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Developers have been teaching AI too much and it has nothing left to learn.

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DeepMind's new self-taught Go-playing program is making moves that other players describe as "alien" and "from an alternate dimension."

It was a tense summer day in 1835 Japan. The country's reigning Go player, Honinbo Jowa, took his seat across a board from a 25-year-old prodigy by the name of Akaboshi Intetsu. Both men had spent their lives mastering the two-player strategy game that's long been popular in East Asia. Their face-off, that day, was high-stakes: Honinbo and Akaboshi represented two Go houses fighting for power, and the rivalry between the two camps had lately exploded into accusations of foul play.

Little did they know that the match-now remembered by Go historians as the "blood-vomiting game"-would last for several grueling days. Or that it would lead to a grisly end.

Early on, the young Akaboshi took a lead. But then, according to lore, "ghosts" appeared and showed Honinbo three crucial moves. His comeback was so overwhelming that, as the story goes, his junior opponent keeled over and began coughing up blood. Weeks later, Akaboshi was found dead. Historians have speculated that he might have had an undiagnosed respiratory disease.

It makes a certain kind of sense that the game's connoisseurs might have wondered if they'd seen glimpses of the occult in those three so-called ghost moves. Unlike something like tic-tac-toe, which is straightforward enough that the optimal strategy is always clear-cut, Go is so complex that new, unfamiliar strategies can feel astonishing, revolutionary, or even uncanny.

Unfortunately for ghosts, now it's computers that are revealing these goosebump-inducing moves.
One gets the sense that an alien civilization has dropped a cryptic guidebook in our midst.
As many will remember, AlphaGo-a program that used machine learning to master Go-decimated world champion Ke Jie earlier this year. Then, the program's creators at Google's DeepMind let the program continue to train by playing millions of games against itself. In a paper published in Nature earlier this week, DeepMind revealed that a new version of AlphaGo (which they christened AlphaGo Zero) picked up Go from scratch, without studying any human games at all. AlphaGo Zero took a mere three days to reach the point where it was pitted against an older version of itself and won 100 games to zero.

Now that AlphaGo's arguably got nothing left to learn from humans-now that its continued progress takes the form of endless training games against itself-what do its tactics look like, in the eyes of experienced human players? We might have some early glimpses into an answer.

AlphaGo Zero's latest games haven't been disclosed yet. But several months ago, the company publicly released 55 games that an older version of AlphaGo played against itself. (Note that this is the incarnation of AlphaGo that had already made quick work of the world's champions.) DeepMind called its offering a "special gift to fans of Go around the world."

Since May, experts have been painstakingly analyzing the 55 machine-versus-machine games. And their descriptions of AlphaGo's moves often seem to keep circling back to the same several words: Amazing. Strange. Alien.

"They're how I imagine games from far in the future," Shi Yue, a top Go player from China, has told the press. A Go enthusiast named Jonathan Hop who's been reviewing the games on YouTube calls the AlphaGo-versus-AlphaGo face-offs "Go from an alternate dimension." From all accounts, one gets the sense that an alien civilization has dropped a cryptic guidebook in our midst: a manual that's brilliant-or at least, the parts of it we can understand.
"You have to be ready to deny a lot of the things that we've believed and that have worked for us."
Will Lockhart, a physics grad student and avid Go player who codirected The Surrounding Game (a documentary about the pastime's history and devotees) tried to describe the difference between watching AlphaGo's games against top human players, on the one hand, and its self-paired games, on the other. (I interviewed Will's Go-playing brother Ben about Asia's intensive Go schools in 2016.) According to Will, AlphaGo's moves against Ke Jie made it seem to be "inevitably marching toward victory," while Ke seemed to be "punching a brick wall." Any time the Chinese player had perhaps found a way forward, said Lockhart, "10 moves later AlphaGo had resolved it in such a simple way, and it was like, 'Poof, well that didn't lead anywhere!'"

By contrast, AlphaGo's self-paired games might have seemed more frenetic. More complex. Lockhart compares them to "people sword-fighting on a tightrope."

Expert players are also noticing AlphaGo's idiosyncrasies. Lockhart and others mention that it almost fights various battles simultaneously, adopting an approach that might seem a bit madcap to human players, who'd probably spend more energy focusing on smaller areas of the board at a time. According to Michael Redmond, the highest-ranked Go player from the Western world (he relocated to Japan at the age of 14 to study Go), humans have accumulated knowledge that might tend to be more useful on the sides and corners of the board. AlphaGo "has less of that bias," he noted, "so it can make impressive moves in the center that are harder for us to grasp."

