Tag Archives: autonomous vehicles

Machine Learning Executive Summary

It is essential to understand what exactly machine learning is and how it works in order to understand the affects it has and will have on society. In basic terms, machine learning is a computer program that can learn and adapt to new data without human interference. It is a field of artificial intelligence that keeps a computer’s built-in algorithms current, regardless of changes in the worldwide economy. As more information it is given, the more it learns and the more accurate it becomes with the result. Therefore, it recognizes patterns and will give updates as relevant data is fed through. Deep learning is a subset of machine learning, which helps the algorithm learn without a human programmer. Through deep learning, information filters through a hierarchy that starts simple and gradually becomes more complex and specific. As the data is going through each level, the algorithm is able to determine what the object or data point belongs in what category. The process behind deep learning is essential to the success of machine learning. Since there is a grand amount of information that the algorithm must analyze to come to a conclusion, a human programmer would not be able to sit there and go through every single point – that would be extremely expensive and time consuming. Many industries and companies are beginning to use machine learning, to cut costs and become more efficient. Some of those industries include transportation, advertisement, medical, education and entertainment.

Transportation & Advertising – Antoneta Sevo

One industry that is being hugely affected by machine learning is transportation, particularly by autonomous vehicles. Though taxi companies like Waymo and Uber are implementing this technology within their services, companies like Tesla are creating vehicles that will be available to consumers for purchase. Tesla has introduced a system called Enhanced Autopilot that allows the driver to sit in front of the wheel and do nothing while the vehicle operates itself. The system includes features like active cruise control, forward collision warning, match speed based on traffic conditions, change lanes without the driver’s input, merge on and off highways and park itself. One main goal of Tesla is to successfully have a car drive itself across the country from LA to New York. Machine learning works by interpreting the ever-changing scenery detected by the sensors surrounding the vehicle. Once the technology is perfected within the industry, there may be no limitations to the future of driving.

As machine learning continues to be introduced into different industries, the amount of information being collected about users and consumers continues to increase. These algorithms are created to handle and sift through large amounts of data in order to identify a pattern and produce a result based on the patterns. This is beneficial to companies for advertising purposes so they can recognize habits of consumers. Essentially, companies track your browsing history to suggest products or other websites. They are also able to figure out how much the user can afford and when they might be able to afford it based on their demographics and when they usually purchase products. Since it would be time-consuming and expensive for a human to find those patterns, an algorithm is put in place and works in real-time. It is a much more efficient way to produce targeted advertisements. The more a user searches and buys, the more information the program collects, and the more accurate the advertisements become. By using machine learning, Target knew a teenager was pregnant before her father did. The algorithm noticed a pattern in her internet searches and sent advertisements designed for pregnant women to her house. That was how her father found out. Machine learning can collect an endless amount of data in order to have accurate predictions, and in some cases, they can be too accurate.

With new technology comes ethical issues and implications. When it comes to autonomous vehicles, many things can go right and there would be a smooth ride, but many things could go wrong as well. For example, the algorithm may make the wrong decision, misinterpret an object, or can be hacked, causing an accident. In order to avoid the program from making the wrong decision or misinterpreting, quantum computing must be implemented so the algorithm could work faster. It is important for companies to consider full transparency, so people understand how the car operates and how it is protected. This also means certain types of cybersecurity and encryptions should be put in place to protect the car from being hacked and causing harm to people on the road. Most car companies do not operate in an ethical manner now, however, they should begin to think differently in the future. There are also many different ethical issues that arise through the advertising industry. Once people find out they are being tracked and targeted, they begin to feel uneasy, as they should. Companies should allow consumers to opt out of their services so users will feel more in control of their information. Also, it would be beneficial if consumers were more aware in order to identify what these big corporations are tracking so they can do things differently to take themselves out of being tracked. Consumers can use a Virtual Private Network, use a search engine that does not track them like DuckDuckGo, or they can choose to use an opt out service. There are plenty of options, the first step, however, is to be aware that something is wrong.

The final scare that comes along with new technologies in machine learning and Artificial Intelligence is unemployment. Many articles talk about how many blue-collar jobs will be obsolete in the coming years and most of them are not wrong. It is a topic that those who want to be employed have to know about. Some jobs that may be affected in the future are schoolteachers, taxi or commercial drivers, positions in the medical field, etc. This technology has the potential to affect an abundant amount of jobs across plenty of industries, which means a solution must be in place before mass unemployment occurs. A short-term solution may include technology companies implementing training programs for current employees to learn the new (and necessary) skills. Another solution might be considering a universal basic income for those who are unable to find work or for everyone if machines and Artificial Intelligence take a significant amount of jobs. In time, as more and more jobs disappear, we, as a society, will have to redefine the definition of work. Millions of jobs will disappear and we will have to accept the change. In order to survive the inevitable societal and economic change, we need to accept that it is happening now. The next step is to begin learning in an exponential way instead of a linear way. The way our world functions now will certainly not be the way it functions in the future and we need to prepare to face it head on.

