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Automation

Visualizing the Jobs Lost to Automation

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Jobs Lost to Automation

Visualizing the Jobs Lost to Automation

The employment landscape of the future will look very different than it does today.

While we’ve charted the automation potential of U.S. jobs before, today’s graphic from Henrik Lindberg perhaps tells the story more succinctly.

In plain black and white, it shows the jobs that exist today in contrast to the jobs that are expected to disappear as a result of automation in the workplace. Though, technically speaking, it is applying the probabilities of the widely-cited Frey & Osborne (2013) study to U.S. jobs as of 2016 to give an expected value to each job title.

A Different Landscape

In the near-future, many of today’s most common jobs may be changed profoundly. People working as retail salespersons, cashiers, fast food counter workers, and truck drivers will likely see opportunities in those fields dry up as automation takes place.

At the same time, jobs such as those in teaching and nursing are expected to stand the test of time, as they require empathy, creativity, and a human touch not yet available through machines. In the coming decades, it’s possible that these could even be professions that employ the most people overall.

Casualties of the Fall?

In the vastly different employment landscape of the future, the worry is that low income workers will have fewer opportunities available to them as technology comes into play.

The good news? Historically this has not been true. As an example, nearly 500 years ago, Queen Elizabeth I had a similar fear when she denied a patent for an automated knitting machine. The thought was that the machine would kill jobs, though eventually factories and companies adopted similar technologies anyways. With the lower prices, higher demand for knitted goods, and more capital for investment, jobs for factory weavers actually quadrupled in the coming years.

As we’ve seen over time, while machines destroy jobs, they also often create new ones.

Composition of U.S. Job Market over the Last 150+ Years

Jobs as a Percent

The bad news? It is now clear that agricultural jobs of the early 20th century were replaced with the white collar jobs of today. However, it is much more difficult to forecast out how some of the jobs of the future will be created, especially for low income workers.

The knitting example above certainly applies in some situations – but in others, it’s hard to say what will happen. For example, with millions of unemployed long-haul truck drivers, what roles will these people be taking in the future job market?

Even with costs of transportation and logistics going down, increased demand, and more capital to invest, it seems that there’s going to be a lengthy period of time where many of these people will have trouble finding work.

Do they join the company to help manage the many more trucks that are self-driving? It’s unlikely, and that is the part of the optimism about automation and future jobs that is the hardest to reconcile.

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Automation

How Self-Driving Cars “See” the World

This video breaks down the complex technology allowing a new generation of self-driving cars to view the world around them.

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self driving car technology

How Self-Driving Cars “See” the World

Modern cars bear little resemblance to their early ancestors, but the basic action of steering a vehicle has always remained the same. Whether you’re behind the wheel of a Tesla or a vintage Model T, turning the wheel dictates the direction of movement. This simple premise, which places humans at the center of control, may be ripe for disruption as tech giants and car companies race toward a future that would render human-controlled vehicles obsolete.

How does this next generation of self-driving cars “see” the road? Today’s video from TED-Ed explains one of the mind-bending innovations making autonomous vehicles a reality.

Eye of the Laser

Safely getting a vehicle and its passengers from point A to B is no simple matter.

First, weather and time of day can create a wide variety of challenging situations, affecting things like visibility, braking distances, or speed. Next, other vehicles, bikes, and pedestrians are constantly moving through the transportation network, sometimes in unpredictable ways. To further complicate matters, the road network is rarely in optimum form. Road lines fade and construction can throw ambiguous detours into the mix.

Sensing and analyzing the world at a granular level is crucial in making self-driving cars a viable transportation option. To solve this problem, new generations of autonomous vehicles are using photonic integrated circuits, as well as light detection and ranging (LiDAR) to generate an extremely nuanced picture of the road ahead.

self driving car lidar technology

How self-driving cars see the world. (Source: Hesai)

LiDAR – which is related to RADAR – uses short laser pulses to sense the depth and shape of objects. Essentially, scattered bursts reflect off objects around the vehicle, painting a detailed 3D picture of its surroundings. LiDAR’s depth resolution is so accurate that it could eventually see details at the millimeter scale.

A Dissenting Opinion

While most companies in the autonomous vehicle space have fully embraced LiDAR, Tesla has a divergent point of view. The company employs a combination of GPS, cameras, and other sensors to help its cars visualize the world.

LiDAR is a fool’s errand. Anyone relying on LiDAR is doomed.

– Elon Musk

Society and Self-Driving Cars

While companies like Uber and Waymo determine the functional mechanics of self-driving cars, the rest of society is left to ponder how this new technology will affect employment, privacy, and personal autonomy.