Also, it's been making unorthodox opening moves. Some of those gambits, just two years ago, might have seemed ill-conceived to experts. But now pro players are copying certain of these unfamiliar tactics in tournaments, even if no one fully understands how certain of these tactics lead to victory. For example, people have noticed that some versions of AlphaGo seem to like playing what's called a three-three invasion on a star point, and they're experimenting with that move in tournaments now too. No one's seeing these experiments lead to clearly consistent victories yet, maybe because human players don't understand how best to follow through.

Some moves AlphaGo likes to make against its clone are downright incomprehensible, even to the world's best players. (These tend to happen early on in the games-probably because that phase is already mysterious, being farthest away from any final game outcome.) One opening move in Game One has many players stumped. Says Redmond, "I think a natural reaction (and the reaction I'm mostly seeing) is that they just sort of give up, and sort of throw their hands up in the opening. Because it's so hard to try to attach a story about what AlphaGo is doing. You have to be ready to deny a lot of the things that we've believed and that have worked for us."

Like others, Redmond notes that the games somehow feel "alien." "There's some inhuman element in the way AlphaGo plays," he says, "which makes it very difficult for us to just even sort of get into the game."
"Generally the way humans learn Go is that we have a story."
Still, Redmond thinks there are moments when AlphaGo (at least its older version) might not necessarily be enigmatically, transcendently good. Moments when it might possibly be making mistakes, even. There are patterns of play called joseki-series of locally confined attacks and responses, in which players essentially battle to a standstill until it only makes sense for them to move to another part of the board. Some of these joseki have been analyzed and memorized and honed over generations. Redmond suspects that people may still be better at responding in a few of these patterns, because people have analyzed them so intensely. (It's hard to tell though, because in the AlphaGo-versus-AlphaGo games, both "copies" of the program seem to avoid getting into these joseki in the first place.)

It's not far-fetched that AlphaGo may still be choosing suboptimal moves-making "mistakes," if you will. You can see Go as a massive tree made of thousands of branches representing possible moves and countermoves. Over generations, Go players have identified certain clusters of branches that seem to work really well. And now that AlphaGo's come along, it's finding even better options. Still, huge swaths of the tree might yet be unexplored. As Lockhart put it, "It could be possible that a perfect God plays [AlphaGo] and crushes it. Or maybe not. Maybe it's already there. We don't know."

From his home base in Chiba, Japan, Redmond says, he has been studying AlphaGo's self-paired games more or less nonstop for the past four months. He's been videotaping his commentaries on each game and putting out one video per week on the American Go Association's YouTube channel. One of his biggest challenges in these videos, he says, is to "attach stories" to AlphaGo's moves.

"Generally the way humans learn Go is that we have a story," he points out. "That's the way we communicate. It's a very human thing."

After all, people can identify and discuss shapes and patterns. Or we can argue with each other about the reasons a killer move won the game. Take a basic example: When teaching beginners, a Go instructor might point out an odd-looking formation of stones resembling a lion's mouth or a tortoiseshell (among other patterns) and discuss how best to play in these situations. In theory, AlphaGo could have something akin to that knowledge: A portion of its neural network might hypothetically be "sounding an alarm," so to speak, whenever that lion's-mouth pattern appears on the board. But even if that were the case, AlphaGo isn't equipped to turn this sort of knowledge into any kind of a shareable story. So far, that task is one that still falls to people.

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The AI That Has Nothing to Learn From Humans

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DeepMind's new self-taught Go-playing program is making moves that other players describe as "alien" and "from an alternate dimension." It was a tense summer day in 1835 Japan. The country's reigning Go player, Honinbo Jowa, took his seat across a board from a 25-year-old prodigy by the name of Akaboshi Intetsu.

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“The five levels

Level 0: Automated system has no vehicle control, but may issue warnings.

Level 1: Driver must be ready to take control at any time. Automated system may include features such as Adaptive Cruise Control (ACC), Parking Assistance with automated steering, and Lane Keeping Assistance (LKA) Type II in any combination.

Level 2: The driver is obliged to detect objects and events and respond if the automated system fails to respond properly. The automated system executes accelerating, braking, and steering. The automated system can deactivate immediately upon takeover by the driver.

Level 3: Within known, limited environments (such as freeways), the driver can safely turn their attention away from driving tasks, but must still be prepared to take control when needed.

Level 4: The automated system can control the vehicle in all but a few environments such as severe weather. The driver must enable the automated system only when it is safe to do so. When enabled, driver attention is not required.

Level 5: Other than setting the destination and starting the system, no human intervention is required. The automatic system can drive to any location where it is legal to drive and make its own decision.”

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Perhaps through this essay I will get the bee out of my bonnet that fully driverless cars are a lot further off than many techies, much of the press, and even many auto executives seem to think. They will get here and human driving will probably disappear in the lifetimes of many people reading this, but it is not going to all happen in the blink of an eye as many expect. There are lots of details to be worked out.

