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  • Ford CTO Ken Washington On Technology Challenge of AI Self-Driving Cars
    Five years ago at the Code Conference, self-driving cars seemed as though they were just around the corner: Google unveiled the project that would later become Waymo, and Uber’s then-CEO Travis Kalanick stirred controversy when he talked about the benefits of replacing human drivers. But in 2019, autonomous vehicle prototypes are a rarity in most cities outside of San Francisco, and humans are still vital to companies like Uber and its first-to-IPO rival Lyft. That’s because self-driving is a really, really hard technological problem, Ford CTO Ken Washington said on the latest episode of Recode Decode with Kara Swisher. But, very slowly, beginning in 2021, you’re going to start seeing cars with no one in the driver’s seat. “You may see some earlier ones in 2020, but we believe in taking the time to work with the cities,” Washington said. “If you just put a bunch of autonomous vehicles in the city without designing it to make life better in that city, you’re gonna have an analogous problem to what happened when Ubers first started showing up. People hated them because they’re camping out on the corners, and it made congestion worse, it created additional pollution.” Ford is currently testing its self-driving cars (still with humans in the front seat as a precaution) in Miami, Washington, Dearborn, Pittsburgh, and multiple places in California. Washington explained that, in order to be ready for regular consumers, these “robo-cars” need to have a pre-existing 3-D scan of every street they might drive on. “This is not your navigation map, the kind of map that you would use on your cellphone that you pull out and you do a Google Map or an Apple Map,” he said. “It’s actually shooting light beams out in three dimensions off of the roof of the vehicle … [and] capturing these points and creating a 3-D image of what the world looks like.” “If you don’t have that part of the map, you’re relying on, in real-time, detecting everything that might happen, and that’s just too hard of a problem,” Washington added, before taking a dig at Tesla’s so-called Autopilot features. “That’s why these vehicles that don’t have LIDAR, that don’t have advanced radar, that haven’t captured a 3-D map, are not self-driving vehicles. Let me just really emphasize that. They’re consumer vehicles with really good driver-assist technology.” Q&A interview follows: Kara Swisher: How are you doing? Ken Washington: I’m great. Now Ken, you’re gonna tell us how cool all this stuff is now that we talked about the disaster that’s coming. Let’s talk a little bit about … I wrote a column last week, which did get a crazy amount of commentary. Thousands and thousands of comments on the New York Times. People were for it, people were really, really for it, and what I did in the column is that I really don’t want to own a car again. I wrote a piece in the Wall Street Journal 25 years ago saying, “You will have mobile phones. You will not have landlines. You will not be wired. It will be all be wireless.” It was a very good prediction, and then I said, “Now, you’re never gonna own a car,” and, “It will be as quaint as owning a horse.” I think that’s the expression I used. I was trying to get a discussion going. I mean, obviously you wanna talk about where this is going, but I do truly believe that we’re on the cusp of this because of self-driving and AI and the stuff that are gonna go into transportation. So let’s talk a little bit about cars first, and then we’ll get into the other things that companies like Ford and others are doing, where AI does benefit a company. So let’s talk about where we are with autonomous vehicles right now and where AI fits in. Well first, I just wanna say, I think you definitely got people’s attention with the article. Yeah. I think the response was a reflection of the fact that people love cars, and some people hate cars, but everyone needs to move around. What autonomous vehicles has done for us is given us the potential and the promise of a new way of moving around, and a new way of creating mobility, and a new way of solving real pain points in cities. What I loved about your article was it really shined a light on the fact that in urban centers where you really need a different model, that now this new model is beginning to emerge. Right. I wasn’t talking about car ownership. I was talking about — and not — I was talking about car ownership, not car driving. I will continue to drive and move in mobile vehicles depending on … but it was the car ownership and it’s the idea of ownership. Just the way we owned entertainment before, now we really don’t. Just the way we owned records, we owned this. It’s the same concept, that this is one that’s moving in, and especially in urban areas where I think 90 percent of the population’s going to be in a megalopolis over the next 25 years, like 90 percent. So those other 10 percent can have their cars, it’s fine, but it’s just what happens when those population … So talk about where we are and how AI fits into the idea of where we are with autonomous. Let’s start with autonomous vehicles. We’re right in several stages, right? Three, four, five, we’re in three now, which is? Well, let me just clarify that. Okay. It’s a term that’s often really misused and misunderstood. When you’re talking about autonomous vehicles, particularly in urban cities where you predict 90 percent of people are gonna live. What you really have to think about is an autonomous vehicle that can truly sense the environment completely and can truly take the human out of the loop. So that’s a level-four autonomous vehicle. Even that level-four autonomous vehicle that can operate in this urban environment, it’s gonna have some boundaries around it. It’s gonna have to have the ability to operate in a city that it’s seen before, so it has to have been mapped. There are gonna be weather restrictions on it, at least with today’s technology, and there are gonna speed restrictions, because the sensors aren’t perfect and hopefully no one in this room believes that the AI part of the problem has been completely solved. You can’t even review résumés with AI and not screw it up. Getting the AI right in a vehicle is really hard. It involves a lot of testing and a lot of validation, a lot of data gathering, but most importantly, the AI that we put into our autonomous vehicles is not just machine learning. You don’t just throw a bunch of data and teach a deep neural network how to drive. You build a lot of sophisticated algorithms around that machine learning, and then you also do a lot of complex integration with the vehicle itself. Read the source article in recode. Read more »
  • Amalgamating of Operational Design Domains (ODDs) for AI Self-Driving Cars
    By Lance Eliot, the AI Trends Insider When I got my very first car, I was so excited to be driving my own car that I opted to drive everywhere that I could think of. I drove all throughout my local neighborhood and honked my horn as I drove past the homes of friends of mine. I drove beyond my community and took the freeway to go visit friends that lived in the inner-city areas. I drove down to the beach, parked at the edge of the sand, and took a picture of me and my car, including as a backdrop a dramatic sunset and the rays of the sun glinting off the ocean, adding a picturesque look to my shiny new automobile. The next day, I took some friends up to the snowy mountains. I had made sure to buy snow-chains for my tires and it was my first foray into putting them on and seeing how the car handled on icy roads and in light snowy conditions. I kept on the snow-plowed roads and did not venture into any off-roading, since my car was, well, just a regular car, and I figured it would be quite a risk to see if it could cope with off-road adversities. Upon returning from the mountains, a good friend suggested we head out to the desert. The mountain trip had involved freezing cold temperatures. Perhaps by going to the dry and hot desert, we’d be able to unfreeze and gain back our normal body temp. With my still brand-new car, we drove on a somewhat barren highway and headed out to the middle of the desert. Once we reached the outskirts of the desert, we went off the main highway and took roads that were only sporadically paved. At one point, we were driving on dirt-like sand-packed roads. I came to a stop before we ended-up in an actual loose desert sand. Not being content with “only” having driven in the city, the suburbs, the mountains, and the desert, I decided that the next adventure with my car would be to the forest. So, I packed my camping gear into the car and drove up to the redwoods. I was able to get a campground that allowed you to park your car right next to where you were going to put your tent. Today, some would say this is a form of glamping, a somewhat newer word that means camping with luxury. Admittedly, being right next to my car was handy and a reassurance. Imagine my horror if a bear were to have tried to pry into my car to get the food I had brought – I would have been devastated that my new car got banged up by the evil claws! As I headed back home, the forest got deluged with quite a rainstorm. Driving out of the woods was a bit tricky as some of the roads began to flood. I was lucky that the rain was only drenching the roads and not completely flooding them. I inched my way out of the woods on the paved roads that were wet and at times I worried that the car might get too much water up into the engine compartment. One other thing that I encountered was a lot of potholes and other marred roadway aspects. Because of the rain on the road, I was not able to readily discern where the cracks and gaps in the asphalt existed. Normally, I would have tried to steer around any potholes or other street maladies. In this case, I opted to focus on staying on the road and not sliding off the road, thus, if I happened to also hit any bumps or holes in the road, so be it, at least I was still on the road itself. In the initial two weeks of getting my first car, I likely put as many miles on it as some people do in an entire year. I’d wager that most young people are equally excited when they get their first car. It is a means to have mobility. You can go where you want. You can go when you want. Previously, prior to getting my own car, I had to borrow my parents car or see if I could get a friend to use their car or loan me their car for any driving trips I wanted to make. Now, I instead just walked out to my car, put the key in the ignition, and by gosh I could go wherever I pleased. Yippee! There were of course some limits about where I could drive. My car was not suited to doing off-roading. I realized that I could either wreck my new car or get stuck if I tried to go off-road. But, nonetheless, I pushed that limit quite a bit. My driving out to the desert got me and my beloved car pretty close to being off-road. When I drove to the beach, it was at the edge of off-road once I touched the sandy beaches. At the woods, and up in the snowy mountains, I pretty much put my on-road-only car into situations that were darned