As I've noted in other discussion threads here, I work in a related field (computer-vision, object-detection, recognition) and I couldn't agree more with Dr. Mitchell and Dr. Cummings. A good related read that is linked to in the original article is this one:
How do you teach a car that a snowman won’t walk across the road? – Melanie Mitchell | Aeon Ideas
There is a
HUGE gap between where we are and where we need to get for truly autonomous self-driving and as alluded to in this article, that requires huge, fundamental leaps in the field of AI / ML and there currently isn't anything even remotely on the horizon that shows any promise of solving these problems. Currently, ML systems using CNNs, RNNs, or Vision Transformers or whatever the latest and greatest tech is, can all be fundamentally reduced to being dumb building blocks that do a basic job with no "smarts" to them. Need to detect STOP signs?... train on thousands of images of STOP signs and then your network will do okay. Need to still detect it when a person is holding one up, or when it is partially occluded by a tree? Well, collect and label a whole bunch of unique instances of those scenarios, and after all that effort you have a slightly more robust STOP sign detector. Oops, now your fantastic STOP sign detector is detecting a STOP sign painted on the back of a van. What do you do now?
The answer, is not train your network not to detect stop-signs on vans. If you do that, you will also train your network not to ping on STOP signs that look very similar to the painted STOP sign in the examples you trained it on as non-stop signs. What you really want, is a "smarter" algorithm that can reason about the world. That understands the scene, that knows that the STOP sign is painted on the back of a van and isn't a "real" stop-sign. It is just another example of what Dr. Mitchell talks about in the article I linked above. Now sure, you can come up with heuristics and hacky logic to try and account for this one edge-case, but the fact of the matter is that there will always be an infinitely large long-tail of scenarios where you need something "smarter", with common-sense about how the world works to actually reason about the perception of the scene and make reasonable decisions. Currently, there isn't even a hint of the field of AI being remotely close to achieving this. Hence the DARPA program to try and train up algorithms to achieve a level of cognitive capabilities to match an 18-month old!
Waymo and others are trying to hack it by controlling things as best they can, relying on as many crutches as they can to avoid having to solve these harder problems, and I think they will and have gotten quite far with this approach, but I just don't see these ever working in a general sense for the very same reasons described above and in the articles. I stay away from the main Autonomous driving thread because some people are extremely opinionated and mostly seem to opine from a place of wishful thinking, rather than any basis in the facts of where the current state of ML and AI really is. Personally, I don't think L5 FSD will happen without huge leaps in the field of AI and ML. I don't even see any reason for optimism that these leaps could possibly happen in the next 5 years. As a practitioner in this field, I honestly have seen almost nothing interesting and of real value come out of research in the past few years. There is a lot of hype and a lot of crank turning and tweaking and performing incrementally better at some basic task on some basic dataset like COCO/Imagenet, but there has been nothing that gets us any closer to moving past training dumb as doorknobs detectors and classifiers.
Now personally, I just want a really good AP experience as an aid to me as a driver, and Tesla already has something pretty good, and I think Tesla and others can make fantastic AP aids using current sensor tech and ML/Computer-vision algorithms and capabilities. I do feel terrible for everyone who has been hoodwinked into spending money on FSD. It is just outrageous that this happened at all and while I want Tesla to succeed in the long-run, I absolutely want to see them raked over the coals for their FSD snake oil.
I think with the current tech on hand, and the current state of incremental advances, we would either need all cars to be on some sort of mesh-network for truly L5 autonomous self-driving (highly unlikely that ever happens), or we will need to make our peace with having less capable "self-driving", whether that be being restricted to well-controlled, geofenced areas, or highways, or only regions with up-to-date HD maps, or just always requiring an attentive driver at the wheel. Perhaps we will get to reliable L4 without too many restrictions, but even that seems pretty iffy to me at the moment.