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Tesla Full Self Driving Is Now 'End-To-End AI'
(odysee.com)
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this post was submitted on 03 Sep 2023
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I wonder what happens when the car is on a collision course with a golden retriever and the only way not to hit it would be to damage the car. Or same scenario, but the only way not to hit it, is it to hit an 07 Carolla parked on the side of the road. Not saying humans have superior judgement... just wondering if it will be programmed by the theory of actuarial of philosophical science.
That makes me think- will the AI see a kid that's about to run out from behind a parked car? As a human, if I see a kid run from the house into a row of parked cars, I know he's still there and will slow down before I get there. But would self driving make that same leap of logic? I'm not sure what the range and capabilities of self driving cars are right now in terms of scanning, but hopefully it would be smart enough to take preventative measures
Right now, car AI has trouble both with kids and non-white persons. That said, when it comes to the things it is good at detecting, the cars respond much more quickly. This came up when an official asked about how it detects brake lights, and the project advisor (from Google, I think) explained that the car doesn't worry about break lights but instantly detects when a car ahead of it rapidly decelerates, and responds immediately.
I'm pretty sure we can get cars smart enough and sharp enough to drive better than humans. But the recent incident in San Francisco where Cruise driverless taxis blocked an ambulance with a patient in critical condition (resulting in their death), suggests to me we underestimated the layers of logistics necessary to make cars truly autonomous.
Randal Munroe listed a few more incidents we can expect (Obligatory XKCD).
According to other commentors, the need will never arise because the AI cars will be programmed so well it's impossible to have accidents ๐... now I see why FSD will never become a reality.
Good question. Neural networks are modelled after how brains learn and process information, so it's certainly theoretically possible for a neural network (or other machine learning algorithm) to make inferences like that, just like how you've learned them with years of experience.
The biggest challenge in any machine learning is finding enough labelled training data. In fact, a friend of mine contributed to a paper in which (no joke) GTA V was used to generate labelled training data for an automous vehicle. Because it's a game engine, every object in the game is already digitized, and the 3D modelling is accurate enough to be useful, at least. This vehicle used LIDAR so the actual shaders and such didn't matter as much as the 3D point cloud.
I doubt it. Germany has already implemented (considering implementing) regulations regarding the ethics of autonomous vehicles. As it is, cars are simply trying not to collide with anything and given their reflexes and perception are way faster and more accurate than human beings, they have a better chance of saving both the dog and the other car.
That said, one of the problems we're seeing with smart devices (that is devices that are software run rather than controlled by simple mechanics) is that companies are keen to abuse the power that gives them, hence the whole John Deere tractors debacle and the development of right-to-repair laws. Also, some BMWs require rental of some of their features (such as seat warmers) which seems to me as less than ethical.
So I hope we'll get to a point where not only is it anyone's right to jailbreak their devices (including a self-driving car) but there will be several FOSS options we can choose from. And that means someone who programmed them may actually find a process-layer in which hazard prioritization or victim prioritization is considered.
It is certainly an entertaining idea of speculative fiction that an aggressive driver package is developed, gets popular and then causes a rise in traffic accidents. More likely would be software packages that allow the vehicle to operate despite self-test failures, again leading to a higher traffic collision rate.
That's already a key plot point in the show Upload (which I really enjoyed)
There are many such hypothetical scenarios based on the trolley problem, but the real answer is that a good self driving system will never end up in that situation in the first place.
So as a dev, you just program to not let that situation arise, then you won't need to program a solution for that.