close to an off-road journey. The limits I had in mind were all based on what the car could and could not do. Though I was still a rather young and inexperienced driver, it didn’t occur to me that my ability to drive the car ought to be another form of limitation. I sheepishly admit that during the snowy mountain trip, I lost control of the car and it skidded into a snow bank. My fault. I was not driving carefully enough for the snowy conditions and also had never particular practiced at driving in such conditions. While driving out of the forest, I got caught in semi-flooded roads. I had never driven a car in rain-soaked situations. I managed to get out of the woods without injury, though other cars around me were certainly wary of my swerving and inexperienced efforts of driving the car. You could say that driving a car involves various potential limits. One obvious limit is the capability of the car. I had a colleague that never drove his car up to the mountains. Why, you might ask? He insisted that the engine was on its last legs and the strain to drive up steep roads would wipe it out. He even avoided driving on any high inclines in city driving, making sure to take the long way around if he could avoid streets that were at a steep pitch. I was willing to take my new car just about anywhere that a road existed. I trusted that since it was a new car, it would be able to handle high speeds, low speeds, bumpy roads, smooth roads, highways, freeways, and the rest. According to the Federal Highway Administration (FHA), there are slightly more than four million miles of roads in the United States. I was determined to see if I could drive everyone of those many millions of miles in my nifty new car. That hope was a bit challenging since the four million miles includes Hawaii and Alaska, which would take some doing to reach. The driver of a car is certainly another limitation. Some drivers are not versed in driving in snowy conditions. Unless they really needed to drive in such inclement conditions, such as in a dire emergency, it’s probably best if they didn’t venture into situations involving driving in the snow (until they got some training in doing so). Here in Southern California, it is a standard joke that most drivers do not seem to be able to drive in the rain. We got so little rain that one might generously suggest we are out of practice of rain driving. When I have visitors from other parts of the country where they routinely get rain and must drive in it, they scoff and laugh at the manner of how locals here drive in the rain. In any case, one could say that a driver that is not versed in rain driving is another kind of limitation related to the driving of a car. In the official parlance of the automotive industry, the way in which you can define the scope and limits of driving are referred to as a “domain” and commonly indicated as the Operational Design Domain (ODD). Per the IEEE standard known as J3016, here’s what ODD formally means: “… operating conditions under which a given driving automation system or feature thereof is specifically designed to function, including, but not limited to, environmental, geographical, and time-of-day restrictions, and/or the requisite presence or absence of certain traffic or roadway characteristics.” That’s a bit of a mouthful. In essence, an ODD is a kind of carve out. Imagine all of the numerous ways in which driving might occur such as in fine weather or bad weather, on bumpy roads or smooth roads, and so on. In that universe of a myriad of driving conditions, you can stake out a subset and declare it to be an ODD. You Can Make Up Your Own ODDs For example, I might define an ODD that consists of smooth roads, absence of rain and the roads must be dry, and there must be high visibility in terms of being able to see around the car. That’s my declared ODD. It’s just one such ODD. I might define a second ODD, for which it consists of smooth and bumpy roads, light rain allowed, roads can be wet but not slick, and the visibility can range from high to mediocre. I could continue declaring various ODDs. Each of the ODDs would have some particular set of indicators about what it includes. This might also include exclusions, thus I can probably be clearer about my ODDs by not only saying what it includes but also what it excludes. That being said, the number of exclusions could be rather vast and perhaps exhausting to try and list them all. There is no accepted standard as to what the ODDs are. Anyone can make-up their own ODDs. I’ve provided you with two ODDs that I just made-up. You might decide that you like those ODDs and opt to use the same ones, exactly as I had declared them, offering no changes or adjustments to them. Or, maybe you decide to make a variant of my ODDs. For the first ODD that I declared, you decide to add that the roads cannot include any roundabouts or traffic circles. I didn’t state in my ODD whether or not roundabouts were allowed, but you could likely assume that since I had not said it was excluded, it presumably was included. You now are making sure to explicitly state that roundabouts are excluded. In that case, my ODD and your ODD are now different from each other. Think of the number and variety of ODDs that could be declared. By mixing and matching all permutations and combinations of the myriad of factors, you could create an enormous number of ODDs. Besides the roadway aspects, you can state that an ODD is good for daylight but does not encompass night time. Thus, time of day can be a factor. The geographical area can be a factor, such as I might declare my first ODD was intended only for say Los Angeles and no other geographical realm. On and on this can go. Who would be making up these ODDs? The auto makers can do so and will likely need to do so. They aren’t the only ones and it is pretty much a free-for-all as to whom can declare ODDs. Researchers can make them up. Industry analysts can make them up. You and I can make them up. I suppose you might be thinking it seems like a rather hazy thing and kind of loose. Yes, you’d be right about that. You might also be thinking that this ODD is something you’ve not heard about before and therefore it doesn’t seem to matter much. I’d say you are half-right about that. ODDs are indeed something you’ve had no cause to necessarily hear about or know about, to-date. But, I fully and boldly predict that pretty soon you’ll be hearing all about them. A lot. It will become a big topic. You will likely ultimately become so familiar with ODDs that you will forget that you ever didn’t know about them. That’s how prevalent awareness of ODDs is going to become. What does this have to do with AI self-driving cars? At the Cybernetic AI Self-Driving Car Institute, we are developing AI software for self-driving cars. For the Level 4 and Level 5 of AI self-driving cars, the nature and use of ODDs is essential. Once the public begins to experience Level 4 and Level 5 AI self-driving cars on the roadways, the ODDs topic is going to hit the big time and be at the forefront of public discussion and discord. Mark my words! Allow me to elaborate. I’d like to first clarify and introduce the notion that there are varying levels of AI self-driving cars. The topmost level is considered Level 5. A Level 5 self-driving car is one that is being driven by the AI and there is no human driver involved. For the design of Level 5 self-driving cars, the auto makers are even removing the gas pedal, brake pedal, and steering wheel, since those are contraptions used by human drivers. The Level 5 self-driving car is not being driven by a human and nor is there an expectation that a human driver will be present in the self-driving car. It’s all on the shoulders of the AI to drive the car. For self-driving cars less than a Level 5, there must be a human driver present in the car. The human driver is currently considered the responsible party for the acts of the car. The AI and the human driver are co-sharing the driving task. In spite of this co-sharing, the human is supposed to remain fully immersed into the driving task and be ready at all times to perform the driving task. I’ve repeatedly warned about the dangers of this co-sharing arrangement and predicted it will produce many untoward results. For my overall framework about AI self-driving cars, see my article: https://aitrends.com/selfdrivingcars/framework-ai-self-driving-driverless-cars-big-picture/ For the levels of self-driving cars, see my article: https://aitrends.com/selfdrivingcars/richter-scale-levels-self-driving-cars/ For why AI Level 5 self-driving cars are like a moonshot, see my article: https://aitrends.com/selfdrivingcars/self-driving-car-mother-ai-projects-moonshot/ For the dangers of co-sharing the driving task, see my article: https://aitrends.com/selfdrivingcars/human-back-up-drivers-for-ai-self-driving-cars/ Let’s focus herein on the true Level 5 self-driving car. Much of the comments apply to the less than Level 5 self-driving cars too, but the fully autonomous AI self-driving car will receive the most attention in this discussion. Here’s the usual steps involved in the AI driving task:         Sensor data collection and interpretation         Sensor fusion         Virtual world model updating         AI action planning         Car controls command issuance Another key aspect of AI self-driving cars is that they will be driving on our roadways in the midst of human driven cars too. There are some pundits of AI self-driving cars that continually refer to a utopian world in which there are only AI self-driving cars on the public roads. Currently there are about 250+ million conventional cars in the United States alone, and those cars are not going to magically disappear or become true Level 5 AI self-driving cars overnight. Indeed, the use of human driven cars will last for many years, likely many decades, and the advent of AI self-driving cars will occur while there are still human driven cars on the roads. This is a crucial point since this means that the AI of self-driving cars needs to be able to contend with not just other AI self-driving cars, but also contend with human driven cars. It is easy to envision a simplistic and rather unrealistic world in which all AI self-driving cars are politely interacting with each other and being civil about roadway interactions. That’s not what is going to be happening for the foreseeable future. AI self-driving cars and human driven cars will need to be able to cope with each other. For my article about the grand convergence that has led us to this moment in time, see: https://aitrends.com/selfdrivingcars/grand-convergence-explains-rise-self-driving-cars/ See my article about the ethical dilemmas facing AI self-driving cars: https://aitrends.com/selfdrivingcars/ethically-ambiguous-self-driving-cars/ For potential regulations about AI self-driving cars, see my article: https://aitrends.com/selfdrivingcars/assessing-federal-regulations-self-driving-cars-house-bill-passed/ For my predictions about AI self-driving cars for the 2020s, 2030s, and 2040s, see my article: https://aitrends.com/selfdrivingcars/gen-z-and-the-fate-of-ai-self-driving-cars/ Returning to the topic of ODDs, let’s take a closer