In my very first post on this blog I talked about the unexpected consequences of having self driving cars. In this post I want to talk about about a number of edge cases, which I think will cause it to be a very long time before we have level 4 or level 5 self driving cars wandering our streets, especially without a human in them, and even then there are going to be lots of problems.

First though, we need to re-familiarize ourselves with the generally accepted levels of autonomy that every one is excited about for our cars.

Here are the levels from the autonomous car entry in Wikipedia which attributes this particular set to the SAE (Society of Automotive Engineers):

Level 0: Automated system has no vehicle control, but may issue warnings.

Level 1: Driver must be ready to take control at any time. Automated system may include features such as Adaptive Cruise Control (ACC), Parking Assistance with automated steering, and Lane Keeping Assistance (LKA) Type II in any combination.

Level 2: The driver is obliged to detect objects and events and respond if the automated system fails to respond properly. The automated system executes accelerating, braking, and steering. The automated system can deactivate immediately upon takeover by the driver.

Level 3: Within known, limited environments (such as freeways), the driver can safely turn their attention away from driving tasks, but must still be prepared to take control when needed.

Level 4: The automated system can control the vehicle in all but a few environments such as severe weather. The driver must enable the automated system only when it is safe to do so. When enabled, driver attention is not required.

Level 5: Other than setting the destination and starting the system, no human intervention is required. The automatic system can drive to any location where it is legal to drive and make its own decision.

There are many issues with level 2 and level 3 autonomy, which might make them further off in the future than people are predicting, or perhaps even forever impractical due to limitations on how quickly humans can go from not paying attention to taking control in difficult situations. Indeed as outlined in this Wired story many companies have decided to skip level 3 and concentrate on levels 4 and 5. The iconic Waymo (formerly Google) car has no steering wheel or other conventional automobile controls-it is born to be a level 4 or level 5 car. [This image is from Wikipedia.]

So here I am going to talk only about level 4 and level 5 autonomy, and not really make a distinction between them. When I refer to an "autonomous car" I'll be talking about ones with level 4 or level 5 autonomy.

I will make distinctions between cars with conventional controls so that they are capable of being driven by a human in the normal way, and cars like the Waymo one pictured above with no such controls, and I will refer to that as an unconventional car. I'll use those two adjectives, conventional, and unconventional, for cars, and then distinguish what is necessary to make them practical in some edge case circumstances.

I will also refer to gasoline powered driverless cars versus all electric driverless cars, i.e., gasoline vs. electric.

Ride-sharing companies like Uber are putting a lot of resources into autonomous cars. This makes sense given their business model as they want to eliminate the need for drivers at all, thus saving their major remaining labor cost. They envision empty cars being summoned by a customer, driving to wherever that customer wants to be picked up, with absolutely no one in the car. Without that, having the autonomy technology doesn't make sense to this growing segment of the transportation industry. I'll refer to such an automobile, with no-one in it as a Carempty. In contrast, an autonomous car which has a conscious person in it, whether it is an unconventional car and they can't actually drive it in the normal way, or whether it is a conventional car but they are not at all involved in the driving, perhaps sitting in the back seat, as Careless, as presumably that person shouldn't have to care less about the driving other than indicating where they want to go.

So we have both an unconventional and a conventional Carempty and Careless, and perhaps they are gasoline or electric.

Many of the edge cases I will talk about here are based on the neighborhood in which I live, Cambridgeport in Cambridge, Massachusetts. It is a neighborhood of narrow one way streets, packed with parked cars on both sides of the road so that it is impossible to pass by if a car or truck stopped in the road. A few larger streets are two way, and some of them have two lanes, one in each direction, but at least one nearby two way street only has one lane-one car needs to pull over, somehow, if two cars are traveling on the opposite direction (the southern end of Hamilton Street in the block where the "The Good News Garage" of the well known NPR radio brothers "Click and Clack" is located).

HOW MUCH DRIVING CAN A NON-DRIVER DO?

In a conventional Careless a licensed human can take over the driving when necessary, unless say it is a ride sharing car, and in that case humans might be locked out of using the controls directly. For an unconventional Careless, like one of the Waymo cars pictured above, the human can not take over directly either. So a passenger in a conventional ride-sharing car, or in an unconventional car are in the same boat. But how much driving can that human do?

In both cases the human passenger needs to be able to specify the destination. For a ride-sharing service that may have been done on a smart phone app when calling for the service. But once in the car the person may want to change their mind, or demand that the car take a particular route-I certainly often do that with less experienced drivers who are clearly going a horrible way, often at the suggestion of their automated route planners. Should all this interaction be via an app? I am guessing, given the rapid improvements in voice systems, such as we see in the Amazon Echo, or the Google Home, we will all expect to be able to converse by voice with any autonomous car that we find ourselves in.

We'll ignore for the moment a whole bunch of teenagers each yelling instructions and pranking the car. Let's just think about a lone sensible mature person in the car trying to get somewhere.

