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A popular self-driving car dataset is missing labels for hundreds of pedestrians

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Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#181

Earlier quoted context omitted.

I agree entirely with your point, and wanted to follow a small tangent: > they lack self-preservation instinct I suspect that a self-preservation instinct, even in relatively dumb animals, is enormously complex. It might seem simple to us because it's so evolved, so hardwired. If I had to bet, I'd bet that a mouse's self-preservation instinct is more complex than the first-to-market Level 5 self-driving car will be.…

That's a good point, and yes, I definitely don't want an automated vehicle to have self-preservation instinct. What we're all after is people-preservation instinct, which is not entirely unrelated to the former. But the broader reason I brought up self-preservation is that in humans, it's not just about not getting killed in a crash. It's also about not having your life ruined by causing it, even if you walk away phy…

> what it has is the reflection of priorities in the company that made it

I think it might even be more like Platonic shadows on a firelit cave wall of the priorities of the company that made it.

At the current level that self-driving is at, the cars' control software is only able to perceive and respond to situations that its programmers anticipated and specifically coded for. That could be heuristics and rules in the hard-coded bits, but, also, even the most sophisticated deep neural net out there isn't even particularly capable of perceiving, let alone understanding, things that weren't coded into its training set. Meaning that, even if the company's intention was that the car should not plow into a pedestrian holding an enormous cellophane-wrapped Edible Arrangements™ fruit basket, that intention doesn't have any bearing on the vehicle's behavior if the software instead classified that object as a plastic bag blowing in the wind.

Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#182

Earlier quoted context omitted.

People should learn not to go outside if they're not labelled.

What a funny future it'd be, if we have to wear something distinctive (giant QR codes?) so we don't get killed outside. As a side effect it would make tracking us much easier...

Sounds like something out of the book Snow Crash or the comic book Transmetropolitian

Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#183

Earlier quoted context omitted.

That's a good point, and yes, I definitely don't want an automated vehicle to have self-preservation instinct. What we're all after is people-preservation instinct, which is not entirely unrelated to the former. But the broader reason I brought up self-preservation is that in humans, it's not just about not getting killed in a crash. It's also about not having your life ruined by causing it, even if you walk away phy…

> what it has is the reflection of priorities in the company that made it I think it might even be more like Platonic shadows on a firelit cave wall of the priorities of the company that made it. At the current level that self-driving is at, the cars' control software is only able to perceive and respond to situations that its programmers anticipated and specifically coded for. That could be heuristics and rules in t…

Great points. And I'd add that the other implementation issue here is the human system any company's intentions get filtered through. So the interests modeled are not the entire corporation, but C-suite intentions passed through executive intentions, manager intentions, and then worker intentions.

E.g., it might be in the long-term interest of the company to not run over pedestrians. If nothing else, the PR cost is very high. But when an exec wants to be first in the field to demonstrate personal success, then hitting a made-up date becomes the priority. Which implicitly puts "not kill people" lower. Middle managers don't want to get blamed, so they'll favor a more complex, muddled organization structure. Per Conway's law, that means muddled code. So instead of the car's software reflecting "don't run over pedestrians" as a key goal, its true priorities are things like "gives a good demo", "was delivered 'on time'", and "reflects an architecture clever enough to get that architect promoted that quarter".

It's not impossible that good software comes out of this system, but the deck is certainly stacked against it.

Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#185
post #12
post #6

Earlier quoted context omitted.

I understand your concern and share it myself. This is an important time and we should be really careful training these things. However, training as used in the real world isn't on a still frame only basis, it's used in sequence. And while a single frame might be missing a label, I bet that at-speed most everything important gets labeled correctly enough to be better than a distracted human driver, or the average hum…

> And while a single frame might be missing a label, I bet that at-speed most everything important gets labeled correctly enough to be better than a distracted human driver, or the average human driver for that matter. Would you bet a family member? That a distracted driver is a hazard does not mean other drivers are safe, or even saf er .

> Would you bet a family member?