look at what they are and why they are going to be so crucial to the advent of AI self-driving cars. Level 4 self-driving cars must provide an indication of the ODDs under which they are able to operate. This means that if you are intending to purchase a Level 4 self-driving car, you would be wise to look carefully at the ODDs that the auto maker says are applicable to the automobile you are about to purchase. You would likely give this even more scrutiny than the typical features of a car such as the Miles Per Gallon (MPG) or how many cup holders it has. The reason to scrutinize the ODDs is so that you’ll then know where, when, and under what circumstances your AI self-driving car is going to be able to operate as a self-driving car. According the standard definition for Level 4, once the AI detects that it has reached a point that the driving is no longer within its defined ODDs, the AI is supposed to let the human driver in the car take over or the AI is supposed to pull over, finding hopefully a safe spot to do so, and wait to continue driving until the situation becomes one encompassed by the ODDs of that particular AI self-driving car. Let’s suppose you buy an AI self-driving car that has a bunch of ODDs and in addition mentions various exclusions of aspects that fall outside of those ODDs. Pretend that one of the exclusions is that the AI self-driving car will not drive in snowy conditions. You would need to dig deeper into how the particular auto maker is defining snowy conditions such as whether this includes a light dusting of fully snowflakes or maybe it only counts once a heavy snowstorm erupts and dumps a ton of snow onto the roadway. In any case, there you are, going along for a spin in your fancy new Level 4 AI self-driving car. It is a wintery day. When you began your joyful journey, the skies were relatively barren of clouds. Sure, it was a cold morning as you got underway, but you didn’t expect bad weather to occur. Darned if toward lunch time, clouds started coming in fast. With the cold temperatures and the clouds forming, it begins to snow. The AI of the Level 4 self-driving car is presumably able to detect the snowfall, doing so via the sensors of the self-driving car. Because the ODDs indicated the AI is not considered able to drive in snowy conditions, the AI alerts you that you’ll need to take over the driving of the self-driving car. If you refuse or don’t speak-up, the default will be to pull the self-driving car over to the side of the road at the earliest feasible and hopefully safe spot. Even though you might be able to drive the self-driving car, and you are willing to do in spite of the flakes of snow, and there’s lots of other car traffic around you that is doing so, your AI is not going to budge one inch. The ODD boundaries have been reached. You would need to take the controls if you didn’t want to sit there by the side of the road and wait for whenever next the snow cleared up sufficiently that the AI declared it was okay for it to proceed and would continue on the driving journey. I realize you might say that it is a small inconvenience in this case. No big deal, you say, it’s a minor annoyance that the AI has opted to no longer drive the self-driving car for the moment. For your driving journey, at least it drove you for a substantial part of the time. You can just now take over the driving and finish the trip. Furthermore, if you are able to drive out of the snowy area, you likely can coax the AI to resume driving the self-driving car. But, imagine that you decided to have your Level 4 AI self-driving car take the kids to school that morning. You had put the kids into the self-driving car and sternly instructed the AI to drive them straight to the school. It had done this many times before. One Day the AI Self-Driving Car Says It’s Too Snowy to Take the Kids to School Unfortunately, on this particular day, let’s assume that the snow starts to fall from the sky while midway to the school. The AI announces that it needs either a licensed driver to take over the controls right away or it will pull over to the side of the road. There isn’t a licensed driver in the self-driving car (you are still at home, awaiting the self-driving car to drop the kids at their school and come back to pick you up to drive you to work). Only your underage children are in the self-driving car. They can’t legally drive and nor do they know how to drive. Regrettably, they now are going to be sitting in the dormant and roadway-parked AI self-driving car which has found hopefully a safe place to sit out the snow. For most parents, this would be a chilling moment and the time at which they start to have second-thoughts about having gotten that Level 4 AI self-driving car. You could say that the parent was “foolish” for having put the children into the AI self-driving car without any adult present. I assure you this is exactly what many, if not most parents are going to do. They are going to leverage the always-available automated chauffeur. It will become more than just a handy convenience. Parents will adjust their lives around the aspect that they no longer need to drive their children to all sorts of places, such as no need to drive your children to school, nor to baseball practice, nor to karate lessons, nor to the local pizza place. You might say that the parent should have known it was going to snow. In that case, on this occasion, the parent should have gone along for the ride, serving as a “human back-up” driver in case the AI had to call it quits. Yes, I suppose you could try to take that angle on this scenario, but I hope that you won’t get quite so literal on this one example. My overall point is that the ODD’s of the Level 4 AI self-driving car could consist of a wide variety of inclusions and exclusions. I made things over-simplified by using just the snowy condition. There might instead by a large number of inclusions and exclusions, making it much harder to judge when you might have the AI opt to quit on you. It won’t be so easy that you’ll readily be able to predict when the exclusions are going to be reached. For my article about ODDs and Level 4, including driving controls aspects, see: https://www.aitrends.com/selfdrivingcars/ai-boundaries-and-self-driving-cars-the-driving-controls-debate/ For my article about the bifurcation of autonomy, see: https://www.aitrends.com/selfdrivingcars/reframing-ai-levels-for-self-driving-cars-bifurcation-of-autonomy/ For my predictions about the marketing of AI self-driving cars, see my article: https://www.aitrends.com/selfdrivingcars/marketing-self-driving-cars-new-paradigms/ For ridesharing aspects of AI self-driving cars, see my article: https://www.aitrends.com/selfdrivingcars/ridesharing-services-and-ai-self-driving-cars-notably-uber-in-or-uber-out/ For the affordability question about AI self-driving cars, see my article: https://www.aitrends.com/selfdrivingcars/affordability-of-ai-self-driving-cars/ I also made things easier by suggesting you had chosen to buy the Level 4 AI self-driving car. I say that’s “easier” because you presumably would have carefully read the ODDs before you purchased that self-driving car. You would have done your due diligence and fully understood what the various inclusions and exclusions consist of. You would have tried to identify the ways in which you’ll be using the self-driving car, such as the geographical area you live in, the seasons of the year, and other factors, all of which would have led you to via full-awareness having decided to buy that self-driving car. At least that’s what should happen, though we know that people don’t necessarily take that kind of overt care and caution when buying a car. The other way in which the ODDs will impact you is when you use a ridesharing service. It is predicted that ridesharing services will flock in droves to using AI self-driving cars. This makes a lot of sense for the ridesharing firms to do so. No need to deal with a human driver for their ridesharing cars. Human drivers are difficult, because they are humans, which means they want to get paid for their driving, they want reasonable hours of driving time, they want to take breaks periodically, and so on. With an AI system, no need to deal with any of those human elements. You are getting off work early and decide to take a ridesharing car to get home. Via a mobile app on your smartphone, you summon a ridesharing car, doing so with a company that prides itself on providing all and only AI self-driving cars. They are using Level 4 AI self-driving cars. One handy aspect is that the company keeps those AI self-driving cars going as much as possible, running them nearly non-stop 24×7, other than when the self-driving cars need to get their electrical charges or when they are out for maintenance purposes. A few minutes later, the AI self-driving car comes to the curb and you get into it. You had already indicated your destination and thus the AI repeats to you the destination, confirming where you want to go, and once you get settled with your seatbelt on, the AI proceeds. How nice that you don’t need to carry on petty conversations with those pesky human ridesharing drivers. The AI tries to initiate a dialogue with you, but you cut it off and state that you want a nice quiet ride instead. No need to worry about hurting the feelings of the AI. It’s just AI. For the non-stop use of AI self-driving cars, see my article: https://www.aitrends.com/selfdrivingcars/non-stop-ai-self-driving-cars-truths-and-consequences/ For family trips and self-driving cars, see my article: https://www.aitrends.com/selfdrivingcars/family-road-trip-and-ai-self-driving-cars/ For my article about safety and AI self-driving cars, see: https://www.aitrends.com/selfdrivingcars/safety-and-ai-self-driving-cars-world-safety-summit-on-autonomous-tech/ For my article about the use of Natural Language Processing (NLP) with AI self-driving cars, see: https://www.aitrends.com/selfdrivingcars/car-voice-commands-nlp-self-driving-cars/ Unbeknownst to you, this particular Level 4 AI self-driving car has an ODD that the auto maker and tech firm defined to exclude heavy gusts of winds. Your home is nestled in a rural area where you thought it would be best to raise a family. The drive from work, which is downtown, and out to the rural area usually takes about an hour or so. On this day, there is a strong set of winds blowing along the highway that takes you to your home. While on the highway, you can see up ahead that the winds are shoving trucks and other cars. It is occurring with some frequency. There doesn’t seem to be any problems though and the vehicles are all continuing along on the blustery highway. You begin to take a nap in the backseat, enjoying the ridesharing ride that lets you take it easy because the AI is doing the driving. All of a sudden, the AI announces that you will need to take over the driving or it will be pulling over to the side of the road momentarily. Why, you ask? The AI responds that the wind speeds are excessive and exceed the defined ODD for this AI self-driving car. Yikes! You had no idea that this ridesharing car had that kind of an ODD. You are irked to no end. I realize that you might object to my scenario and say that the ridesharing service should have informed the rider about the ODDs. Yes, I am sure that the ridesharing services will post the ODD’s of their cars. When you book one of their cars, there will likely be a place to click on a lengthy legal-looking narrative that carefully spells out all of the inclusions and exclusions. I wonder how many people will go to the trouble to read those? Probably the same number that read the legal limits and caveats that the ridesharing services also post at their sites right now (have you ever read those?). If you are assuming that this ODD matter is going to be simplified by merely having all AI self-driving cars adopt the same ODDs, I’ll remind you that I earlier had stated that there is no such standard. This means that if you consider buying a Level 4 AI self-driving car from auto maker X, they will presumably have defined whatever set of ODDs they wanted to establish for their Level 4 AI self-driving cars. They might also have different sets of ODDs among their own line of Level 4 AI self-driving cars. Maybe the low-end lower-cost Level 4 AI self-driving car of auto maker X has one set of ODDs, we’ll call it the AI-1 model, while their more expensive higher-end Level 4 AI self-driving car has a more extensive set of ODDs, we’ll call it the AI-2 model. When you buy the car, you’ll need to decide whether you are fine with the lesser set of ODDs and buy the AI-1 or might get stuck at some point and so prefer to get the more in-depth set of ODDs offered by the AI-2. Furthermore, keep in mind that another auto maker, we’ll call them auto maker Y,… Read more »