Medical & Education- Mayra Luna

Machine learning is all about data recollection and data processing. Its capability of analyzing huge amounts of data will eventually replace a great number of human jobs, even those that require a higher education. However, as explained by Medtronic CEO Omar Ishrak, the real value of artificial intelligence is in making more efficient use of human resources in healthcare.  For example, IBM’s Watson can read 40 million documents in 15 seconds, optimizing time and performance. Healthcare has loads of data: Test results, consultation notes, scans, appointment follow ups, etc., creating an ideal environment for the use of Machine Learning (More data, better results).

The ability of computer systems to assume tasks for humans has improved efficiency in healthcare. Now hospitals are getting into the game, deploying AI to take on challenges from diagnosing patients more quickly in the emergency room. Other technology developers, are focusing on software that can read CT scans and other medical images and then suggest the most likely diagnosis by reviewing similar images stored in patient databases. And these programs can accurately process these tasks far faster than human technicians. For example; Stanford researchers have developed an algorithm that offers diagnoses based off chest X-ray images. It can diagnose up to 14 types of medical conditions and is able to diagnose pneumonia better than expert radiologists working alone.

Machine learning can help healthcare executives and caregivers with things like precision medicine. Precision medicine is “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” This approach will allow doctors and researchers to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people. It is in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for the average person, with less consideration for the differences between individuals. For example, tech giant Microsoft wishes to improve health care using machine learning and AI. As part of this initiative, Microsoft is expanding into cancer research and treatment, and its approaching cancer cells as if they were a glitch in a computer system.  

Though ML promises to drastically improve the efficiency and effectiveness of healthcare, when it comes to predicting, diagnosing, and treating medical conditions there are many concerns: Data quality, Manipulation risk, Obscured logic

Four factors should be present to improve accuracy and overcoming risk: Confidence scores, Complex rules, Clinical data, Natural language processing

We must understand that machine learning is a powerful tool, not a complete solution. There is no substitute for a skilled physician’s expertise, however with the right data, ML can certainly help accelerate diagnosis, treatment, and program development.

Machine learning systems can give teachers more free time to actually teach and mentor on a more personalized level, instead of focusing on the never-ending grading and lesson planning. In addition, the current learning system consists of a “one size fits all” model. We are in desperate need of a system where the educational experience can be personalized to each students abilities and needs. Machine learning could address these issues by collecting and analyzing the data generated by students, identifying meaningful patterns and transforming that information into structural knowledge. In other words, when the student interacts with a digital learning platform, the machine learning system can accurately predict and better assess that person’s educational level, being able to tailor specific material for that individual.

Specific roles and examples of Machine Learning and its use in education: Content analytics, learning, analytics, dynamic scheduling platforms, grading systems, process intelligence, predictive analysis.

The ethical issues may include:

  • Unemployment: Labor is concerned primarily with automation. As we continue to implement machine automation, certain jobs (predictable physical work) could disappear. While this might sound like something bad, we must also keep in mind that new jobs will be created due to this disruption. The real question is how are we going to educate people for these new jobs?
  • Inequality: By using artificial intelligence, companies can drastically reduce the reliance on human workforce, which means people will work less hours (therefore make less income, broadening the labor gap).
  • Humanity: Humans are limited, while machines have unlimited resources. How will machine learning affect the way we behave and interact with others? Will we soon be interacting with machines as if they were humans? Will machines adapt to cultural norms?
  • Algorithmic Bias: Blind spots or biases in the algorithms could lead to discrimination against certain types of people (As seen in AI systems that can tell if you are homosexual).

Entertainment- Olivia Finan

The role that machine learning plays in entertainment is very interesting.  A common belief among the class is that entertainment is an industry that will more or less remain untouched in the coming years by the disruptive technology. However, research shows that this may not be the case. We have already begun to see drastic changes in the industry throughout the years, specifically in music and cinema. AI systems are being created and coded to be able to sift through video footage and put together a 10 minute video using several clips in under and hour.  This is impressive timing when you consider how long it takes to watch hours of footage, edit, tag, and compile all those clips into one succinct video my hand.

Filmmaker Oscar Sharp and technologist Ross Goodwin fed a machine learning algorithm with a bunch of Sci-Fi movie scripts to see what new script it would spit out.

The trends that we think will see in entertainment are not necessarily what is coming. How this content is created is what will change how the industry progresses through the coming years and how it is affected by disruptive technology. The entertainment industry is a prime example of how we must pivot and change how we do things rather than change what we do.

More so then ethical issues, legal issues come into play when talking about the entertainment industry. Laws regarding copyright infringement are always looked at thoroughly in this particular industry. However, ethical issues tend to revolve around the consumer rather then the company or a performer. For example, at live events, issues about safety come into play. This means that a major role would be ensuring that concert or festival goers are safe at the venue. This is just one example of what time of ethical dilemmas companies have to deal with in the entertainment industry.  What these companies now have to begin thinking that the ethical implications that once were may not be the same anymore. We may not be having live concerts, there might be other ethical issues that arise, and that is what the industry predicts.

The entertainment industry is not exempt from responsibilities associated to employment. However, if there is a change in music, for example, and humans are no longer the ones producing it then what happens to the people who world at record labels, or what happens to the artist themselves? This section of the machine learning project will explore all the changes the industry sees coming in the future and how the major players are beginning to prepare and adjust to the changes.