In the U.S., more than 70% of goods are moved by truck, and over 80% of commuters take a private vehicle to work on any given day. Even partial automation of the nation’s transportation network will have wide-sweeping impacts on the economy.

As AI-powered cars and trucks hit the streets at scale, how cars see the road will be a detail most of us will overlook. The bigger question will be whether we are ready for a society where we’re no longer in the driver’s seat.

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Automation

Ranked: The Autonomous Vehicle Readiness of 20 Countries

This interactive visual shows the countries best prepared for the shift to autonomous vehicles, as well as the associated societal and economic impacts.

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For the past decade, manufacturers and governments all over the world have been preparing for the adoption of self-driving cars—with the promise of transformative economic development.

As autonomous vehicles become more of a looming certainty, what will be the wider impacts of this monumental transition?

Which Countries are Ready?

Today’s interactive visual from Aquinov Mathappan ranks countries on their preparedness to adopt self-driving cars, while also exploring the range of challenges they will face in achieving complete automation.

The Five Levels of Automation

The graphic above uses the Autonomous Vehicles Readiness Index, which details the five levels of automation. Level 0 vehicles place the responsibility for all menial tasks with the driver, including steering, braking, and acceleration. In contrast, level 5 vehicles demand nothing of the driver and can operate entirely without their presence.

Today, most cars sit between levels 1 and 3, typically with few or limited automated functions. There are some exceptions to the rule, such as certain Tesla models and Google’s Waymo. Both feature a full range of self-driving capabilities—enabling the car to steer, accelerate and brake on behalf of the driver.

The Journey to Personal Driving Freedom

There are three main challenges that come with achieving a fully-automated level 5 status:

  1. Data Storage
    Effectively storing data and translating it into actionable insights is difficult when 4TB of raw data is generated every day—the equivalent of the data generated by 3,000 internet users in 24 hours.
  2. Data Transportation
    Autonomous vehicles need to communicate with each other and transport data with the use of consistently high-speed internet, highlighting the need for large-scale adoption of 5G.
  3. Verifying Deep Neural Networks
    The safety of these vehicles will be dictated by their ability to distinguish between a vehicle and a person, but they currently rely on algorithms which are not yet fully understood.

Which Countries are Leading the Charge?

The 20 countries were selected for the report based on economic size, and their automation progress was ranked using four key metrics: technology and innovation, infrastructure, policy and legislation, and consumer acceptance.

The United States leads the way on technology and innovation, with 163 company headquarters, and more than 50% of cities currently preparing their streets for self-driving vehicles. The Netherlands and Singapore rank in the top three for infrastructure, legislation, and consumer acceptance. Singapore is currently testing a fleet of autonomous buses created by Volvo, which will join the existing public transit fleet in 2022.

India, Mexico, and Russia lag behind on all fronts—despite enthusiasm for self-driving cars, these countries require legislative changes and improvements in the existing quality of roads. Mexico also lacks industrial activity and clear regulations around autonomous vehicles, but close proximity to the U.S. has already garnered interest from companies like Intel for manufacturing autonomous vehicles south of the border.

How Autonomous Vehicles Impact the Economy

Once successfully adopted, autonomous vehicles will save the U.S. economy $1.3 trillion per year, which will come from a variety of sources including:

  • $563 billion: Reduction in accidents
  • $422 billion: Productivity gains
  • $158 billion: Decline in fuel costs
  • $138 billion: Fuel savings from congestion avoidance
  • $11 billion: Improved traffic flow and reduction of energy use
    • With the adoption of autonomous vehicles projected to reduce private car ownership in the U.S. to 43% by 2030, it’s disrupting many other industries in the process.

      • Insurance
        Transportation will be safer, potentially reducing the number of accidents over time. Insurance companies are already rolling out usage-based insurance policies (UBIs), which charge customers based on how many miles they drive and how safe their driving habits are.
      • Travel
        Long distance traveling in autonomous vehicles provides a painless alternative to train and air travel. The vehicles are designed for comfort, making it possible to sleep overnight easily—which could also impact the hotel industry significantly.
      • Real Estate
        An increase in effortless travel could lead to increased urban sprawl, as people prioritize the convenience of proximity to city centers less and less.
        • Defining the parameters for this emerging industry will present significant and unpredictable challenges. Once the initial barriers are eliminated and the technology matures, the world could see a new renaissance of mobility, and the disruption of dozens of other industries as a result.

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