  • What New Data Scientists Need to Know for Their First Job
    By J.T. Wolohan, Data Scientist, Booz Allen Hamilton I’m a lead data scientist at the consulting firm and federal contracting giant Booz Allen Hamilton—a leader in the analytics services space. I oversee a small team of data scientists—some of whom are fresh out of masters and undergrad programs—in a variety of analytics platform development and algorithm development projects, from text mining, to document similarity and retrieval, to operations, program and business analytics. As an alumnus of Syracuse University, I’m happy to be able to share some advice with soon-to-be graduates looking to enter a data science role in industry. Having had the opportunity to watch new data scientists grow, I want to share the three things that separate the great data scientists from the good data scientists I work with—customer thinking, data munging, and DevOps—as well as some tips about what I look for when interviewing data scientists. Customer Thinking The first and most important skill that separates the best data scientists I work with from everyone else is customer thinking. Data science is a highly complex field. It is quickly evolving and requires a variety of technical knowledge—from coding to mathematics. This makes it really hard for customers to ask for what they need. A lot of data science tasks take the form of “I’m having this problem and I’ve got some data that should be able to fix it, what can you do?” The great data scientists always keep their focus on what’s going to be most impactful for their customers. Does the customer need better accuracy? Better recall? Do they need faster runtime? Do they need lots of options or just one? Customers needs must be incorporated into every step of the data science process. Data Munging The second skill that separates the best data scientists I know is the ability to work with a wide variety of data formats and types. The number of projects that involve well formatted data—never mind situations where you’ll have programmatic access via an API—are few and far between. Far more prevalent are the situations where the customer has a handful of Excel workbooks, knowledge about a database somewhere that they don’t have access to, and a piece of software from 2003 that doesn’t have a maintainer but is still being used. To succeed in this environment, data scientists must be able to bring together data from a variety of formats. You should be able to rip data from PDFs, parse the XML from a convoluted document, unpack deeply-nested JSON from an obscure API, scrape data from idiosyncratic webpages and bring all of that information together into a format that disguises all that messiness. DevOps The final skill that separates great data scientists is an awareness of DevOps. Now, data scientists by no means need to be DevOps / continuous delivery experts—but analytics need to be deployed to the customer somehow and DevOps is that how. An ability to wrap your models up as APIs in a deployable Docker container goes a long way. Of course, this means you’ll need to know how to build APIs too—and it will help to have an understanding of microservices. There’s a lot of ideas to unpack there, but the key is this: data science models and trained machine learning algorithms get deployed as pieces of a system. That piece needs to be self-contained so that if it needs to be switched out it can be switched out easily, or if the parts around it change the model itself doesn’t need to be redesigned. DevOps, Containers, APIs and microservices are the modern way of handling all that. What do Data Science Interviewers Look For? I’ve covered the three skills that separate the great new data scientists from the rest of the new data scientists – but even if you have all the skills you need to succeed at the job, you will still need to ace an interview (or a few) to land the job. Here are three tips from my experience interviewing young data scientists. First, tech skills matter – so make sure you know the technology that’s listed in the job description. That said, sometimes you’ll only need to have knowledge of a type of technology (e.g., Hadoop OR Spark for Big Data analytics.) This is especially true with less-technical groups. Additionally, feel free to say you don’t know the answer to a question. Technology is complex and you won’t be an expert in everything. Read the source article in InfoSpace, blog of the U of Syracuse iSchool. Read more »
  • Feds Working on Ways To Protect AI Training Data from Malicious Tampering
    The intelligence community’s advanced research agency has laid the groundwork for two programs focused on ways to overcome adversarial machine learning and prevent adversaries from using artificial intelligence tools against users. Stacey Dixon, director of the Intelligence Advanced Research Projects Activity (IARPA), said the agency expects both programs to run for about two years. “We appreciate the fact that AI is going to be in a lot more things in our life, and we’re going to be relying on it a lot more, so we would want to be able to take advantage of, or at least mitigate, those vulnerabilities that we know exist,” Dixon said on April 16 at an Intelligence and National Security Alliance (INSA) conference in Arlington, Virginia. The first project, called Trojans in Artificial Intelligence (TrojAI), looks to sound the alarm whenever an adversary has compromised the training data for a machine-learning algorithm. “They have inserted some training data that is saying that a stop sign is actually a speed limit sign, for example,” Dixon said. “How do you know that there are these kinds of triggers in your training data, as you take the algorithms that come out of the training and use them for something else?” IARPA released a draft broad agency announcement last December and had received feedback, comments and suggested changes from the private sector through the end of February. Another program, which Dixon said would have a draft announcement coming later this year, will look to protect the identities of people whose images have served as training data for facial recognition tools. “How do you ensure that no one can take the algorithm that you created and go back and recreate the faces that were in the database?” Dixon said. “These are certain areas that we hadn’t seen too much research, and so we will be starting programs.” While a handful of agencies have piloted simpler AI tools, like robotic process automation, Customs and Border Protection since June 2016 has been working on a biometric facial recognition pilot program that compares images of passengers boarding flights to photos on their passports, visas and other forms of government-issued identification. In addition, Dixon said IARPA has made cybersecurity forecasting an “aspirational” goal, and described the project as giving agencies and companies a heads-up about an imminent cyber-attack, and the identify of who might be behind it. Read the source article at Federal News Network. Read more »
  • Meet OilX – Startup Using AI to Transform the Oil Trade
    Artificial intelligence has been making inroads into the oil and gas industry for a while now after the industry realized all the benefits it could reap from the deployment of these technologies. Now, it has begun changing oil and gas trading as well. First of all, it bears noting the term artificial intelligence has developed into an umbrella term for a host of predictive and analytical technologies that are a far cry from the average layman’s idea of AI, that is, machines capable of independent thought. We are not there yet. Yet the technology has advanced sufficiently to begin transforming the oil and gas industry, including the trade of these commodities and products. For now, the space of AI-enabled energy trading providers is relatively empty. One notable recent addition to it was OilX, an oiltech startup that provides traders with real-time oil analytics based on a combination of satellite tracking data and reports from various official organizations, including customs, JODI, and statistics agencies. Thanks to AI, the OilX platform can process and offer traders a lot more comprehensive and hence more reliable oil fundamentals data in a fraction of the time traditional oil supply and demand analysis takes. Speed and accuracy are what, according to OilX’s founders, makes the platform unique and these two features also highlight the top priorities of modern-day traders generally. Yet this is only a nascent market with a huge potential. As OilX’s chief executive Florian Thaler told Oilprice, “Theoretically, AI-enabled solutions can be found everywhere in a trading organisation, from front to middle to back office in trading operations. Ranging from analytics, trade execution, risk management, HR. We believe that the change is coming from a series of small, highly focused and specialized solutions which – when put together – form a comprehensive solution.” But AI is encroaching on traditional practices in price forecasting as well. This is hardly a surprise given one of the main advantages of algorithms over humans is in the superior predictive capabilities of the former. “Price suggestion has clearly become a key factor [for AI] where for large trades and complex derivatives it used to take a while to price trades,” a senior Citi executive told S&P Global Platts at an industry event last November. AI is already helping traders make better decisions based on price forecasts made by the algorithms, Sandeep Arora said. And it goes beyond just price forecasts. Artificial intelligence is also being used to help humans learn how to better predict prices. Read the source article in OilPrice.com. Read more »