Ethical Implications of Autonomous Vehicles

Autonomous vehicles will one day become the normal way to travel. However, there are still plenty of ethical issues and dangers this new technology holds. It is easy to forget about the impacts technology has on society because everything is innovative and exciting. Nevertheless, the ethical implications must be discussed in order to avoid potential accidents or tragedies. The possible dangers might include the likelihood of a hacking or if the vehicle does not make a decision fast enough. Some of the ethical effects can be what kind of decisions should be made in certain situations and if programmers should have transparency with consumers, so they know exactly what the autonomous vehicle entails.

These cars rely on machine learning in order to evaluate situations and make a decision. The computer is simply not given a set of rules to follow. Instead, it is fed images of objects – for example, a pedestrian, a ball, another vehicle, etc. – and tries to guess what that object is. In the beginning, it will guess wrong. However, as time goes on, the program adjusts itself, and continues to try as more information it is given, it begins to learn what is what with the help from the cars sensors. If there is unidentified object in the road, the car should reduce speed or stop altogether. Another way for the vehicle to learn is by feeding it certain traffic information and the programmer would say the right way to get out of it. The algorithm will learn from that, along with other aspects of a situation, and determine the correct way to get out of it. One of the main issues is how fast these computers will be able to make decisions. While humans drive, it takes a split second to make a mistake and terrible things could happen or it takes just as long to avoid that. Most people have good reflexes and are able to avoid a tragedy. Autonomous vehicles must have that same ability to avoid accidents. Machine learning and quantum computing must work together in order to allow those cars to make effective and quick decisions. The programmer must teach the computer the basic rules of the road and allow the machine to learn impactful and successful ways to avoid accidents.

Another issue that stems from autonomous vehicles is the possibility of someone hacking the program of one. Skilled hackers are able to break into almost anything, so how is a vehicle any different? Software and algorithms will power them, which can be susceptible to malicious people who have the intent to harm others. It might not be a trend now, however, as this technology becomes more normalized, anything is possible. Car and technology companies claim that the consumers will be safe from hacking, however, it would be in the best interest of the consumer to not take their word. Some in the industry have waited to announce a recall until it became cheaper than paying the wrongful death lawsuits. It would take enough steps in the right direction for car and technology companies to act in an ethical manner. It would be best to not trust their word. As the conversation about hacking becomes more popular, there should be laws requiring cars to have certain types of encryption and cybersecurity in order to protect the passengers of autonomous vehicles. These companies should also consider the approach of a greater transparency with their consumers. That way, if they are ethical and genuine, consumers could trust using their products, in this case an autonomous car.

Though autonomous vehicles will be able to solve many problems and subtract human error, it is important that it does not replace it with programming errors. It is also essential that the algorithm learns in an ethical and correct way. It may take time to determine what that is, however, the minimum amount of accidents and casualties is desired. Car and technology companies must implement sophisticated cybersecurity to protect against any type of hacking that might take place for any reason. There is a long road ahead when it comes to creating the software in the right way. That way when it learns, it learns in a correct and moral method. Machine learning plays a big role in the success of autonomous vehicles and though there will be problems, it would be beneficial to minimize them as much as possible.

The Future In Energy Transformation

What will the future of Energy be like in 30-50 Years? There are higher future energy demands; in the next 30 to 50 years and our global environment will demand more and more energy. There are three driving forces that will make energy more in demand. There is a vast increase in technologically dependency. The emerging technologies (i.e. autonomous vehicles, advanced genomics, mobile) have the potential to change and reshape the surroundings in which we live and work. The extensive use of the Internet whereby people rely extensively to communicate through email, the use of online banking, tools to find information and many more. These are just a few of things that people are so reliant on the internet. It has been estimated that by 2051, the US population is projected to reach the 400 million threshold, and 420 million by 2062. The future of energy is also affected by the supply side of energy, whereby various sources of energy are working together to make fuel in order to satisfy the increasing demands in the next 30 to 50 years. As we noted earlier coal was the dominant source of energy in America, but in recent years the use of coal has decreased drastically, as such in the future will be the second most protrusive source used in the future as energy over the next 30-50 years. This decrease in coal is predominantly due to coal plants becoming older and obsolete. As a result, the closing of these coal plants mean that there will be less coal being produced. The closing of old plants does not necessary induce for new coal plants to be built. It is estimated that coal with drop by 30% of the nation’s energy in the year 2064.   Another agent of energy change is the increase of renewable energy. Solar and wind are two examples. It is vital that both government and businesses are knowledgeable on the upcoming new technologies so that they can begin implementing strategies and start preparing for its impact.   In recent years there have been numerous disruptive technologies introduced into the public sector. Natural Gas will be considered the primary source of energy. The growth of natural gas will be the biggest change. Natural gas is considered to be in abundance and cheap. Currently, 25% of natural gas accounts for the production of electricity, and the majority of homes are being heated by natural gas. Due to the high gas demand, low cost, and the abundance of it, natural gas will be the driving factor of utilization in the future. In the year 2040, natural gas is estimated to make up 35% of US energy production, resulting in being the driver source of energy surpassing coal consumption. It is apparent that the advancement will forever revolutionize the lives of many people, businesses and especially the overall economy. Energy transformation is being driven by five global megatrends interacting with and amplified by a set of shifts taking place within the power sector. The five megatrends-technological breakthroughs; climate change and resource scarcity; demographic and social change; a shift in global economic power and rapid urbanization – are challenges for businesses. Is the Energy sector ready to revitalize its business model to sustain current and future disruptive innovations? In the near future, society will be forced to find new ways and will be required to research and develop alternative energy sources. If no action will be taken in coming up with new ways to generate energy there will be an energy crisis in this century. Breakthroughs and advances have been made in the technology sector of renewable energy. Energy companies are addressing the growing demand of having to provide new products and services by making strides in how energy sources are extracted, created and used. Renewable energy technologies are being utilized such as solar wind and hydro power, which are more efficient for meeting today’s growing energy demands. According to Forbes “The development of energy storage technology is going to be one of the defining features of the 21st century’s energy landscape”. Energy storage technologies allow you to get the most out of renewable energy resources such as wind, which produces more power than it is needed at night where much goes to waste. They can use this wasted energy to heat homes and offices. One of the future sources of energy storage as we said is batteries. Batteries are an integral part of an electric vehicle. This energy storage technology, i.e. “zombie” batteries are being used in the existing electronic vehicle. As the demand increases and the number of electronic vehicles are increasing in purchases, charging stations are being set up in various places. It has been estimated that a lithium ion battery could last from 5 to 20 years and still retain 80% of its charge. The lithium ion battery afterlife can be utilized in homes.

