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Comment by throwaway55554 | Hacker News Reader

Awesome! Now do it again and when it passes one set of parked cars on the side, have someone roll a soccer ball in front of the Tesla. Will the car assume a child will follow from in between the cars or not?

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> Will the car assume a child will follow from in between the cars or not?

Will most human drivers?

Should we not expect both to?

I would expect both to, but for me the baseline is "as good as the average human". So in that vein, not predicting a child after a ball is still better than the baseline.

Most will assume this, the correct question would be: Would most human react fast enough?

> Most will assume this,

I've been driving a long time. I rarely see people hit their brakes when a ball comes out, or even slow down. My anecdotal evidence from 300,000 miles of driving says this isn't the case.

A neural network needs to be taught this and then all cars with that training will respond correctly forever.

Every individual human would need to learn this separately from experience, which would require far more soccer balls (and children).

It's not that hard for people to learn; see a ball, expect danger and take action.

The problem with people is distraction. The problem with code (AI-ish) is people.

By "taught this" do you mean kill a kid?

No. He means see a human avoid killing a kid.

Run this scenario in a thousand variants in sims.

I've yet to meet a human that needs to observe enormous numbers of balls and children against a number of different backdrops before they grasp the concept that they're different from the background environments, never mind potentially linked to unsafe road use.

The conclusion that a neural network classifies stuff 'correctly forever' is also not one supported by the current state of computer vision.

As you have implied in your example, humans cannot make observations about the present and reason about the near future. As a result, they must learn the consequences of any action by experiencing it.

So the situation is really much worse than you describe. Even if we invested in demonstrating the "soccer ball and child" scenario for all driving students, they wouldn't be able to apply the experience to tennis balls and dogs, or a child entering the road without any sort of ball. Teaching people to drive would require an exhaustive course in every conceivable scenario that might arise while driving. You can see why it's an intractable problem.

Say what you want, but you would never be able to avoid a crash like this: https://www.youtube.com/watch?v=oqHtavx-eec

Or this https://www.youtube.com/watch?v=2uqA9bqICEk

I think the first might just look difficult to avoid because if the lack of peripheral view in the video- a driver would have seen the other car much earlier than the video suggests.

As for the second one, looks like the other car just passed in front of it.

Not if a big car is next to you. And even then many people wouldn't be able to react. We can argue this case, but that collision avoidance overall is a very helpful feature is pretty clear.

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