  • EU Unveils Ethics Guidelines for Artificial Intelligence
    The European Union has presented ethics guidelines as it seeks to promote its own artificial intelligence sector, which has fallen behind developments in China and the United States. The European Commission, the bloc’s executive arm, unveiled a framework aimed at boosting trust in AI by ensuring, for example, data about EU citizens are not used to harm them. “Ethical AI is a win-win proposition that can become a competitive advantage for Europe: being a leader of human-centric AI that people can trust,” Commission Vice President Andrus Ansip said. According to the guidelines, trustworthy AI should be: (1) lawful –  respecting all applicable laws and regulations (2) ethical – respecting ethical principles and values (3) robust – both from a technical perspective while taking into account its social environment The guidelines put forward a set of 7 key requirements that AI systems should meet in order to be deemed trustworthy. A specific assessment list aims to help verify the application of each of the key requirements: Human agency and oversight: AI systems should empower human beings, allowing them to make informed decisions and fostering their fundamental rights. At the same time, proper oversight mechanisms need to be ensured, which can be achieved through human-in-the-loop, human-on-the-loop, and human-in-command approaches Technical Robustness and safety: AI systems need to be resilient and secure. They need to be safe, ensuring a fall back plan in case something goes wrong, as well as being accurate, reliable and reproducible. That is the only way to ensure that also unintentional harm can be minimized and prevented. Privacy and data governance: besides ensuring full respect for privacy and date protection, adequate data governance mechanisms must also be ensured, taking into account the quality and integrity of the data, and ensuring legitimised access to data. Transparency: the data, system and AI business models should be transparent. Traceability mechanisms can help achieving this. Moreover, AI systems and their decisions should be explained in a manner adapted to the stakeholder concerned. Humans need to be aware that they are interacting with an AI system, and must be informed of the system’s capabilities and limitations. Diversity, non-discrimination and fairness: Unfair bias must be avoided, as it could could have multiple negative implications, from the marginalization of vulnerable groups, to the exacerbation of prejudice and discrimination. Fostering diversity, AI systems should be accessible to all, regardless of any disability, and involve relevant stakeholders throughout their entire life circle. Societal and environmental well-being: AI systems should benefit all human beings, including future generations. It must hence be ensured that they are sustainable and environmentally friendly. Moreover, they should take into account the environment, including other living beings, and their social and societal impact should be carefully considered. Accountability: Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes. Auditability, which enables the assessment of algorithms, data and design processes plays a key role therein, especially in critical applications. Moreover, adequate an accessible redress should be ensured. Read the source post on the EU website. Download the guidelines. Read more »
  • Human Driving Extinction Debate: The Case of AI Self-Driving Cars
    By Lance Eliot, the AI Trends Insider What is your relationship with driving? Kind of a curious question, I realize, but it goes to the heart of the matter about whether you are someone that craves being able to drive a car or instead consider driving to be a burdensome task that happens to be a necessity. Ponder for a moment where you fall on the spectrum of driving interests, consisting at one end of the gamut are those that are extremely passionate about being able to drive and at the other end are those that would just as soon not drive if they could avoid doing so (perhaps even abhorring the act of driving). When I was in college, I had one friend that loved to drive. He would drive a car for any reason whatsoever. One day, we wanted to go to the lower part of the campus, which involved about a five-minute walk, an easy downhill jaunt from the upper campus, and he offered to drive instead of walking. This was kind of crazy because we would first have needed to walk to the parking lot that housed his car, and once he drove us down to the lower part of campus, he’d need to park in another parking lot down there. In the end, we would have ended-up walking to and from the campus parking lots, which was a cumulative total distance greater than if we simply walked directly to the building on the lower campus that we wanted to visit. It didn’t matter to him, since he was focused on driving. He relished driving. No matter how short or far a distance involved. On another occasion, we were joking about driving from Los Angeles up to Berkeley to visit the famous Cal campus up there, possibly doing so because we had heard that there was a pizza place near the UC Berkeley campus that had the best slices in California. This would be a six-hour drive, in each direction, driving up and driving back down. We were joking about it. He offered to go and get us some of that pizza. The drive time was an attractor to him, allowing him to have even more time behind the wheel. When I was first learning to drive, I remember that my grandmother was someone that did not favor the act of driving. She sternly cautioned me that I should avoid driving on freeways. Her logic was that the freeway was a last resort way to get to someplace and the speeds were so dangerous that I should take side streets instead of using the freeway. She also counseled me to try and group together my driving tasks, doing them back-to-back, rather than going on separate trips. This advice was based on the notion that I would then be on the roadways as a driver for a lesser amount of time. For the getting of groceries, my grandmother would drive to the local grocery store once per month, buy all the supplies she needed for about a month, and then drive home. The distance each way was maybe five miles. Not very far at all. Yet, she hated driving and was only doing the once monthly trip as an absolute “survival” necessity, getting the food and other items that she needed for a month at a time. If you sat in the car as she drove, you could see her hands clutching the steering wheel with a deathlike grip, her head pushed forward, her eyes intently scanning the surroundings, and the sweat coming down her forehead as she clearly disliked having to drive. In between those that love to drive and those that hate to drive are those that are somewhat ambivalent about driving. They will drive as needed, not fearing it, nor craving it. Essentially, driving is a chore. When the chore needs to be undertaken, so be it. No qualms. If they were to choose between driving a car and not driving a car, it would be an economic kind of decision as to whether driving was a more rational way to get to their destination or not. I was working at a major entertainment company based in Hollywood and the firm opted to have a New York City (NYC) based executive of the firm switch to working in Los Angeles. When he first arrived, I met with him and we chatted about the differences between Los Angeles and NYC. He mentioned that he did not own a car. I told him that having a car in Los Angeles is pretty much a must-have. He then somewhat embarrassingly told me that he had never driven a car. Having grown-up in NYC, he had never seen a need to learn to drive. He normally used the NYC subways and cabs and felt that driving a car was unnecessary for him. He hoped that in Los Angeles he could use our public transportation system and ridesharing to get around. I politely indicated that unlike NYC, the Los Angeles area is not really a mass transit kind of place, and the odds were that he’d eventually realize that driving is a fundamental condition of living here. Within about two months, he got his driver’s license, started actively driving, and bought a car. That’s Los Angeles for you. Driving Is A Privilege, Not A Right For those that do drive a car, they often are quite strong willed about their perceived “right” to drive. There are some people that seem to think that driving a car is a constitutional right, which is a misnomer. I am not sure why there are people that believe they have a right to drive. I’ve heard some claim that it is a basic or foundational right of all humans. Some say that driving is a core aspect of freedom, meaning that we are apparently all born to be free and driving is part of that moral immutable all-mankind code. Let’s be clear that by-and-large there is no viable “right” of driving. It is not in the Constitution. In the United States, driving is considered a privilege. This means that there is a governmental authority, usually the states, upon which there is a granting of the privilege to their citizens that they can drive a car. Since it is a privilege, this also means that the granting authority can invoke it, or the authority can revoke it, or the authority can suspend it.  Most states have requirements for you to be granted the privilege to drive, including requiring you to take a test, provide evidence of insurance, and take other steps to fulfill the stated requirements. Once you’ve jumped through the needed hoops, you are granted the driving privilege. If you abuse the privilege and violate the restrictions, the granting authority can opt to suspend your privilege of driving. For example, this could happen if you are caught and convicted of drunk driving or being DUI. There are many ways in which you might have your driving privilege suspended. Likewise, the granting authority can revoke your driving privilege altogether. In some rarer instances, your driving license might have driving impositions imposed, rather than being suspended or outright revoked. Once your driving privilege is suspended or revoked, or if you never had it invoked to begin with, it is generally illegal for you to be driving a car. I point this out because there is nothing that physically bars you from driving a car per se. You could still get behind the wheel, but you’d be driving unlawfully. In California, someone caught driving without a valid driver’s license is subject to being prosecuted as a criminal and could get up to one year of jail time. There is another myth about driving that many people harbor, namely that they falsely believe that the privilege of driving applies only to driving on public roads. These people are apt to quickly claim that they can drive without a driver’s license as long as they do so on a private road or on any private property. I hear people say this quite often. They could be mistaken. It is up to each state in the USA to decide what posture the state wishes to take as a granting authority about the driver license requirements concerning private