http://video.cnbc.com/gallery/?video=3000397437

 

 

 

Various countries utilize solar power, wind power and water power as their renewable energy. It is estimated that in the future renewable energy sources will be a thing of the past. Korea is planning to invest $36 Billion in renewable energy by year 2020. They are planning to use this money to develop renewable energy industries, such as solar and wind power and eco-friendly power plants by year 2020. It is estimated that power plants will generate 13 million kilowatts of electricity manually which is an equivalent of 26 coal plants. In addition, 4.5 trillion is to be invested in energy storage and 2 trillion in eco-friendly power plants. Another advantage to this investment of building plants and investing in renewable energy will result in an increase of 30,000 jobs by 2020. The Netherlands has built a high-tech Dutch solar bike path. This high-tech solar bike path is called “SolaRoad”, whereby one of the two lanes has solar panels which serves as the feeder of energy back to the grid. The solar panels are designed to be able to generate enough electricity to power homes. After a year of testing it was concluded that the solar panels generated enough energy to power a home for a year just from operating for only six months. There is still more work to be done with improving these solar panels; an issue occurred whereby a portion of the panels peeled off and the path had to be closed off. Japan has entered the solar panel by placing them on their rooftop. Japan has begun work on what will be the biggest floating solar farm. This solar farm is being built on a reservoir. This is estimated to supply energy to approximately 5,000 households when it is completed in 2018. China, Brazil, Egypt and India are also countries which have joined in putting solar panels on their rooftop. The government is encouraging Tokyo builders to make buildings more energy-efficient with solar panels in addition to having form of storage and other devices such as fuel cells. California installed solar panels which resulted in an excess of solar energy. California is considered the leader in the production of solar energy.

 

 

 

 

Will Automated Vehicles Change the World?

In a world that is defined by one constant: change, one single technology being called “ the most influential technology in the past century” is a bold statement that people cannot ignore any longer. But is this truly a technology which will revolutionize the way in which we see our world? Is this really the aforementioned “most influential technology in the past century”? As we’ve covered previously, car manufacturing and transportation, two of the sectors that people are perhaps most familiar with and can relate to will experience massive changes that will effect not only the people in the industry, but also the world at large. And yet, the positive aspects of this technology are immeasurable. Looking at the U.S. transportation system current day, once a person is 17 they are flung into the traffic and daily struggles of navigating on some of the most dangerous roadways. Now stop and think for a second as the future of driving will be changed with upgrades to the standard vehicle today: Roads will be safer, traffic could be eliminated, and “passengers” (anyone in an automated vehicle) will experience an increase in the amount of free time they have due to shorter rides. 

We can see one very apt comparison can be made when buildings first adopted fully automatic elevators. There was a similar reaction made by many people back then akin to the reaction people have when talking about automated vehicles today.  Many felt uncomfortable to be in an elevator that was automatic, these people longed for an operator in the elevator to make sure they could get to their floor safely because they simply did not trust the new technology. Current-day generations unsurprisingly take this technology for granted because they never experienced a time where there was not automated elevators. Is this starting to sound familiar? It should. Just how the idea of automated vehicles driving around and having free reign on the road is a scary thought for so many people today, so too was the idea of elevators working on their own in the past. So then, will automated vehicles one day be as simple and regular as automatic elevators? We’ve all seen videos online like this one involving young children who display a familiarity and enjoyment in using an iPad, so in that same vein will these self-driving cars become the new iPad or automated elevator? A tool that newer generations will accept much more easily than those who live through the transition? I’d like to think that as the technology advances, and the world gets more and more exposure to autonomous vehicles it will become a banal normality to no longer drive your vehicles any longer. The common person will have to become comfortable with the fact that their cars were pre-programmed and they do not have complete control in decision making.

