This happens to professionals in any line of work. And generally to people doing repetitive work a lot.
In normal circumstances it’s perfectly safe, until it’s not because of an unpredictable situation.
Not really. Follow the car in front, stop for red, wait for green, check mirror. You could make an algorithm for 99% of the interactions that happen, at least in Danish cities. But if you live in a city with almost no bike infrastructure and visit a city with bike lanes everywhere, it isn’t part of your “learned automation” to check the bike lane before turning. And it is usually worse if the place is “familiar enough” since you need that familiarity for the “automation” to kick in.
You could make an algorithm for 99% of the interactions that happen
Absolutely. But you still have to be actively paying attention to watch for the 1% that isn’t predictable. It’s like flying a plane; autopilot systems are theoretically advanced enough to complete an entire flight all by themselves, but the pilot at the controls is still expected to be fully alert and active at all times.
Couldn’t agree more, I’m just arguing that city traffic can still be predictable enough to inadvertently trigger that “automation” mode. As with my example the car would risk torpedoing a cyclist when turning. That’s something I’m acutely aware of when biking and I know exactly which turns are the most dangerous in my city.
When biking, my autonomous activities are turned off. I become hyper-aware because I’m an American and I know that my value has gone down 90% just by hopping on a bike instead of a big truck.
That’s the problem: it’s a limitation of the human brain, not a moral falling. We can’t give total attention when bored, which is why having cars as the primary mode of daily transport is an absolutely awful idea.
This happens to professionals in any line of work. And generally to people doing repetitive work a lot. In normal circumstances it’s perfectly safe, until it’s not because of an unpredictable situation.
Japanese railways use a technique called point-and-call to deal with it
https://www.youtube.com/watch?v=RZun7IvqMvE
Which driving in city traffic usually is, I would think
Not really. Follow the car in front, stop for red, wait for green, check mirror. You could make an algorithm for 99% of the interactions that happen, at least in Danish cities. But if you live in a city with almost no bike infrastructure and visit a city with bike lanes everywhere, it isn’t part of your “learned automation” to check the bike lane before turning. And it is usually worse if the place is “familiar enough” since you need that familiarity for the “automation” to kick in.
Absolutely. But you still have to be actively paying attention to watch for the 1% that isn’t predictable. It’s like flying a plane; autopilot systems are theoretically advanced enough to complete an entire flight all by themselves, but the pilot at the controls is still expected to be fully alert and active at all times.
Couldn’t agree more, I’m just arguing that city traffic can still be predictable enough to inadvertently trigger that “automation” mode. As with my example the car would risk torpedoing a cyclist when turning. That’s something I’m acutely aware of when biking and I know exactly which turns are the most dangerous in my city.
When biking, my autonomous activities are turned off. I become hyper-aware because I’m an American and I know that my value has gone down 90% just by hopping on a bike instead of a big truck.
That’s the problem: it’s a limitation of the human brain, not a moral falling. We can’t give total attention when bored, which is why having cars as the primary mode of daily transport is an absolutely awful idea.