roads and private properties. In Mississippi, it is against the law to drive DUI anywhere, including both public and private property. In Connecticut, driving recklessly is banned on both public and private property. Overall, the granting authorities tend to have various rules about public versus private property, providing a bit more leniency or exceptions if you are driving on private property. Sometimes there is confusion too about what private property consists of, in comparison to public property. You drive your car on public roads to a local mall. The mall is owned by a private company. Once you drive from the public roads onto the mall property, and drive around the mall parking lot, are you now driving on private property or public property? You would be tempted to say that you are driving on private property. That’s not often the case. In California, a private property that is open to the public, such as a mall parking lot, becomes bound generally by the rules of driving that apply to public property. The logic being that the private property is being used in a manner consistent with a public property, and therefore the state wants to ensure that the driving there be under the umbrella of public property driving rules. Being Protective Of The Driving Privilege My college buddy would have told you that he would fight to the ends of the earth to keep his privilege to drive. My grandmother, in spite of her hesitation about driving, would nearly be as earnest in her support for the privilege to drive. Whether you like driving or not, most people seem to be willing to acknowledge that driving is something that people should be able to do, as long as they do so responsibly. My children were eager to get their driver’s licenses. In our society, earning the privilege of driving is a kind of rites of passage. There were many of their peers that wanted to get a driver’s license, even though they had little or no intention of actually driving, at least not right away. Having a driver’s license suggests that you have become an adult, though the requirements often don’t require that you must have reached the legally stipulated age of an adult. It is a cultural notion of adulthood. I had used the word freedom earlier. For many drivers, the privilege of driving is a form of personal freedom. It provides a vital personal means of mobility. They can go where they want, when they want, and don’t need to rely upon others to do so. When my grandmother got older and was no longer a viable driver, it was devastating to her that she no longer had the privilege to drive. It was more than the act of driving, it was her spirit and view of the world was wrapped into the capability of being able to drive a car. The act of driving involves not merely the technical motions of maneuvering a car, it also includes a basket of other societal and cultural elements. You might drive because you enjoy it. You might drive because it gets you to work. You might drive because you can. You might drive to show-off to your friends. You might drive to socialize with others. You might drive to rush to a hospital because you need urgent care. And so on. Currently, we are a car focused society. It permeates most aspects of our daily lives. There are some analysts that say we are perhaps weaning away from driving and toward being driven. Gen Z is said to be eschewing owning a car. They are growing up with a ridesharing approach to transportation. This means that they are used to someone else doing the driving. This seems to be fine with many in the Gen Z segment. Baby boomers and Gen X appear to be continuing to cling to their driving privilege. This raises in interesting question. Will the newest generation and future generations perceive the act of driving in a different way than most of the rest of us do today? As the existing and older generations expire, will society shift toward a less vital perspective about individuals being able to drive? Maybe society will consider driving a “profession” such as being a chauffeur, like a cab driver or a ridesharing driver, and the everyday person won’t drive, or not drive much. When this topic comes up, there are some that will exclaim that you will take away their driving privilege over their dead body. You will pry the steering wheel from their cold dead hands. That kind of resistance is often heatedly offered. Why would there be a potential movement to somehow undermine the driving privileges that we enjoy today? What stokes these passionate drivers about being upset of having their driving “rights” denied to them? As I’ll describe in a moment, the topic of AI self-driving cars often gets this kind of visceral reaction about human driving as a potential for being on the chopping block. Some are worried, very worried, seriously worried, gravely worried that human driving might become extinct. AI Self-Driving Cars And The Human Driving Debate What does this have to do with AI self-driving cars? At the Cybernetic AI Self-Driving Car Institute, we are developing AI software for self-driving cars. At many AI and Autonomous Vehicles (AV) conferences, attendees often bring up whether or not human driving is going to last or not. This is a topic that can rapidly devolve into a muddied shouting match. I’d like to instead offer some calm thoughts on the matter. Allow me to elaborate. I’d like to first clarify and introduce the notion that there are varying levels of AI self-driving cars. The topmost level is considered Level 5. A Level 5 self-driving car is one that is being driven by the AI and there is no human driver involved. For the design of Level 5 self-driving cars, the auto makers are even removing the gas pedal, brake pedal, and steering wheel, since those are contraptions used by human drivers. The Level 5 self-driving car is not being driven by a human and nor is there an expectation that a human driver will be present in the self-driving car. It’s all on the shoulders of the AI to drive the car. For self-driving cars less than a Level 5, there must be a human driver present in the car. The human driver is currently considered the responsible party for the acts of the car. The AI and the human driver are co-sharing the driving task. In spite of this co-sharing, the human is supposed to remain fully immersed into the driving task and be ready at all times to perform the driving task. I’ve repeatedly warned about the dangers of this co-sharing arrangement and predicted it will produce many untoward results. For my overall framework about AI self-driving cars, see my article: https://aitrends.com/selfdrivingcars/framework-ai-self-driving-driverless-cars-big-picture/ For the levels of self-driving cars, see my article: https://aitrends.com/selfdrivingcars/richter-scale-levels-self-driving-cars/ For why AI Level 5 self-driving cars are like a moonshot, see my article: https://aitrends.com/selfdrivingcars/self-driving-car-mother-ai-projects-moonshot/ For the dangers of co-sharing the driving task, see my article: https://aitrends.com/selfdrivingcars/human-back-up-drivers-for-ai-self-driving-cars/ Let’s focus herein on the true Level 5 self-driving car. Much of the comments apply to the less than Level 5 self-driving cars too, but the fully autonomous AI self-driving car will receive the most attention in this discussion. Here’s the usual steps involved in the AI driving task:         Sensor data collection and interpretation         Sensor fusion         Virtual world model updating         AI action planning         Car controls command issuance Another key aspect of AI self-driving cars is that they will be driving on our roadways in the midst of human driven cars too. There are some pundits of AI self-driving cars that continually refer to a utopian world in which there are only AI self-driving cars on the public roads. Currently there are about 250+ million conventional cars in the United States alone, and those cars are not going to magically disappear or become true Level 5 AI self-driving cars overnight. Indeed, the use of human driven cars will last for many years, likely many decades, and the advent of AI self-driving cars will occur while there are still human driven cars on the roads. This is a crucial point since this means that the AI of self-driving cars needs to be able to contend with not just other AI self-driving cars, but also contend with human driven cars. It is easy to envision a simplistic and rather unrealistic world in which all AI self-driving cars are politely interacting with each other and being civil about roadway interactions. That’s not what is going to be happening for the foreseeable future. AI self-driving cars and human driven cars will need to be able to cope with each other. Period. For my article about the grand convergence that has led us to this moment in time, see: https://aitrends.com/selfdrivingcars/grand-convergence-explains-rise-self-driving-cars/ See my article about the ethical dilemmas facing AI self-driving cars: https://aitrends.com/selfdrivingcars/ethically-ambiguous-self-driving-cars/ For potential regulations about AI self-driving cars, see my article: https://aitrends.com/selfdrivingcars/assessing-federal-regulations-self-driving-cars-house-bill-passed/ For my predictions about AI self-driving cars for the 2020s, 2030s, and 2040s, see my article: https://aitrends.com/selfdrivingcars/gen-z-and-the-fate-of-ai-self-driving-cars/ Returning to the topic of driving as a human privilege, let’s consider the various ways in which this topic comes up when also discussing AI self-driving cars. Some Claim To Replace Human Drivers Entirely By AI Self-Driving Cars I’ll begin with the elephant in the room. There seems to be a contingent of pundits that often will get people agitated by saying that we should replace all human drivers with AI self-driving cars. When stated in that manner, it certainly seems like a rather stark proposition. Definitely has the potential to get the blood boiling. The rationale is usually predicated on the belief that AI self-driving cars will be safer as drivers than are humans. It is assumed by these pundits that by eliminating human drivers, there will be a complete elimination of all driving related injuries, deaths, and property damages that come from car accidents or incidents. This is the Holy Grail of AI self-driving cars, at least according to such pundits. We ought to carefully unpack such an incendiary claim. The first point to consider involves the timeframe involved in this claim. The proposition is often stated as though starting tomorrow we will round-up all driver’s licenses and toss them into a mighty bonfire. For those of you that relish driving your car, apparently by the end of the week you’ll no longer ever get to touch a steering wheel or use the pedals of a car, again, ever again. Sorry, but it’s for the good of society, tough luck to you. I think this is either unintentionally (or sometimes intentionally) used to get a knee-jerk reaction and have a shock effect. That being said, I know some that have lost a loved one via a car accident, and for which they are desirous that no one else ever suffer such a loss, therefore the AI self-driving car seems like a welcome way to ensure that others don’t