Perhaps contrasting the final point regarding a loss of control in the previous paragraph, another angle to self-driving cars is to think about the amount of companies that will grow and prosper making their living off of the rise of this technology. Not only that, we must also try to observe and understand the amount of change that will be brought on not only on a personal level by automated vehicles but also for city planning and other logistical endeavors. This article does an extraordinary job looking at the different ways in different approaches to automated vehicles will have different results for society as a whole. For example, Uber has already taken over Pittsburgh with their autonomous fleet as we’ve discussed previously. However, this is just one of the three options currently being talked about for the future of autonomous vehicles. The first option is private ownership, which is perhaps the most well known category. We see this already with the current state of our transportation system using buses, trains, etc. to move people from point A to point B that are all owned by companies. Another option is buying into companies and “renting” cars from Tesla, Google, or Ford. This means that after paying a fee to a specific company whenever a car is needed you would simply call for it and they would send a car. The last option is a bit similar to the last but for key reasons is the favorite of urban planners because it will eliminate the most cars: a shared fleets of cars. Acting like Uber Pools or a taxi, a car would pick up a group of people all heading to the same location and would drop them off and then when a car is needed again, another one can just be called. The key difference here is that these pools would be owned by the government much like buses or trains and not require fees be paid to a company for the service.

Now there is currently a three-era breakdown of the installation of fully functioning autonomous vehicles that starts at 2015, goes to 2020, and finally stops at 2050. The first era as most of you may already know has already started: automated vehicles are already a reality and being tested in fleets across the world like in Singapore and Pittsburgh. Couple this with the fact that there are now emerging models and technologies that are being created and released and that testing has been ramped up especially in a state like California and you get a formula that is set for mass amounts of innovation in a very quick time span. Tesla is one of the best examples of this with their release of Autopilot 2.0. The next era is set to begin in 2020 and end in 2030: this era will be marked by the insurance companies no longer covering an individual driver, but rather now covering companies due in large part to private ownership becoming a thing of the past, causing companies to own the cars and rent out their vehicles to citizens in the country. Along those lines, since the driver will have no longer have liability of any decision that the car makes the insurance must also insure that the technologies controlling the vehicles is for lack of a better word, bulletproof. Finally, the years from 2030 to 2050 are forecasted to be when automated vehicles are predicted to become the primary means of transportation. The most important milestone reached in this era will be that vehicle crashes will fall 90%, saving billions of dollars per year and making the roads a safer place for all drivers. This will then lead to the redesigning of major cities and towns as we know; as an example, with cars constantly coming and going parking spots can be replaced or removed. Today, cars are parked 95% of the day which will be dramatically decreased to a mere 40-50%. The extra space can lead to further innovation of new technology in now available space. Right now it may be hard to fathom of a world where the drivers will no longer be driving but rather passengers in their own car however once the world has become fully comfortable with this idea, look out for the rapid of advancements of this great technology. The world of tomorrow will undoubtedly become more efficient and roads will look dramatically different than they do present day.

Yielding to the Wealth Gap

As our society draws closer and closer to a world with autonomous vehicles there is always a bit of uncertainty as to what the future will hold. What changes will be made to the roads of our world? How will these vehicles function? etc. But there is one question that perhaps isn’t receiving the amount of attention it should be: who will be driving these cars? Certainly we can expect that car manufacturers will not be standing on street corners handing out keys to their newest and fanciest autonomous cars with no concern for profits or the like. So we must now ask ourselves this: will the people who absolutely need this technology be the ones to get it? Before we go on please take a a few minutes and watch the video below to understand just what I mean when I say that.

As we see in the video these cars can undoubtedly have an amazing effect on the lives of people from all walks of life. From erasing the gap of mobility and ease of travel between drivers today and those who are disabled, to significantly reducing the amount of crashes and accidents as we’ve covered previously it is clear that automated vehicles will have an immeasurable impact on the quality of life of everybody in the United States and beyond. Knowing that, it would seem only logical that the government or car manufacturers at the very least take steps to ensure this technology gets in the hands of everyone – one safer driver means a whole safer road in general after all. But yet this is the area of automated vehicles that gets a little complicated because as we all know, technology is expensive – even technology that has been around already for years (looking at you, new Macbook Pro). So what then do we do? Do we have an obligation as a society to ensure that everyone who needs an automated vehicle gets one? And if so how do we finance such an endeavor?

Looking just at the data, in 2014 the average American spent around $30,000 on a new car. For reference, the Toyota Prius in the video above starts at a price of $20,806 and while on the surface it would seem that the average American would be able to afford this vehicle this is before any of the new automation technology is taken into account. Looking at the technology we’ll start with the addition of Velodyne LIDAR system which is the main operating system for the vehicle; add to that the visual and radar sensors for the vehicle and the cost for that alone comes to about $10,000. Moving on from that there is also the GPS array which is needed to keep the automated vehicles running that clocks in at a cool $200,000. So just looking at this from an extremely shallow perspective, the Toyota Prius that was featured in the above video costs nearly $320,000; more expensive than a Ferrari 599. It should go without saying that as of right now this does not bode well for the future of affordable self-driving cars as with the high costs of the new technologies your average American will not be able to afford one of these vehicles.