Will all they be able to do is give the destination and some optional route advice, or will they be able to give more detailed instructions when the car is clearly screwing up, or missing some perceptual clue that the occupant can clearly recognize? The next few sections give lots of examples from my neighborhood that are going to be quite challenging for autonomous cars for many years to come, and so such advice will come in handy.

In some cases the human might be called upon to, or just wish to, give quite detailed advice to the car. What if they don't have a driver's license? Will the be guilty of illegally driving a car in that case? How much advice should they be allowed to give (spoiler alert, the car might need a lot in some circumstances)? And when should the car take the advice of the human? Does it need to know if the person in the car talking to it has a driver's license?

Read on.

WHAT TO DO ABOUT A BLOCKED ROAD

In my local one-way streets the only thing to do if a car or other vehicle is stopped in the travel lane is to wait for it to move on. There is no way to get past it while it stays where it is.

The question is whether to toot the horn or not at a stopped vehicle.

Why would it be stopped? It could be a Lyft or an Uber waiting for a person to come out of their house or condominium. A little soft toot will often get cooperation and they will try to find a place a bit further up the street to pull over. A loud toot, however, might cause some ire and they will just sit there. And if it is a regular taxi service then no amount of gentleness or harshness will do any good at all. "Screw you" is the default position.

Sometimes a car is stopped because the driver is busy texting, most usually when they are at an intersection, had to wait for some one to the cross in front of them, their attention wandered, they started reading a text, and now they are texting and have forgotten that they are in charge of an automobile. From behind one can often tell what they are up to by noticing their head inclination, even from inside the car behind. A very gentle toot will usually get them to move; they will be slightly embarrassed at their own illegal (in Massachusetts) behavior.

And sometimes it is a car stopped outside an eldercare residence building with someone helping a very frail person into or out of the car. Any sort of toot from a stopped car behind is really quite rude in these circumstances, distressing for the elderly person being helped, and rightfully ire raising for the person taking care of that older person.

Another common case of road blockage is that a garbage truck stopped to pick up garbage. There are actual two varieties, one for trash, and one for recyclables. It is best to stop back a bit further from these trucks than from other things blocking the road, as people will be running around to the back of the truck and hoisting heavy bins into it. And there is no way to get these trucks to move faster than they already are. Unlike other trucks, they will continue to stop every few yards. So the best strategy is to follow, stop and go, until the first side street and take that, even if, as it is most likely a one-way street, it sends you off in a really inconvenient direction.

Yet a third case is a delivery truck. It might be a US Postal Service truck, or a UPS or Fedex truck, or sometimes even an Amazon branded truck. Again tooting these trucks makes absolutely no difference-often the driver is getting a signature at a house, or may be in the lobby of a large condominium complex. It is easy for a human driver to figure out that it is one of these sorts of trucks. And then the human knows that it is not so likely to stop again really soon, so staying behind this truck once it moves rather than taking the first side street is probably the right decision.

If on the other hand it is a truck from a plumbing service, say, it is worth blasting it with your horn. These guys can be shamed into moving on and finding some sort of legal parking space. If you just sit there however it could be many minutes before they will move.

A Careless automobile could ask its human occupant whether it should toot. But should it make a value judgement if the human is spontaneously demanding that it toot its horn loudly?

A Carempty automobile could just never toot, though the driver in a car behind it might start tooting it, loudly. Not tooting is going to slow down Carempties quite a bit, and texting drivers just might not care at all if they realize it is a Carempty that is showing even a little impatience. And should an autonomous car be listening for toots from a car behind it, and change its behavior based on what it hears? We expect humans to do so. But are the near future autonomous cars going to be so perfect already that they should take no external advice?

Now if Carempties get toot happy, at least in my neighborhood that will annoy the residents having tooting cars outside their houses at a much higher level than at the moment, and they might start to annoy the human drivers in the neighborhood.

The point here is that there is a whole lot of perceptual situations that a an autonomous vehicle will need to recognize if it is to be anything more than a clumsy moronic driver (an evaluation us locals often make of each other in my neighborhood...). As a class, autonomous vehicles will not want to get such a reputation, as the humans will soon discriminate against them in ways subtle and not so subtle.

Maps DOn'T Tell the Whole Story

Recently I pulled out of the my garage and turned right onto the one way street that runs past my condominium building, and headed to the end of my single block street, expecting to turn right at a "T" junction onto another one way street. But when I got there, just to the right of the intersection the street was blocked by street construction, cordoned off, and with a small orange sign a foot or so off the ground saying "No Entry".

The only truly legal choice for me to make was to stop. To go back from where I had come I needed to travel the wrong way on my street, facing either backwards or forwards, and either stopping at my garage, or continuing all the way to the street at the start of my street. Or I could turn left and go the wrong way on the street I had wanted to turn right onto, and after a block turn off onto a side street going in a legal direction.