have to undergo what they have had to deal with. Those people are doing what is in their hearts, and sincerely believe in the idea of getting human drivers out-of-the-loop of driving. The thing is, realistically we are decades (at least) away from being able to even consider doing what they are proposing. There are about 250 million cars in the United States today. About 15 million or so new cars are sold each year in the United States. If we had true Level 5 AI self-driving cars, how many years would it take to gradually do away with the existing stock of conventional cars and bring into the marketplace the new Level 5 self-driving cars? Would we need to replace all 250 million conventional cars with the same number of AI self-driving cars? Some argue that with the gradually shifting trend towards a desire to use ridesharing, we presumably won’t need to replace all 250 million conventional cars and some lesser number of AI self-driving cars would suffice, since they would be used on a shared basis. Okay, if that’s the case, how many AI self-driving cars would there need to be in circulation? It still has to be into the many millions of cars, double-digit or low three-digits, so let’s pretend for argument sake that it is say 100 million such AI self-driving cars. Do you realize how long it would take to make that many cars? And how long it would take for people or companies to purchase such cars and put them into use? There is a thing known as AI self-driving cars at scale. This means going far beyond merely handfuls or hundreds of AI self-driving cars and moving toward having thousands and hundreds of thousands of them. Millions is a whole another level of scaling. We are right now working on the baby steps. Dealing with millions upon millions of AI self-driving cars is very far off on the horizon. It is an act of fiction to simply assume that if you can make one AI self-driving car that you can just crank out millions of them and put them onto our roads. This is a fallacy of logic. There is another perspective that says the number of AI self-driving cars might become even higher than the number of conventional cars in-place today. In essence, maybe we might end-up with maybe 300 million AI self-driving cars and no convention cars, over time. Why? Because there is the “law” of induced demand. When you make available a new means of transportation, what can happen is that the suppressed need of transportation can emerge. This implies that there is a possibility that the existing base of conventional cars is insufficient to meet the total demand that will emerge once AI self-driving cars arise. The counter-argument is that the conventional car of today is not especially being shared. The shared aspects of an AI self-driving car, assuming it will be shared, would suggest that the AI self-driving car can meet more driving demand than does a conventional car. Also, the AI self-driving car can be used 7×24, whereas conventional cars are “limited” to needing a human driver, which is not as readily viable. I defy you to provide an economic means by which any this would happen in any short time frame on the scale of allowing society to stop all human driving and rely instead on AI self-driving cars. It really doesn’t square out. This means that when you start saying that there won’t be anymore human driving, due to the advent of AI self-driving cars, you are really talking about something that might happen many decades from now, maybe. Furthermore, we don’t really know what society might be like by the time that such a possibility even might be available. Flying cars? Personal jet packs? Mass transit unlike the kind that we know of today? There are so many changes bound to happen that it is not contextually sensible to claim that we would overnight stop people from driving. It could be that by the time the advent of mass-scale use of AI self-driving cars arises, people won’t be doing conventional driving very much anyway. There might be an ongoing shift in society toward not driving a car. Thus, by the time that there is an initiative to close off human driving, few will care much about it anyway. My point is that having an argument about needing to give-up your privilege of driving, due to the pervasive adoption of AI self-driving cars, sufficiently to overcome the loss of human driving and yet still meet driving demand, it is premature to argue as though this is real, and instead it is merely an abstract proposition, which might or might not come to fruition at some far-off future. For my article about induced demand, see: https://www.aitrends.com/selfdrivingcars/induced-demand-driven-by-ai-self-driving-cars/ For the use of AI self-driving cars non-stop, see my article: https://www.aitrends.com/selfdrivingcars/non-stop-ai-self-driving-cars-truths-and-consequences/ For the rise of ridesharing and AI self-driving cars, see: https://www.aitrends.com/selfdrivingcars/ridesharing-services-and-ai-self-driving-cars-notably-uber-in-or-uber-out/ For my claim that zero fatalities is zero chance, see my article: https://www.aitrends.com/selfdrivingcars/self-driving-cars-zero-fatalities-zero-chance/ Narrower Elimination of Human Driving I’ve tried to make the case that a full-scale whole-hog elimination of human driving as a result of the emergence of AI self-driving cars is not in the cards as yet, and it is a distant future idea, which we can only speculate about. Some worry about it now, some don’t. Some say let’s cross that bridge when there are actually viable signs that the bridge is actually up ahead. Others say that it is worthwhile to ponder what might be in the future, regardless of how far ahead it might be and no matter how theoretical the debate might be. There are some pundits that once they are presented with such a view and the suggestion that the urgency or near-term does not seem to encompass the outlawing entirely of human driving, not in any practical sense, will recast how the elimination of human driving might happen. In this recast perspective, the scope of elimination might be narrowed, so let’s consider that alternative. Suppose the emergence of AI self-driving cars suggests such autonomous vehicles can work safely and appropriately on our roadways, but maybe only best when geofenced and kept to areas that are comprehensively mapped and understood.  Rather than using them everywhere, perhaps they are limited to being used in certain areas. A downtown area might declare that henceforth there are only AI self-driving cars allowed to drive in their downtown area. No human driven cars allowed. Does this mean that human drivers are going to lose their privilege to drive? Not really. It means that you cannot drive a car while inside the downtown area. You can still drive a car on the freeways, highways, and streets that are outside of the downtown area. I realize you might get upset about the restriction of not being able to drive while in the downtown area, but this seems to be not be much of a valid complaint. There are many areas that already restrict the driving of cars and instead have local shuttles, buses, rental bikes, scooters, and encourage walking rather than driving. You won’t get much sympathy from me about your being prevented from driving your car in that downtown area. Live with it. You still have the driving privilege. You can still drive while outside of the downtown area. Some though tell me that they are worried this is a kind of slippery slope. First confining step, they cannot drive in a downtown area. Next confining step, it will be that you cannot drive in a suburb area. Next down the rabbit hole, you cannot drive on certain freeways or highways. In a “death by a thousand cuts” manner, your privilege of driving is being eroded. Some suggest it is all a conspiracy to ultimately rob you of the privilege of driving. As an aside, I’m not much of a fan of conspiracy theories. I doubt that this would be a grand scheme. I do concede though that something like this might happen in an incremental fashion, one slow step at a time, but not due to a sinister secretive underbelly of miscreants having devilish plans. For my article about conspiracy theories in AI, see: https://www.aitrends.com/selfdrivingcars/conspiracy-theories-about-ai-self-driving-cars/ The time frame is once again decades away, at best. Could though it be the case that a long time from now the only place you can drive a car would be in a few leftover places? Sure, I suppose that is possible. Some even envision a future whereby the only human driving that will occur involves driving on a closed track. There might be locales that setup closed tracks and let you drive a car, perhaps an old farm converted to a closed track or other expansive property transformed, doing so for the thrill of driving (and as a potential money maker). These would be amusement parks for driving. There are similar kinds of tracks today for those that want to do race car style driving. These future tracks would presumably be used by anyone wanting to simply be able to drive a car, even at a scant five or ten miles per hour, reinvigorating the excitement and joys of driving a car. There is perhaps an irony about this notion, since today we have AI self-driving cars that make use of closed tracks for providing grounds. Could it really be that someday the AI self-driving cars would drive where we as humans drive today, and the humans of the future would be relegated to only being able to drive on closed tracks that AI self-driving cars once were saddled to use? It’s a bit of conjecture, one would say. In any case, notice that human driving is still being allowed. It is not the complete elimination of human driving. For those of you determined to keep the driving privilege, you might have a pained expression and be saying that a driving privilege that only applies to driving on specially provided closed tracks or on only the off-the-beaten path roads is not any more a bona fide driving privilege. The restrictions are so severe that it might as well be the wholescale elimination of driving for humans.  Well, I get your point, but once again we are debating an obscure possibility that is far away in the future. For my article about human driving foibles, see: https://www.aitrends.com/selfdrivingcars/ten-human-driving-foibles-self-driving-car-deep-learning-counter-tactics/ For closed tracks, see my article: https://www.aitrends.com/selfdrivingcars/proving-grounds-ai-self-driving-cars/ For self-driving cars needing to adopt defensive driving techniques, see my article: https://www.aitrends.com/selfdrivingcars/art-defensive-driving-key-self-driving-car-success/ For my article about… Read more »
  • White House Has Launched ai.gov as Central Resource for AI Efforts