However, all is not lost as with advancing technology also comes cheaper alternatives to the technology in an attempt to stay competitive.  Today, instead of Toyota rolling out a new fully automated Prius and adding nearly $300,000 to the price tag they are instead opting to add only around $7,000-$10,000 to price tag in exchange for having the new Prius instead be a semi-autonomous vehicle. With these minor adjustments and technology prices decreasing eventually over time it is predicted that by 2035 automating a vehicle will only increase the price of the car by $3,000. Currently and perhaps unsurprisingly it appears that automotive companies have a bit of an advantage with rolling out these cars quickly as industry giant Google continues to hold that they still are operating under the model that their fully automated vehicles will not available for sale until the five to ten years. Looking at the landscape of autonomous vehicles today it is not an unreasonable expectation that most of the country will have the opportunity to buy a fully autonomous vehicle soon. However we must be mindful that having the opportunity and being able to are two very different things, and that even as prices drop in some areas there will still be people left behind as a result of lacking the money to advance into the automated age with everyone else. Today I leave you with a video posted below; a recent publicity stunt from Budweiser involving an automated beer truck driving around on a highway – let it serve to remind us that for as amazing and cool as this technology is lets not break out the beer and celebrate before the people who really need it, the Steve Mahan’s of the world, get it.

Automated Vehicles: Questionable Ethics

Ethics is hardly, if ever, the starting point of a conversation about automated vehicles. The truth is that in the world of automated vehicles ethics can be something that is often overlooked or forgotten about entirely, seemingly taking a backseat in discussion. In this blog post however I hope to rectify this immediately because after reading an article last week, ethics in autonomous vehicles have been the only topics that I have been researching. Pulling no punches, the article in question looks at Mercedes-Benz  as the first car manufacturer to release their software information and brings up a rather blunt initial question: in the event of a unavoidable crash would you want your new self-driving vehicle to prioritize your own life as the owner of the vehicle or the lives of several innocent children? In so many words the scenario is broached like this: suppose you were in an autonomous vehicle and a car was on the wrong side of the road. The software driving the car now has a decision to make: it can either swerve left into oncoming traffic, putting you in immediate danger or, option two, swerve the car to the right onto the sidewalk and potentially harm a group of children walking home from school. The decision is not an easy one, nor is it one to be made lightly.

Regardless, as per the article Mercedes has now given their answer to this question: they will swerve to the right and run over the group the children on their way home from school. Now to some people this may be the clear decision to make in this situation but some may still be wondering exactly why Mercedes has gone in this direction when programming the software for their autonomous vehicles. To help understand we will take a look at a moral issue very closely associated with this dilemma, the “Trolley Problem. The Trolley Problem is a thought experiment developed by Philippa Foot in 1967 which involved a trolley coming down a road where men were currently working. If the trolley stays straight on its current path, it will kill five people on the tracks, however if you switch a lever, the trolley will instead go down a different path only killing one person. The main question raised is obvious: what is the right decision to make in this situation? This has been the moral dilemma as we’ve understood it for many decades, however now car manufacturers have to address this issue with a whole new layer of complexity added to the equation. Below this paragraph I’ve included a video to help explain the idea of this problem before we go any farther to help clarify any questions you may have. 

As I’m sure most of you could probably have concluded by now, in the real world of self-driving cars this problem is more than just an ethical dilemma, it’s a PR bomb waiting to go off. Just think about the car companies that will soon be designing and programming the new autonomous vehicles of the future and which car you would rather drive, the one that prioritized your own personal safety at all times or the one that prioritized others before you; I know which I’d rather drive. The fact of the matter is that if Mercedes-Benz (or any other automotive company for that matter) prides themselves on customer satisfaction it would make absolutely no sense to have cars programmed not to prioritize customer safety. Essentially, (under the assumption that there would still be automotive accidents) Mercedes-Benz would effectively be designing “death cars” in the eyes of their customers, not a very good business strategy at all. Looking at another article similar questions are brought up revolving around the difference between a car and a motorcycle: is it better to hit a car or a motorcycle in this situation? The unfortunate fact is that all this is a catch 22 situation, not helped by the fact that right now there is no law in place to lead the car manufacturers and developers in the legally “right” direction. Therefore, there is no question that it makes the most sense that the manufacturers are taking the Mercedes-Benz approach and developing with the customer in mind. What are your thoughts on this situation? Should automotive companies be taking this kind of approach in the future or is there perhaps a better solution?

Automated Vehicles: Here & Now

Science fiction has always been an extremely popular genre whether in movies, in television, or in novels. Indeed, it is a fascination fueled by the innate imagination inside of every human being – the ability to dream endlessly about what the future may hold. However, as many sci-fi fans may tell you such fantasies usually stay as just that, a fantasy, as is the case of lightsabers from Star Wars, or The Starship Enterprise from Star Trek. But today the world is bearing witness to perhaps one of the greatest exceptions to this rule: automated vehicles. Posted below this paragraph is a video that details a brief history of the idea of automated vehicles for the first few minutes of the video’s run time. In the video the narrator explains not only have automated vehicles been around in some form for longer than most people would suspect, but also that the idea originated in a 1929 sci-fi magazine. Ladies and gentlemen, this is the future and we get to be a part of it here and now.

