[c06n]

> Software should try to learn from human drivers

Yeah, that doesn't work though. Basically because you would need to have an excellent situation representation to really understand the drivers' reactions to outside events. But that does not exist.

Perception and situation representation are key to mastering the driving task, and they both differ greatly between humans and machines.

[Silhouette]

Basically because you would need to have an excellent situation representation to really understand the drivers' reactions to outside events. But that does not exist.

This is the #1 reason I'm sceptical about self-driving cars becoming ubiquitous any time soon. Clearly they have potential advantages over a human driver in terms of not being tired or distracted, better sensors and better reaction times, but their judgement in any given situation will always be a function of some predetermined inputs. It's a brute force approach.

Until a self-driving car can recognise a pub door opening around throwing-out time where a drunk patron is about to stumble out into the road from a hidden position, or that it's about to pass a park and a nearby school just finished for the day so kids will be kicking balls around and running across the road to join their friends, or that the recent weather conditions make black ice likely and the cyclist it's about to pass doesn't seem very steady, and take corresponding actions to reduce both the risk and the consequences of a collision, it's going to take a lot of brute force to outperform an experienced and reasonably careful human driver.

In short, reacting to an emergency 100ms faster than a human driver is good, but sufficient situational awareness and forward planning that you were never in the emergency situation in the first place is better.

[ThrustVectoring]

It doesn't need to outperform an experienced and reasonably careful human driver to be a significant net benefit to society. All it needs to do is get the most dangerous 10-20% of the population out from behind the wheel.

[Nomentatus]

It's occurred to me lately that we probably need to get autonomous vehicles on the road even a bit earlier than this, since delaying how quickly the safety learning curve is mounted has a long-term cost in lives, too.

[ryandvm]

Bingo. This is the difference between "intelligence" and "artificial intelligence". AI as we know it today is pattern recognition. There is no ability to form even the most basic of concepts. They may have incredible sensors, but these driverless cars hardly have the intelligence of a dragonfly.

[perfmode]

I challenge you to prove that you are capable of more than recognizing patterns.

[ryandvm]

Okay, for the sake of argument let's suppose that I was clever enough to come up with the famous Grandfather Paradox of time travel. Certainly no one has observed such an event before - or anything like it. I would posit that it takes more than pattern recognition to build the necessary mental concepts to design, much less understand, such a thought experiment.

In fairness, I will concede that pattern recognition is crucial to intelligence. I would clarify my earlier position by saying that pattern recognition alone can only get you so far. Intelligence is the process of taking data, recognizing patterns, constructing multi-layered concepts and models from those patterns, and then being able to simulate and extrapolate potential outcomes based on varying inputs.

The inability of modern AI to build complex concepts from they patterns they observe is why I know to slow down my car on a Halloween night in a residential neighborhood and a self-driving Uber doesn't.

[perfmode]

Your Halloween example is you recognizing patterns:

- on Halloween there are more children on the road than usual - children are more likely to disobey traffic laws

It’s quite possible that waymo cars are already capable of this.

[spacehome]

You might perform well in those scenarios, but a lot of people in many parts of the world do not.