A Careless might inform its human occupant of the quandry and ask for advice on what to do. That person might be able to do any of the social interactions needed should the Careless meet another car coming in the legal direction under either of these options.

But Carempty will need some extra smarts for this case. Either hordes of empty cars eventually pile up at this intersection or each one will need to decide to break the law and go the wrong way down one of the two one way streets-that is what I had to do that morning.

The maps that a Carempty has won't help it a whole lot in this case, beyond letting it know the minimum distance it is going to have to be in a transgressive state.

Hmmm. It is OK for a Carempty to break the law when it decides it has to? Is it OK for a Careless to break the law when its human occupant tells it to? In the situation I found myself in above, I would certainly have expected my Careless to obey me and go the wrong way down a one way street. But perhaps the Careless shouldn't do that if it knows that it is transporting a dementia patient.

How are the police supposed to interact with a Carempty?

While we have both driverful and driverless cars on our roads I think the police are going to assume that as with driverful cars they can interact with them by waving them through an intersection perhaps through a red light, stopping them with a hand signal at a green light, or just to allow someone to cross the road.

But besides being able to understand what an external human hand signaling them is trying to convey, autonomous cars probably should try to certify in some sense whether the person that is giving them those signals is supposed to be doing so with authority, with politeness, or with malice. Certainly police should be obeyed, and police should expect that they will be. So the car needs to recognize when someone is a police officer, no matter what additional weather gear they might be wearing. Likewise they should recognize and obey school crossing monitors. And road construction workers. And pedestrians giving them a break and letting them pass ahead of them. But should they obey all humans at all times? And what if in a Careless situation their human occupant tells them to ignore the taunting teenager?

Sometimes a police officer might direct a car to do something otherwise considered illegal, like drive up on to a sidewalk to get around some road obstacle. In that case a Carempty probably should do it. But if it is just the delivery driver whose truck is blocking the road wanting to get the Carempty to stop tooting at them, then probably the car should not obey, as then it could be in trouble with the actual police. That is a lot of situational awareness for a car to have to have.

Things get more complicated when it is the police and the car is doing something wrong, or there is an extraordinary circumstance which the car has no way of understanding.

In the previous section we just established that autonomous cars will sometimes need to break the law. So police might need to interact with law breaking autonomous cars.

One view of the possible conundrum is this cartoon from the New Yorker. There are two instantly recognizable Waymo style self driving cars, with no steering wheels or other controls, one a police car that has just pulled over the other car. They both had people in them, and the cop is asking the guy in the car that has just been pulled over, "Does your car have any idea why my car pulled it over?".

If an autonomous car fails to see a temporary local speed sign and gets caught in a speed trap, how is it to be pulled over? Does it need to understand flashing blue lights and a siren, and does it do the pull to the side in a way that we have all done, only to be relieved when we realize that we were not the actual target?

And getting back to when I had to decide to go the wrong way down a one way street, what if a whole bunch of Carempties have accumulated at that intersection and a police officer is dispatched to clear them out? For driverful cars a police officee might give a series of instructions and point out in just a few seconds who goes first, who goes second, third, etc. That is a subtle elongated set of gestures that I am pretty sure no deep learning network has any hope at the moment of intpreting, of fully understanding the range of possibilities that a police officer might choose to use.

Or will it be the case that the police need to learn a whole new gesture language to deal with driverless cars? And will all makes all understand the same language?

Or will we first need to develop a communication system that all police officers will have access to and which all autonomous cars will understand so that police can interact with autonomous cars? Who will pay for the training? How long will that take, and what sort of legislation (in how many jurisdictions) will be required?

Getting Towed

A lot of cars get towed in Cambridge. Most streets get cleaned on a regular schedule (different sides of the same street on different days), and if your car is parked there at 7am you will get towed-see the sign in the left image. And during snow emergencies, or without the right sticker/permit you might get towed at any time. And then there are pop-up no parking signs, partially hand written, that are issued by the city on request for places for moving vans, etc. Will our autonomous cars be able to read these? Will they be fooled by fake signs that residents put up to keep pesky autonomous cars from taking up a parking spot right outside their house?

If an unconventional Carempty is parked on the street, one assumes that it might at any time start up upon being summoned by its owner, or if it is a ride-share car when its services are needed. So now imagine that you are the tow truck operator and you are supposed to be towing such a car. Can you be sure it won't try driving away as you are crawling under it connect the chains, etc., to tow it? If a human runs out to move their car at the last minute you can see when things are going to start and adjust. How will it work with fully autonomous cars?

And what about a Carempty that has a serious breakdown, perhaps in its driving system, and it just sits there and can no longer safely move itself. That will need to be towed most likely. Can the tow truck operator have some way to guarantee that it is shut down and will not jump back to life, especially when the owner has not been contactable, to put it in safe mode remotely? What will be the protocols and regulations around this?