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But now that we’ve succeed in merging one of the coolest ideas of science fiction into the real world, just what exactly are we doing with autonomous vehicles current day? Today’s post aims to take a shorter term approach and dig deep into what this technology is doing for us not in the future, but current day.

To start off, Tesla has been on the forefront of innovation since their insertion into the auto industry in 2003. Currently they are best known for their semi-automatic vehicles on the road that are impressive not only from a technological standpoint, but also for the fact that they are electric. The main driving force of Tesla is the CEO, Elon Musk, who can be frequently seen on social media and in various other meetings and talks supporting the progression of autonomous vehicles. The company constantly updates the software that goes into their cars, and are now soon to release their first autopilot software to be installed into their newer model cars. Musk was quoted in August as saying “What we’ve got will blow people’s minds, it blows my mind …it’ll come sooner than people think.” In connection with this, Bosch, the leading distributor of car parts has just released their first self driving vehicle. This is a huge step for Tesla because the software being used in the Bosch’s vehicle will be the same software in Tesla’s Autopilot 2.0. To help understand just how big a leap this is, a level system is used by the National Highway Traffic Safety Administration (NHTSA) when describing how autonomous certain vehicles are. Currently Tesla’s cars are at a level 2 autonomy, however these cars coming from Bosch rank higher at level 4 autonomy (fully functioning autonomous vehicle) thanks to the autopilot program that is soon to be released. The reason Tesla is now using the Bosch technology is because of an accident that occurred with one of their semi-autonomous in Florida because of a “technical failure” when the vehicle’s sensor could not recognize a tractor trailer due to it blending in with the glare of the sun. Due to the crash, Moblieye, an auto tech supplier left the company, so Tesla turned to Bosch. Despite this setback the world is still eagerly awaiting the next big piece of news to come from Tesla in the future.

The next company to look at is Ford, a longstanding and popular motor company that created the “first affordable automobile” the Model-T. However, that small 1927 revolution is nothing compared to what Ford is planning on releasing in 2021 as heard from CEO Mark Fields when he made the announcement on August 16th that Ford will release a level 4 autonomous vehicle. As the level system from the NHTSA above tells us, this is final level of autonomy which requires absolutely no human interaction. Interestingly, Ford also announced that this first new vehicle would not have steering wheels or control pads. Further, in 2021 Ford will not be selling the cars to the public but rather using the vehicles as a shuttle for their own employees. But perhaps the most interesting aspect of this announcement from Ford is that they are skipping levels of autonomy and opting instead to release a vehicle which is fully autonomous. While some companies like Tesla, Google, and Uber are taking a more comprehensive approach with street testing and semi-autonomous vehicles first to move the software along this could all change extremely quick because Ford is opting for a more immediate route. Look for Ford and other U.S. auto companies to continue innovation and progress even further.

Finally, we step away from car manufacturers and take a look at the transport company, Uber. When Uber was founded in 2009 it instantaneously become a disruptive force in the automotive industry. Taxi drivers in all cities around the country scrambled to try to keep up with the massive changes that Uber was causing. Fast forward seven years and now Uber has upped the ante with a strong push in the world of autonomous innovation. Two months ago Uber rolled out autonomous vehicles on the streets of Pittsburgh. As of right now the cars unfortunately have a limited number of streets they can operate on due to programming constraints however this technology has gotten to the point where Uber drivers were only operating the vehicle close to 30% of the time on any given ride. This decision made many people wonder why Uber chose Pittsburgh for the initial testing of their automated vehicles as they are a California company and California is known as a state leading the way with laws and regulations allowing autonomous vehicles to hit the roads.  The main reason for the Pittsburgh is surprisingly simple however, Carniege Mellon University, which is home to most of the technology that is driving Uber’s advancements. Additionally, the company felt it was important to have engineers close to the vehicles just in case anything happened. Thus far there have been two conflicting reports about two incidents involving accidents occurring with the new autonomous vehicles. However, both of the accidents were human error, one being the driver went down a one-way street and the other was an Uber vehicle that got rear ended by another vehicle. The critics are trying hard to restrct Uber because right now they are the closest company to moving this technology to a national level. 

According to Reuters, various companies are just starting onto the onset of a competition between each other in the autonomous vehicle world. Indeed in terms of unlikely bedfellows , not only does Reuters have Uber slated to be Apple’s competition in the autonomous vehicle industry but they are also reporting that Google and Ford are rumored to partner in 2016 for automotive innovation. It would seem that many companies such as Google and Ford or Apple and Tesla are teaming up because while the tech and media companies have the advantage for Research and Development capabilities as well as existing computing technologies, the auto makers possess the industry expertise and facilities necessary to make the innovation a reality.  Yet, Uber is arguably well placed to be the leader in this regard as they well capitalized and Uber has already brought many changes in the taxi-driver on demand sector.  Uber is no longer simply viewed as a ridesharing app, current day it has now reached a market whereby using a smartphone to match demand and supply for automobiles efficiently and cheaper. Between Uber and Apple it would seem that Apple will need to utilize their technological capability to enter that sector in order to compete with Uber.

