyclist ever?
Good luck thinking a computer program will know his parents would let him quit school and move out at 16 to start gigging. That he was willing to more or less be homeless for four years making a name for himself, the amount of fortitude he’d have to push through all the above while regularly playing shows where nobody was in the audience. That learning Eminem, another guy nobody and no-thing would have predicted would be where he is, songs is how he got over his stutter so he could eventually do this-
Those aren’t even his most popular songs. Of all things this guy is known as a first-dance-at-your-wedding artist!
Proof of his youth:
This is the messiness of being a human.
And the fear is not we’ll never get AI that good. The fear is all the people we’ll prematurely screen out of something that could have lead to them impacting millions. How much less interesting society could be.
There is no better filtering process than letting a person do the activity and see what happens. AI or not.
Nine part series-
- AI is neat. People are messy.
- Are computers really as good as humans in chess / Go / poker?
- Classification is done by people. Not AI.
- And people are fallible.
- Liability / Are we ok with machines telling us what to do? / Loneliness
- It’s not all sunshine and rainbows.
- The more expensive the gym is the less incentive the gym has to keep us there
- Why the gym hopes you never show up.
- Improved performance methods aren’t too relevant / Improving performance filtering is a dangerous, superfluous, endeavor
- Ed Sheeran laughs at predictive analytics.
- Why you’re unlikely to find the perfect program yourself, and why AI might not be better than a trainer
- Machines can tell you what to do, but can they tell you why?
- Thinking about why other countries have more trust in their healthcare system
- The electricity bill could be insane
- Incentives still matter. Voo doo economics.
- Is any company that says it’s green, actually?
- While there are rules, like less metabolic cost, people bend them, and humans as a market are rather hard to predict
- What happened to Xbox Kinect?
Posted on April 10, 2017