And then if the car is towed, and I know this from experience, it is going to be in a muddy lot full of enormous potholes in some nearby town, with no marked parking areas or driving lanes. The cars will have been dumped at all angles, higgledy-piggledy. And the lot is certainly not going have its instantaneous layout mapped by one of the mapping companies, providing the maps that autonomous cars rely on for navigation. To retrieve such a car a human is likely going to have to go do it (and pay before getting it out), but if it is an unconventional car it is certainly going to require some one in it to talk it through getting out of there without angering the lot owner (and again from experience, that is a really easy thing to do-anger the lot owner). Yes, in some distant future tow lots in Massachusetts will be clean, and flat with no potholes deeper than six inches, and with electronic payment systems, and all will be wonderful for our autonomous cars to find their way out.

Don't hold your breath.

OTHER TRICKY SITUATIONS

What happens when a Carempty is involved in an accident? We know that many car companies are hoping that their cars will never be involved in an accident, but humans are dumb enough that as long as there are both human drivers and autonomous cars on the same streets, sometimes a human is going to drive right into an autonomous car.

Autonomous cars will need to recognize such a situation and go through some protocol. There is a ritual when a fender bender happens between two driverful cars. Both drivers stop and get out of their cars, perhaps blocking traffic (see above) and go through a process of exchanging insurance information. If one of the cars is an autonomous vehicle the the human driver can take a photo on their phone (technology to the rescue!) of the autonomous car's license plate. But how is a Carempty supposed to find out who hit it? In the distant future when all the automobile stock on the road have transponders (like current airplanes) that will be relatively easy (though we will need to work through horrendous privacy issues to get there), but for the foreseeable future this is going to be something of a problem.

And what about refueling? If a ride-sharing car is gasoline powered and out giving rides all day, how does it get refueled? Does it need to go back to its home base to have a human from its company put in more gasoline? Or will we expect to have auto refueling stations around our cities? The same problem will be there even if we quickly pass beyond gasoline powered cars. Electric Carempties will still need to recharge-will we need to replace all the electric car recharging stations that are starting to pop up with ones that require no human intervention?

Autonomous cars are likely to require lots of infrastructure changes that we are just not quite ready for yet.

Impacts on the Future of Autonomous Cars

I have exposed a whole bunch of quandaries here for both Carempties and Carelesses. None rise to the moral level of the so called trolley problem (do I kill the one nun or seven robbers?) but unlike the trolley problem variants of these edge cases are very likely to arise, at least in my neighborhood. There will be many other edge case conundrums in the thousands, perhaps millions, of unique neighborhoods around the world.

One could try to have some general purpose principles that cars could reason from in any circumstances, perhaps like Asimov's Three Laws , and perhaps tune the principles to the prevailing local wisdom on what is appropriate or not. In any case there will need to be a lot of codifying of what is required of autonomous cars in the form of new traffic laws and regulations. It will take a lot of trial and error and time to get these laws right.

Even with an appropriate set of guiding principles there are going to be a lot of perceptual challenges for both Carempties and Carelesses that are way beyond those that current developers have solved with deep learning networks, and perhaps a lot more automated reasoning that any AI systems have so far been expected to demonstrate.

I suspect that to get this right we will end up wanting our cars to be as intelligent as a human, in order to handle all the edge cases appropriately.

And then they might not like the wage levels that ride-sharing companies will be willing to pay them.

But maybe not. I may have one more essay on how driverless cars are going to cause major infrastructure changes in our cities, just as the original driverful cars did. These changes will be brought on by the need for geofencing-something that I think proponents are underestimating in importance.

Recall that Isaac Asimov used these laws as a plot device for his science fiction stories, by laying out situations where these seemingly simple and straightforward laws led to logical fallacies that the story proponents, be they robot or human, had to find a way through.

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Perhaps through this essay I will get the bee out of my bonnet that fully driverless cars are a lot further off than many techies, much of the press, and even many auto executives seem to think.

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The main problems shown in this article are that they will be flawed, hacked, or not smart enough without some sort of human engagement. All problems that can be fixed and developed but with the current standings most likely not in this lifetime.