Meanwhile current day, Google has created a self-driving car with two routing programs, a “long term router” that acts much like the GPS device on a normal car, and another, short-term router that makes decisions on when to speed up, slow down, turn and execute other maneuvers. The self-driving car is poised to have a positive impact because there will be less accidents on the road, and as such less fatalities. At the moment, it would seem that autonomous vehicles are right around the corner waiting for the light to turn green so they can be allowed onto the streets of the United States.

No Automated Answers

Automated vehicles, like most up and coming technologies, are extremely exciting to some people but unsurprisingly terrifying to others. There exist a great many people who cannot wait to see increases in productivity or inefficiency the likes of which we’ve never seen before that is currently being heralded by the coming of automated vehicles. As we will cover in a future post, automated vehicles will make almost everyone’s lives easier and more convenient by decreasing the amount of time and effort spent driving cars. But why exactly is this being mentioned in a post about the downsides of automated vehicles? What could make people be reprehensible about having automated vehicles? You’ve probably already figured out the answer on your own: job loss. Just from a cursory glance at statistics from 2014 provided by the United States Bureau of Labor Statistics we are able to see that in the United States alone transportation makes up 4,640,300 jobs, all of which stand to become redundant when the revolution that is automation hits the transportation industry. Unfortunately, those four million people are not the only ones who should be worried because the way this technological change is set to change our world there will be no one who is left unaffected. Before going anything farther into this topic I’ve posted an extremely well-made video below on the topic of automation which may help to convey the extent to which automation will touch not just vehicles but all facets of our lives.

Coming away from that video I’m reminded very much of poem by famous English poet John Donne which has a verse that reads thusly,

No man is an island,

Entire of itself,

Every man is a piece of the continent,

A part of the main.

If a clod be washed away by the sea,

Europe is the less.”

Just keeping the conversation focused on the transportation industry, the loss of over four million jobs in the United States will be felt not only be those unemployed people but also economically nationwide. However, problems will persist farther than just on an economic scale when those four million jobs are made redundant. The United States will be left with a dearth of jobs for those four million displaced transportation employees as most will not have the education nor the skill set needed to obtain a job in skilled labor industries. Therefore with four million people out of a job and lacking the prerequisites to get a job that has not been automated the United States, as well as the rest of the world, will be left in a very precarious situation with no easy solution for combating unemployment.

Following that, for all the good that the future of autonomous vehicles holds there are still other issues that arise when trying to successfully implement them. The first and perhaps the biggest obstacle for getting an autonomous vehicle on the road would be the rapid pace that both driving laws and the legal system in the United States and around the world would need to change. Before any automated vehicles can be made street legal various laws would have to dramatically reworked. Just as an example, when doing research for this blog post I attempted to find posts or videos on the internet which would provide a useful definition of what being street legal is with regards to automated vehicles. Of the multiple articles that I found, none of them have any useful information regarding self-driving cars. The only article I was able to find about the issue would only go as far as to say that self-driving cars operate in a, “kind of legal gray zone.” Regardless, steps are however being made in the right direction. The first state to take one such step has been California, which is allowing testing on the streets of it’s state once certain conditions are met. The most important part of all of this for both companies and the government is the cost of the law with each automated vehicle that is being tested without the aid of a human behind the wheel needing to be insured for five million dollars. While this will make it extremely costly for companies to test their cars on California streets the unfortunate reality is that California is the only state where humanless tests are allowed. Delving deeper into the law and logistics of automated vehicles, the next part of the new California laws are 112 pages and a four part policy that must be met in order for any car to even hit the streets. The U.S. Department of Transportation has set a clear 15- point safety assessment clearance policy that each car must pass before they are allowed to be driven which could make the process rather repetitive and tedious.  The obvious downside here is that because of the increase in costs and the high levels of restrictions levied upon automated technology by the law the technology is unable to grow at the fastest possible rate.

On a completely different front, with an increase in reliance on technology and software to operate our vehicles people will start viewing these less as vehicles and more as computers. Unfortunately, just like with computers people will look to hack into our cars, which could be detrimental for the safety of the roads. The world of cyber security is still years away from catching up with the ever advancing technology we know as autonomous vehicles. We are verging on a world where there will be thousands of networks operating to make self-driving cars run everyday, and moreover, a world where automakers will have to step up their security in order to ensure the safety of all drivers. Think of a world where a terrorist attack is no longer the threat of a nuclear bomb, but the threat of them gaining access to our driving networks and controlling our streets and highways. The future is a place where we cannot afford to have no internet connection as that will make it impossible for autonomous vehicles to communicate with other autonomous vehicles on the road. Right now the automated vehicles are relying on software like Google Maps to operate their vehicles which translates to vehicles of the future having a dependency on being connected to wifi at all times which would require the addition of wireless networks on all U.S. roadways. Not only that, the installation of wifi is just the first step as for the technologies to truly work. GPS and specific software for the vehicles themselves will need to be updated constantly so that the cars can function properly and avoid accidents. Not only would all this be costly but also it would require wireless companies to come together in order to be able to string up connection needed for the cars to run.  So yes, you could say that automated vehicles have more than a few areas in which they are still for lack of a better word, lacking.