    The White House recently launched an ai.gov website to share AI initiatives from the Trump administration and federal U.S. agencies. Featured initiatives include a National Institutes of Health (NIH) biomedical research project using AI and a recent Department of Transportation report on autonomous vehicles. A number of initiatives — some launched during the Trump administration and others during the Obama era — are highlighted on the website, including the Department of Energy’s efforts to create supercomputers and AI Next, DAPRA’s $2 billion investment commitment to solve big AI problems, which was announced last fall. The website launch came a month after the Pentagon released its AI strategy, which will be led by the newly created Joint AI Center. On multiple occasions, the website cites the American AI initiative President Trump issued by executive order last month, which, among other things, called for sustained AI research funding for federal agencies. Critics of the president’s plan have called the initiative vague and lacking substance. The website also points out that the United States AI R&D strategic plan, first rolled out in the final months of the Obama administration, is currently underway. Concurrent with that effort, the Computing Community Consortium, an organization of AI researchers across the United States, is writing a 20-year AI research roadmap to define academia, business, and government priorities to move AI forward. The roadmap calls for the creation of national AI labs and competitions, as well as an Open AI system. With businesses deploying artificial intelligence and the technology expected to transform or eliminate a large number of jobs, politicians are becoming increasingly interested in AI. The 2018 AI Index report found that mentions of AI have gone up among members of the U.S. Congress, as well as in houses of parliament in Canada and the United Kingdom. As things heat up ahead of the 2020 U.S. presidential race, Democratic candidates who want to take on Donald Trump are also talking more about AI and the future of work. Bernie Sanders made his stance on AI part of his campaign announcement and a cornerstone of his platform. Democratic presidential candidate and businessman Andrew Yang surpassed the 65,000 donor mark last week, clearing him to participate in the first presidential candidate debate. Yang believes AI will be responsible for the greatest shift to the U.S. economy in the country’s history and wants every U.S. citizen aged 18 to 65 to receive a $1,000 universal basic income. AI regulation is also fueling much of the conversation. Following news that IBM used photos of people from Flickr’s Creative Commons website without their knowledge, a bipartisan group of U.S. senators proposed the Commercial Facial Recognition Privacy Act of 2019. Under the proposed law, companies would have to inform consumers when facial recognition software is being used. Read the source article in VentureBeat. Visit the White House AI website. Read more »
  • Walmart Employing Thousands of Robots Scrub Floors, Stock Shelves
    A new tech trend has emerged at the world’s largest retailer, as Walmart brings on board thousands of robots in nearly 5,000 of its 11,348  stores. According to CNN Business, these robots will be scrubbing floors, scanning boxes, unloading trucks and tracking shelf inventory at mostly domestic U.S. locations. Robots will replace lower-level jobs—serving in janitorial functions as well as performing basic inventory work—in order to manage rising costs. A new robot unloader has already been used on the docks in hundreds of stores, pulling boxes from delivery trucks while automatically scanning and sorting merchandise. The unloader will be deployed at over 1,100 retail locations in the near future. “Automating certain tasks,” according to Walmart CEO, Doug McMillon on CNN, “gives associates more time to do work they find fulfilling and to interact with customers.” Continuing this logic, the retailer points to robots as a source of greater efficiency, increased sales and reduced employee turnover. Tests in dozens of markets and hundreds of stores have proven the effectiveness of the robots, but how will replacing people with machines actually reduce turnover? Perhaps if you are not hiring people, they can’t quit… so turnover is reduced? That assertion remains to be seen, but there does seem to be powerful support for driving greater profitability via robotics. “As we evolve, there are certain jobs that will go away,” said Michael Dastugue, Walmart U.S. CFO. By sharing this in a March analyst call, Dastugue may have unintentionally nominated himself for the understatement of the year. The message is clear: robots continue to be a viable resource for replacing lower-level jobs. The company states that this investment will allow the human workers to execute more varied tasks—as the robots take on the work that humans don’t want to do anyway. (For more from Forbes on the topic of employment risk due to automation, check out “Should We Be Scared of Our Robotic Colleagues?“) Profit vs. People It’s no secret that, in 2018, over a dozen major retailers filed for bankruptcy.  Sears, Diesel, Beauty Brands, Mattress Firm and many others are restructuring—or disappearing—due to bankruptcy. Walmart’s obligation to its people remains strong—if, by “people” we mean “shareholders.” Business considerations are behind the move to utilize new technology, and employees will have to adapt. Consider these startling statistics in a recent study commissioned by Bossa Nova Robotics. (Full disclosure: Bossa Nova is the manufacturer of the inventory-assessment robots at Walmart, and others. With over $70 million in capital raised, this Carnegie-Mellon powered startup is revolutionizing retail with robots, according to sources at CNBC.) It’s In Inventory, Right Now Based on feedback from 100 retail executives, all from companies with more than $500 million in revenue, 99% reported some kind of inventory problem. Additionally, the survey revealed: 87% of respondents said inaccurate inventories are to blame for more lost revenue than stealing 92% said their stores spend more time identifying inventory issues than they do implementing solutions 81% said they feel their stores are only keeping pace or actually falling behind technologically, despite the availability of new technologies And perhaps most compelling: 76% said the introduction of robots in stores would improve employee productivity Read the source article in Forbes. Read more »
  • Women Seen Facing Disproportionately Negative Consequences from AI
    Apple’s Siri, Amazon’s Alexa, Netflix’s prediction of your next favorite show—we’re already living with artificial intelligence, and its adoption by the business world will only increase in coming years. We’re already hearing about AI’s potentially disastrous impact on the labor market, but how will these technological tools, designed to augment or replace human cognition, affect women? The first-ever study to map the labor consequences of AI for women, published by the Institute for Women’s Policy Research (IWPR), is a reminder of the intractable stubbornness of gender inequality, despite, or increasingly, because of, the direction of our digital future. While estimates vary hugely, IWPR calculates that although women make up just under half the US workforce, they will make up nearly 60 percent of the workers at highest risk of being displaced by technology. Today, argues Ariane Hegewisch—IWPR’s program director for employment and earnings—“The impact of technology critically depends on how it is implemented and who is at the table when it is implemented.” Overall, IWPR estimates that there are 10 women for every seven men who work in jobs “threatened” by technological advancement (jobs that have at least a 90 percent likelihood of going extinct). Moreover, these jobs are concentrated in relatively high-paying positions, compared to the male-dominated jobs that will decline. So as women seek upward mobility in the face of long-standing employment barriers, Hegewisch explains, “the threat that tech poses to those jobs may also mean that you eliminate some of the ladders that are now available for people to really climb into a better economic prospect.” Whether you’re an accountant competing with bookkeeping algorithms or a senior bank teller soon to be replaced by an ATM, automation could wreak havoc on women’s participation in the workforce if robust protections are not put in place. In addition, the jobs that will survive AI disruption are disproportionately low quality, such as senior- and personal-care jobs, domestic work, and adjunct teaching jobs. The promise of tech to improve jobs—making them healthier, more enjoyable, less physically taxing and more flexible for workers—is largely driven by politics and extant hierarchies in the workforce. Workers who lack power in general will be less resilient and adaptable when technology begins to marginalize them. Decisions on when and how to introduce new technology, Hegewisch argues, hinge on whether the disruption is used “to complement people’s jobs or to replace people.” One solution could be to retrofit traditional collective bargaining for future change: For example, union contracts for Marriott Hotel workers include rules safeguarding members from the impact of automation, requiring advanced consultation and preparation of compensatory measures when potentially disruptive technology is introduced to the workplace. The jobs most directly, and positively, impacted by tech are, of course, in technology-based industries. But with a massive gender gap in those workforces, even as Silicon Valley expands and advances, women will likely continue to be marginalized in lower-paying or lower-ranking positions. Paradoxically, women working in the industries making up the technological cutting edge face some of the worst employment trends. Over the past 20 years, women’s representation has declined in the three largest tech sectors: computer scientists and systems analysts, software developers, and computer support specialists. Despite Silicon Valley’s progressive cultural patina, women of color are even more underrepresented in the current tech workforce: Even amid growing cultural emphasis on female-friendly STEM education programs and diversity in tech, women are still stuck on an unlevel playing field: “for women and men working at the same level of digitalization, women face an earnings gap in returns on digital skills of 41 percent.” Another sector that will proliferate with automation is platform-based work, like ridesharing or digital “tasking” gigs. Though currently these make up just a small fraction of the job market, they are shaping patterns of commerce and culture for the digital age. And yet they are also pushing many workers into erratic schedules and unstable jobs with virtually no labor protections. Landing a fast gig online may mean less transparency, less ability to negotiate working conditions, and no effective way to organize with peers and colleagues, leading to economic insecurity and exploitation. And others are excluded from these platforms altogether: IWPR warns that the shifting of decent work to online platforms “puts older and immigrant workers, many of whom speak English as a second language or have less familiarity with social media, at a disadvantage.” The key to navigating these future trends is to get ahead of and harness the automation wave: First, comprehensive training programs could allow the workforce to be more adaptable to technological changes. Read the source article in The Nation. Read more »
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