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All the ways the self-driving future won't come to pass

Self-driving cars are coming. Tech giants such as Uber and Alphabet have bet on it, as have old-school car manufacturers such as Ford and General Motors. But even as Google's sister company Waymo prepares to launch its self-driving-car service and automakers prototype vehicles with various levels of artificial intelligence, there are some who believe that the autonomous future has been oversold-that even if driverless cars are coming, it won't be as fast, or as smooth, as we've been led to think. The skeptics come from different disciplines inside and out of the technology and automotive industries, and each has a different bear case against self-driving cars. Add them up and you have a guide to all the ways our autonomous future might not materialize.
Bear Case 1: They Won't Work Until Cars Are as Smart as Humans
Computers have nowhere near human intelligence. On individual tasks, such as playing Go or identifying some objects in a picture, they can outperform humans, but that skill does not generalize. Proponents of autonomous cars tend to see driving as more like Go: a task that can be accomplished with a far-lower-than-human understanding of the world. But in a duo of essays in 2017, Rodney Brooks, a legendary roboticist and artificial-intelligence researcher who directed the MIT Computer Science and Artificial Intelligence Laboratory for a decade, argued against the short-term viability of self-driving cars based on the sheer number of "edge cases," i.e., unusual circumstances, they'd have to handle.
Read: The AI that has nothing to learn from humans
"Even with an appropriate set of guiding principles, there are going to be a lot of perceptual challenges ... that are way beyond those that current developers have solved with deep learning networks, and perhaps a lot more automated reasoning than any AI systems have so far been expected to demonstrate," he wrote. "I suspect that to get this right we will end up wanting our cars to be as intelligent as a human, in order to handle all the edge cases appropriately. "

He still believes that self-driving cars will one day come to supplant human drivers. "Human driving will probably disappear in the lifetimes of many people reading this," he wrote. "But it is not going to all happen in the blink of an eye."
Bear Case 2: They Won't Work, Because They'll Get Hacked
Every other computer thing occasionally gets hacked, so it's a near-certainty that self-driving cars will be hacked, too. The question is whether that intrusion-or the fear of it- will be sufficient to delay or even halt the introduction of autonomous vehicles.
Read: The banality of the Equifax breach
The transportation reporter and self-driving car skeptic Christian Wolmar once asked a self-driving-car security specialist named Tim Mackey to lay out the problem. Mackey "believes there will be a seminal event that will stop all the players in the industry in their tracks," Wolmar wrote. ''We have had it in other areas of computing, such as the big-data hacks and security lapses and it will happen in relation to autonomous cars." Cars, even ones that don't drive themselves, have already proved vulnerable to hackers.

The obvious counterargument is that data lapses, hacking, identity theft, and a whole lot of other things have done basically nothing to slow down the consumer internet. A lot of people see these problems and shrug. However, the physical danger that cars pose is far greater, and maybe the norms developed for robots will be different from those prevalent on the internet, legally and otherwise, as the University of Washington legal scholar Ryan Calo has argued.
Bear Case 3: They Won't Work as a Transportation Service
Right now most companies working on self-driving cars are working on them as the prelude to a self-driving-car service. So you wouldn't own your car; you'd just get rides from a fleet of robo-cars maintained by Waymo or Uber or Lyft. One reason for that is the current transportation-service companies can't seem to find their way to profitability. In fact, they keep losing insane amounts of money. Take the driver out of the equation and maybe all of that money saved would put them in the black. At the same time, the equipment that's mounted on self-driving cars to allow them to adequately convert physical reality into data is extremely expensive. Consumer vehicles with all those lasers and computers on board would be prohibitively expensive. On top of that, the question of calibrating and maintaining all that equipment would be entrusted to people like me, who don't wash their car for months at a time.
Read: Will Uber and Lyft become different things?
Put these factors together and the first step in fully autonomous vehicles that most companies are betting on is to sell robo-car service, not robo-cars.

There is a simple rejoinder to why this might not work. George Hotz, who is himself attempting to build a DIY driving device, has a funny line that sums it up. "They already have this product, it's called Uber, it works pretty good," Hotz told The Verge. And what is a robo-car ride if not "a worse Uber"?
Bear Case 4: They Won't Work, Because You Can't Prove They're Safe
Commercial airplanes rely heavily on autopilot, but the autopilot software is considered provably safe because it does not rely on machine-learning algorithms. Such algorithms are harder to test because they rely on statistical techniques that are not deterministic. Several engineers have questioned how self-driving systems based on machine learning could be rigorously screened. "Most people, when they talk about safety, it's 'Try not to hit something,'" Phil Koopman, who studies self-driving-car safety at Carnegie Mellon University, this year. "In the software-safety world, that's just basic functionality. Real safety is, 'Does it really work?' Safety is about the one kid the software might have missed, not about the 99 it didn't."

Regulators will ultimately decide if the evidence that self-driving-car companies such as Waymo have compiled of safe operation on roads and in simulations meets some threshold of safety. More deaths caused by autonomous vehicles, such as an Uber's killing of Elaine Herzberg, seem likely to drive that threshold higher.