I bet myself and my passengers and everyone else on the road every time I take the wheel. That's what seat belts and other safety measures are for. I'm also willing to take those risks of other drivers I can't control. Why wouldn't I extend those risks one more step to a proven system? (The onus is on proof of that risk)

Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#186

Earlier quoted context omitted.

The average of something cannot be more than the average of... itself. Thus, "Humans are much safer than people on average" is nonsensical. > Why do you believe that Autopilot outperforms humans in comparable conditions? Because they have the data that proves it? > I'm extremely prejudiced against them And I've chosen to take them at face value with a grain of salt, and to believe that for the data they've collected…

"Our secret telemetry dataset gives us reason to believe that the cars produced by us are not safe." Would a statement like this be a surprise for you?

Only because you made it up to spread FUD. Good job.

Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#187

Earlier quoted context omitted.

The average of something cannot be more than the average of... itself. Thus, "Humans are much safer than people on average" is nonsensical. > Why do you believe that Autopilot outperforms humans in comparable conditions? Because they have the data that proves it? > I'm extremely prejudiced against them And I've chosen to take them at face value with a grain of salt, and to believe that for the data they've collected…

"Thus, "Humans are much safer than people on average" is nonsensical." Does it make more sense as "Humans, when driving in conditions suitable for Autopilot, are much safer than people on average"? "I've chosen to take them at face value with a grain of salt, and to believe that for the data they've collected from the hundreds of thousands of Tesla's with millions of hours of data using Autopilot, it's fair to say th…

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Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#188

Earlier quoted context omitted.

Sophistry. 'Much better' can be very clear, in terms of death or injury, or property damage, or insurance claims, or half a dozen reasonable measures. Sure it takes miles to determine what's better. Once automated driving is happening in millions (instead of hundreds) of cars on the road, it will take only days to measure.

I mean, the 'half a dozen reasonable measures' is a problem, not a solution, when they're not all saying the same thing. And sure, it only takes days before we know the latest version of the software actually isn't safer than the average human. And a lot of unnecessary deaths, and the likelihood the fix will cause other unnecessary deaths instead [maybe more, maybe less]. It's frankly sociopathic to dismiss the possi…

Straw man? There are many phases to testing a new piece of software, short of deploying everything to the field indiscriminately.

Some of us believe (perhaps wrong but there it is) that the human error rate will be trivially easy to improve upon. That's not sociopathic. It would be unhelpful to dismiss this innovation (self-driving cars) because of FUD.

Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#189
post #83

Earlier quoted context omitted.

If everyone believes that everyone else will be irrational, then they themselves will not throw their support behind nuclear power, rendering their stance on nuclear de facto irrational. As Baby Boomers age, and Millennials/GenZ form a greater percentage of the voting population, we have an opportunity to press the reset button on nuclear. The younger generations don’t really have a solid opinion on the matter, and p…

Is it a tautology or just an unfortunate nash equilibrium?

As you know, a nash equilibrium is the point at which no player can benefit from a move away from the equilibrium. However, that's a concept from game theory. What is the game here? Who are the players?

Part of my point is that you might think that the game is "scientists vs. politicians, ignoramuses, and fear-mongers," but that's not the case. Sometimes they're all on the same side. Imagine a 4 player split-screen Star Fox, where the scientist leaves their controller and helps the others shoot down their plane because they don't think they can win. If that sounds baffling, it is.

Re: A popular self-driving car dataset is missing labels for hundreds of pedestrians

#190

Earlier quoted context omitted.

The drawback of this method is that it's easy to miss a pedestrian amidst the sea of rectangles already drawn. You would be far better off paying people $x/hour to look at an image for 30 seconds and answer the question "Does this image have any people in it?" Y/N and watching for the human who says "Yes" when the AI says "No". Their accuracy rating will help distinguish who is best able to detect pedestrians that AI…

Why pay people to do this when you can make a CAPTCHA that requires them to do it for free? Google must have a really good data set from all those "click the boxes containing X" tests they make people do.

Most people don't have the funds on hand to use predatory pricing^ tactics to train machine learning algorithms.

^ "the pricing of goods or services at such a low level that other suppliers cannot compete and are forced to leave the market", to quote Google's definition (that was itself taken from some other company's dataset).

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