Automation is coming to the workplace.
Millions of jobs will be destroyed, but many jobs will also be simultaneously created in the process as well.
For those in the workforce – or for those just joining it for the first time – the big question is: what skills are needed to navigate this monumental shift in the economy? How will humans create value in an increasingly automated world?
The Human Touch
Today’s infographic comes to us from Guthrie Jensen, and it summarizes the skills needed in 2020 and beyond to take advantage of the shifting landscape of work.
In short, for those looking to future proof their careers, building competencies in areas that machines will be unlikely to tackle effectively (i.e. complex problem solving, creativity) is likely the best recipe for success.
It can be daunting to think about automation’s role in the future – but if you’re a bookkeeper, legal secretary, insurance underwriter, credit analyst, or any other person in a job with high automation potential, it would be prudent to be thinking long and hard about what you can offer beyond your existing set of skills and competencies.
Here’s just a quick look at automation potential of select positions, according to a study by Oxford University:
|Position||Chance of Automation||Position||Chance of Automation|
|Insurance Underwriter||99%||Computer Systems Analyst||0.7%|
|Bookkeeping Clerk||98%||Registered Nurse||0.9%|
|Real Estate Broker||97%||Sales Manager||1.3%|
|Budget Analyst||94%||PR Manager||1.5%|
So how do we set ourselves up for future success in a world where even real estate brokers are likely to be automated?
It Starts With Soft Skills
There are many considerations for career success during a time of significant change.
However, there’s a good case that skills – especially soft skills – are the most important foundation to build upon. These include things like the ability to communicate and work well with others, solve problems, and think outside of the box, as well as other aspects of emotional intelligence.
Here are some skills that experts say should be prioritized:
1. Complex Problem Solving
It’s true that AI can solve problems that humans cannot – but it also goes the other way. When problem solving needs to span multiple industries or when problems are not fully defined, humans can work backwards to figure out a solution.
2. Critical Thinking
Machines are getting better at aspects of critical thinking, but humans are still able to to connect, interpret and imagine concepts in a world full of ambiguity and nuance. A lawyer can pinpoint the exact positioning to make a case for a client, or a marketer can figure out an overarching message that can resonate with consumers.
Creativity requires a degree of intuitive randomness that can not yet be imitated by AI. Why did the architect design the building a certain way, and why did the musician improvise by playing a chord out of key? It’s hard to explain why to a computer – it just feels right.
Other important soft skills to consider?
People management, coordinating with others, decision-making, negotiation, and serving others will all be important going forward as well.
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.
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:
- 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.
- 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.
- 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
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.
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.
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.
The Outlook for Automation and Manufacturing Jobs in Seven Charts
How will technologies such as automation and artificial intelligence end up impacting jobs and the workforce? Here are seven charts that tell the story.
The Outlook for Automation and Manufacturing in Seven Charts
View the high resolution version of today’s graphic by clicking here.
Over the last decade, the prospect of mass automation has seemingly shifted from a vague possibility to an inescapable reality.
While it’s still incredibly difficult to estimate the ultimate impact of automation and AI on the economy, the picture is starting to become a bit clearer as projections begin to converge.
Today’s infographic comes to us from Raconteur, and it highlights seven different charts that show us how automation is shaping the world – and in particular, the future outlook for manufacturing jobs.
The Age of Automation
The precise details are up to debate, but here are a few key areas that many experts agree on with respect to the coming age of automation:
Half of manufacturing hours worked today are spent on manual jobs.
- In an analysis of North American and European manufacturing jobs, it was found that roughly 48% of hours primarily relied on the use of manual or physical labor.
- By the year 2030, it’s estimated that only 35% of time will be spent on such routine work.
Automation’s impact will be felt by the mid-2020s.
- According to a recent report from PwC, the impact on OECD jobs will start to be felt in the mid-2020s.
- By 2025, for example, it’s projected that 10-15% of jobs in three sectors (manufacturing, transportation and storage, and wholesales and retail trade) will have high potential for automation.
- By 2035, the range of jobs with high automation potential will be closer to 35-50% for those sectors.
Industrial robot prices are decreasing.
- Industrial robot sales are sky high, mainly the result of falling industry costs.
- This trend is expected to continue, with the cost of robots falling by 65% between 2015 and 2025.
- With the cost of labor generally rising, this makes it more difficult to keep low-skilled jobs.
Technology simultaneously creates jobs, but how many?
- One bright spot is that automation and AI will also create jobs, likely in functions that are difficult for us to conceive of today.
- Historically, technology has created more jobs than it has destroyed.
- AI alone is expected to have an economic impact of $15.7 trillion by 2030.
Unfortunately, although experts agree that jobs will be created by these technologies, they disagree considerably on how many. This important discrepancy is likely the biggest x-factor in determining the ultimate impact that these technologies will have in the coming years, especially on the workforce.
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