Koopman, for one, thinks that new global standards like the ones we have for aviation are needed before self-driving cars can really get on the road, which one imagines would slow down the adoption of the cars worldwide.
Bear Case 5: They'll Work, But Not Anytime Soon
Last year, Ford announced plans to invest $1 billion in Argo AI, a self-driving-car company. So it was somewhat surprising when Argo's CEO, Bryan Salesky, posted a pessimistic note about autonomous vehicles on Medium shortly after. "We're still very much in the early days of making self-driving cars a reality," he wrote. "Those who think fully self-driving vehicles will be ubiquitous on city streets months from now or even in a few years are not well connected to the state of the art or committed to the safe deployment of the technology."

In truth, that's the timeline the less aggressive carmakers have put forth. Most companies expect some version of self-driving cars in the 2020s, but when within the decade is where the disagreement lies.
Bear Case 6: Self-Driving Cars Will Mostly Mean Computer-Assisted Drivers
While Waymo and a few other companies are committed to fully driverless cars or nothing, most major carmakers plan to offer increasing levels of autonomy, bit by bit. That's GM's play with the Cadillac Super Cruise. Daimler, Nissan, and Toyota are targeting the early 2020s for incremental autonomy.
Read: The most important self-driving car announcement yet
Waymo's leadership and Aurora's Chris Urmson worry that disastrous scenarios lie down this path. A car that advertises itself as self-driving "should never require the person in the driver's seat to drive. That hand back [from machine to human] is the hard part," Urmson told me last year. "If you want to drive and enjoy driving, God bless you, go have fun, do it. But if you don't want to drive, it's not okay for the car to say, 'I really need you in this moment to do that.'"
Bear Case 7: Self-Driving Cars Will Work, But Make Traffic and Emissions Worse
And finally, what if self-driving works, technically, but the system it creates only "solve[s] the problem of 'I live in a wealthy suburb but have a horrible car commute and don't want to drive anymore but also hate trains and buses,'" as the climate advocate Matt Lewis put it. That's what University of California at Davis researchers warn could happen if people don't use (electric-powered) self-driving services and instead own (gasoline-powered) self-driving cars. "Sprawl would continue to grow as people seek more affordable housing in the suburbs or the countryside, since they'll be able to work or sleep in the car on their commute," the scenario unfolds. Public transportation could spiral downward as ride-hailing services take share from the common infrastructure.

And that's not an unlikely scenario based on current technological and market trends. "Left to the market and individual choice, the likely outcome is more vehicles, more driving and a slow transition to electric cars," wrote Dan Sperling, the director of the UC Davis Institute of Transportation Studies, in his 2018 book, Three Revolutions: Steering Automated, Shared, and Electric Vehicles to a Better Future.

It would certainly be a cruel twist if self-driving cars managed to save lives on the road while contributing to climate catastrophe. But if the past few years of internet history have taught us anything, any technology as powerful and society-shaping as autonomous vehicles will certainly have unintended consequences. And skeptics might just have a handle on what those could be.

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banality of the equifax breachthe transportation reporter

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various levels of artificial intelligence

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7 Arguments Against the Autonomous-Vehicle Utopia

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All the ways the self-driving future won't come to pass Self-driving cars are coming. Tech giants such as Uber and Alphabet have bet on it, as have old-school car manufacturers such as Ford and General Motors.

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The five levels (including 0) show how eventually we can grow from fully focused drivers having to do every action themselves to having the driver be completely eliminated from the equation.

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“Examples of where level 5 vehicles excel include off-road driving and other terrains that Level 4 vehicles may not necessarily be able to detect or intelligently comprehend. In other words, level 5 vehicles have a much more advanced environment detection system.”

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Scientists have developed a software that can play a game (Go) and it has learned how to play it so well and developed new moves to the point where it has gotten better than the worlds champions.

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The AI got so knowledgeable about the game that some players gave up after its first move, figuring out theat  there was no way they could beat the computer competitor. But this AI only simply learned a game and  conquered it, driving with AI seems much harder to comprehend from both the human and computers sides.

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The Go game only shows how limited the AI system is but it also shows how much further AI can go and how much more it can learn. The AI for go also figured out new techniques for winning the game that has begun to be used by actual plays, this shows how AI can figure out problems and build from them and though this can prove to be beneficial for the development of driving AI it’s not enough yet.

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“As many will remember, AlphaGo—a program that used machine learning to master Go—decimated world champion Ke Jie earlier this year. Then, the program’s creators at Google’s DeepMind let the program continue to train by playing millions of games against itself. In a paper published in Nature earlier this week, DeepMind revealed that a new version of AlphaGo (which they christened AlphaGo Zero) picked up Go from scratch, without studying any human games at all. AlphaGo Zero took a mere three days to reach the point where it was pitted against an older version of itself and won 100 games to zero.”

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“Now that AlphaGo’s arguably got nothing left to learn from humans—now that its continued progress takes the form of endless training games against itself—what do its tactics look like, in the eyes of experienced human players? We might have some early glimpses into an answer.”