Automation

Ranked: The Autonomous Vehicle Readiness of 20 Countries

Published

4 years ago

August 27, 2019

Katie Jones

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

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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Automation

Which Jobs Will Be Most Impacted by ChatGPT?

OpenAI, the creators of ChatGPT, have authored a research paper that tries to predict the impact of AI on the job market.

Creator Program

Published

4 weeks ago

April 30, 2023

Pallavi Rao

Jobs Most Impacted by ChatGPT and Similar AI Models

On November 30, 2022, OpenAI heralded a new era of artificial intelligence (AI) by introducing ChatGPT to the world.

The AI chatbot stunned users with its human-like and thorough responses. ChatGPT could comprehend and answer a variety of different questions, make suggestions, research and write essays and briefs, and even tell jokes (amongst other tasks).

Many of these skills are used by workers in their jobs across the world, which begs the question: which jobs will be transformed, or even replaced, by generative AI in the coming future?

This infographic from Harrison Schell visualizes the March 2023 findings of OpenAI on the potential labor market impact of large language models (LLMs) and various applications of generative AI, including ChatGPT.

Methodology

The OpenAI working paper specifically examined the U.S. industries and jobs most “exposed” to large language models like GPT, which the chatbot ChatGPT operates on.

Key to the paper is the definition of what “exposed” actually means:

“A proxy for potential economic impact without distinguishing between labor-augmenting or labor-displacing effects.” – OpenAI

Thus, the results include both jobs where humans could possibly use AI to optimize their work, along with jobs that could potentially be automated altogether.

OpenAI found that 80% of the American workforce belonged to an occupation where at least 10% of their tasks can be done (or aided) by AI. One-fifth of the workforce belonged to an occupation where 50% of work tasks would be impacted by artificial intelligence.

The Jobs Most and Least at Risk of AI Disruption

Here is a list of jobs highlighted in the paper as likely to see (or already seeing) AI disruption, where AI can reduce the time to do tasks associated with the occupation by at least 50%.

Analysis was provided by a variety of human-made models as well as ChatGPT-4 models, with results from both showing below:

Jobs	Categorized By	AI Exposure
Accountants	AI	100%
Admin and legal assistants	AI	100%
Climate change policy analysts	AI	100%
Reporters & journalists	AI	100%
Mathematicians	Human & AI	100%
Tax preparers	Human	100%
Financial analysts	Human	100%
Writers & authors	Human	100%
Web designers	Human	100%
Blockchain engineers	AI	97.1%
Court reporters	AI	96.4%
Proofreaders	AI	95.5%
Correspondence clerks	AI	95.2%
Survey researchers	Human	84.0%
Interpreters/translators	Human	82.4%
PR specialists	Human	80.6%
Animal scientists	Human	77.8%

Editor’s note: The paper only highlights some jobs impacted. One AI model found a list of 84 additional jobs that were “fully exposed”, but not all were listed. One human model found 15 additional “fully exposed” jobs that were not listed.

Generally, jobs that require repetitive tasks, some level of data analysis, and routine decision-making were found to face the highest risk of exposure.

Perhaps unsurprisingly, “information processing industries” that involve writing, calculating, and high-level analysis have a higher exposure to LLM-based artificial intelligence. However, science and critical-thinking jobs within those industries negatively correlate with AI exposure.

On the flipside, not every job is likely to be affected. Here’s a list of jobs that are likely least exposed to large language model AI disruption.

Jobs Least Exposed to AI
Athletes	Short-order cooks
Large equipment operators	Barbers/hair stylists
Glass installers & repairers	Dredge operators
Automotive mechanics	Power-line installers/repairers
Masons, carpenters, roofers	Oil field maintenance workers
Plumbers, painters, pipefitters	Servers, dishwashers, bartenders

Naturally, hands-on industries like manufacturing, mining, and agriculture were more protected, but still include information processing roles at risk.

Likewise, the in-person service industry is also expected to see minimal impact from these kinds of AI models. But, patterns are beginning to emerge for job-seekers and industries that may have to contend with artificial intelligence soon.

Artificial Intelligence Impacts on Different Levels of Jobs

OpenAI analyzed correlations between AI exposure in the labor market against a job’s requisite education level, wages, and job-training.

The paper found that jobs with higher wages have a higher exposure to LLM-based AI (though there were numerous low-wage jobs with high exposure as well).

Job Parameter	AI Exposure Correlation
Wages	Direct
Education	Direct
Training	Inverse

Professionals with higher education degrees also appeared to be more greatly exposed to AI impact, compared to those without.

However, occupations with a greater level of on-the-job training had the least amount of work tasks exposed, compared to those jobs with little-to-no training.

Will AI’s Impact on the Job Market Be Good or Bad?

The potential impact of ChatGPT and similar AI-driven models on individual job titles depends on several factors, including the nature of the job, the level of automation that is possible, and the exact tasks required.

However, while certain repetitive and predictable tasks can be automated, others that require intangibles like creative input, understanding cultural nuance, reading social cues, or executing good judgement cannot be fully hands-off yet.

And keep in mind that AI exposure isn’t limited to job replacement. Job transformation, with workers utilizing the AI to speed up or improve tasks output, is extremely likely in many of these scenarios. Already, there are employment ads for “AI Whisperers” who can effectively optimize automated responses from generalist AI.

As the AI arms race moves forward at a rapid pace rarely seen before in the history of technology, it likely won’t take long for us to see the full impact of ChatGPT and other LLMs on both jobs and the economy.