On one hand I understand that it is a monumental advance in technology.
On the other hand a computer can recognize a unique face from pretty far.
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It’s rife with flaws. It can’t make a decision that will be less impactful compared with a human.
Also, how does a person teach a car to make decisions in moments of a crash? If a child walks out in front of a car but the alternative to the child surviving is hitting a pole straight on and the driver won’t survive… People have to teach the computer how to make those decisions. We studied that in my automotive engineering classes and it was terrifying.
Think that scene in IRobot where Will Smith wanted to save the drowning girl but the robot refused to because he had a better chance of living.
A computer can recognize a face assuming it has a clear view of the face and has the time to process it. But that’s really not the problem.
If you are in your self driving car and it sees a blob on the road, what is that blob?
A piece of cardboard that’s blown onto the road? An animal that’s wandered onto the road?
Is it a rock that’s fallen off a truck?
Did a person slip trying to cross the road?
Did something fall off someone’s car?
What do you do when it’s raining/snowing so hard you can’t see 3ft in front of you?
What happens if the sensors are dirty and not able to get a reading clearly?
What if the road is incredibly worn that it’s nearly impossible to see the lines?
What if the roads are covered with an inch of snow?
You are in a moving vehicle, it only has fractions of a second to see, recognize and react. Being able to accurately recognize hazards is incredibly difficult because a false reading could be incredibly dangerous to the driver or anyone in the area.
Good self-driving cars can likely outperform a large majority of human drivers in good conditions. The other parts that it doesn’t get right too well (by not being able to think like a human can) can cause *massive* problems when you’re driving around large vehicles in unpredictable environments.
They also can work even better when they can communicate with the cars around them as a sort of “hive mind” (warning of traffic conditions ahead, emergency vehicles, etc). With such few (by total percentage) self-driving cars running on the road, this “hive mind” doesn’t work too well.
Add in less predictable drivers (humans instead of “hive mind” from above) to throw a few wrenches in there and it’ll be awhile before a majority of self-driving is approved for wide enough usage to overcome some of the above issues.
Road conditions can cause issues too – any significant amount of snow can very much disable self-driving because the car can’t see a road at all, whereas a human can estimate where the road should be to make it through when necessary.
over the course of the last decades, we have learned that within a closed system – with concrete parameters and explicit rules/rewards, a computer will almost always outperform a human. this is why computers are, like you mentioned, incredibly good at facial recognition, video games, chess, etc.
however, the problem of driving is much more nuanced, and complicated. the act driving involves a ton of moving parts (changing lanes, watching for pedestrians, reacting to other drivers, changing lanes, knowing the rules of the road, speed limits, highway construction, etc. etc.) tesla and comma.ai as well as some other companies have already developed self driving systems that work, and are being used by people on the roads daily. but the real problem of self driving is building true, level 5 systems which are unquestionably better than a human. so it’s not a matter of just building self driving software, it’s about building incredibly good self driving software that can operate without human intervention/oversight.
perhaps we can, and perhaps we can’t. regardless, the challenge requires us to build artificial intelligence systems that are generalized and incredibly adaptable to any number of problems that can arise on the road. this is a very difficult computer science problem that many people are working on, and many dollars are being invested into – it will be fun to see how it plays out over the next decade.
Having self driving in a controlled environment (akin to a laboratory environment in other fields of research) can be done now. But, we are still long ways away from self driving as an consumer product, that works everyday, everywhere, and, makes money for the companies that are selling it.
To get there using machine leaning, we still need to collect a lot of data on things that can occur on the road, and the right ways to respond to each of those conditions.
Then there is the matter of making money. To get there faster, we can always pile on more sensors and more expensive sensors, as well as powerful expensive computers to process those data. But are consumers willing to spend 10’s of thousands more per car to get the self driving feature?
Then there is the matter of engineering. All of those new equipment that has not been used in cars before, now has to work every where a car can go, and over the life duration that a car is expected to last, and have a low enough failure rate as to not cause a stir over millions of cars sold. That is not easy.
But never the less, I don’t think that there is any doubt we will eventually have self driving. Unlike human drivers where each person has to learn from scratch, get better, then get worse as we age, and lastly lose it all as we die, the AI behind self driving will never get worse.
I think we will see self operating trains before cars, but there is a great deal of issues to work out there too
The “recognize a unique face” hurdle was a huge one that computer scientists have been working on for almost 75 years at this point. Image recognition in general is a hard problem for us to come up with an algorithmic solution for, because it isn’t something that humans know through an algorithm – we have built-in brain structures to deal with image processing and through heuristics of a lifetime of doing that plus a lifetime of living and existing in the world, we’re able to tell the difference between a sheep and a cloud, while a computer lacks a lot of that context.
There are many specific examples but it boils down to you can’t control the outside world. Driving is easy. In controlled environments like mining, ag and industrial they’re swarming with autonomous.
I don’t think self driving cars will be common until the roads are built specifically for that purpose. [u/NDZ188](https://www.reddit.com/r/explainlikeimfive/comments/spl4ec/eli5_what_makes_self_driving_so_hard/hwfx6p5/) gives a pretty good rundown of some of the difficulties. I don’t see most of those being solved until we build roads that computers can understand. Things like lane markings and stop signs would have to identify themselves to the car computers.
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