Is Automation Taking Jobs? The Truth About Automation

With self-driving cars and warehouse robots on the rise, many workers across the nation are pondering. Is automation taking jobs away?


Automation by Industry

Automation can take the form of physical tasks assisted by robotics or data management tasks assisted by computers. Either way, the effects of automation have been substantial in scale over time.

For businesses, Automation and Artificial Intelligence are a tremendous source of leverage for scaling up operations. But as consumers, automation means we have access to more resources for cheaper prices.

As employees, however, automation often means taking away redundant and labor-intensive jobs. Robots and computers can perform those duties cheaper and faster.

Let’s check out the top industries that are undergoing disruptive forces of automation:

Online Shopping

Amazon now has a database of over 12 million products. During the low season, they sell surplus computational power to other businesses via AWS (Amazon Web Services).

Warehouse worker

Automated Warehouses

The Amazon empire uses a unique supply chain that leverages technology to predict the demand for a product and efficiently manages inventory count.

Their FBA (Fulfilled by Amazon) system allows manufacturers to ship their products to Amazon’s fulfillment centers. After that, a fulfillment center completely manages the shipping process as well as communicating inventory demand back to manufacturers.

With over 200,000 robotic vehicles in Amazon warehouses, the megacorporation has managed to crush competitors in speed and cost-efficiency. Firstly, this allows Amazon to provide 2-day shipping for many of their top-selling products. And secondly, it allows manufacturers to focus on building great products.

Physical products and services still require some human interaction to fulfill a sale. And today’s digital services can run entirely on their own through software. In the end, software only requires maintenance when bugs are found in features or systems become overloaded.

eBay takes the throne as the largest marketplace for second-hand items. Millions of people around the world sell have sold their old stuff with the help of PayPal’s trustworthy finance platform. Above all, no physical middle-man is required.

Agriculture

Agricultural workers and "Vegebot" harvesting lettuce
“Vegebot” harvesting lettuce

With the US approaching a population of 330 million people, the demand for agricultural goods continues to grow. The demand for food is at a steep enough rate that automation is deemed necessary in this sector.

Key activities for growing crops include weeding, harvesting, and spraying pesticides. All of which have historically required the manual labor of farmers.

But not anymore.

Internet of Things

Sure, autonomous harvesting robots have become increasingly common. But the IoT (Internet of Things) has taken a stronghold over agricultural monitoring, too.

Farmers can now digitally view the water levels, soil composition, temperature, and other data points for their entire farm. Sprinklers, fertilization, and alerts can be triggered automatically by different environmental conditions by leveraging Artificial Intelligence.

The increased awareness and precision provided by these technologies have cut down annual agricultural costs by 80% in some cases.

Is the increased efficiency and automation of farming taking away jobs? In short, yes. Farming has become more consolidated, with less, more efficient farming facilities.


Transportation

2020 Tesla Model X
2020 Tesla Model X

The Tesla “Gigafactory” is a state-of-the-art car manufacturing plant built from the ground up with engineering efficiency in mind. Tesla aims at a target output of 500,000 cars manufactured per year by the end of 2020.

Tesla’s mission is to “accelerate the world’s transition to sustainable energy”. As such, by supplying electric motors and battery packs for Tesla vehicles, the Gigafactory is part of an extremely efficient manufacturing ecosystem.

Self-Driving Cars

Google's prototype self-driving car leveraging Artificial Intelligence
Google’s prototype self-driving car

With self-driving cars now within the focal point of tech, Uber and major auto manufacturers are delegating more resources towards Machine Learning and Artificial Intelligence research.

Firstly, cameras and Lidar sensors work together with Computer Vision software to allow self-driving cars to recognize objects, even in hazy conditions. Street lights, humans, and other relevant objects on the road can be seen and recognized by the algorithms.

Additionally, Tesla has been able to crowd-source data from their 900,000+ vehicles currently on the road via internet connectivity. This allows researchers to train neural networks on how to respond to the environment. The results have gotten better and better over time.

As a result, Elon Musk has rolled out “Full Self Driving” for select Tesla vehicle owners. Only time will tell how effective and safe this technology is, but there are already astonishing stories being told about it. You can find plenty of YouTube videos showing drivers being taken long distances without even needing to touch the steering wheel.

While the state of self-driving is in its infancy, it is certainly a technology that should be watched closely. If fully adopted at a large scale, we can expect to see automation taking away jobs from millions of drivers.


Customer Service

Woman talking to customer support on phone

If you’ve ever called a customer service hotline, then you know that it’s rare to speak directly to a human.

Automated Phone Systems

An automated phone system will give you a list of options to manage your services, find out business hours, etc. You can usually speak to a human if you dial the magic number (often zero). When it comes to customer support, human interaction is more of a last resort than a first response.

Chatbots

Nowadays we don’t just communicate over voice, but also over text messaging. Many websites have a chat box where you can exchange typed messages with customer support representatives.

But oftentimes, you’re not actualy chatting with a human.

Chatbots usually deliver a limited range of responses. However, chatbots can still analyze messages for certain words and use Neural Linguistic Processing to guess the type of request.

Once your request is understood by the chatbot, it can take action without human assistance. Chatbots are like humans, but much faster.


Finance

Cryptocurrency bitcoin market illustration

In the finance sector, direct deposits and mobile banking have mostly eliminated the need for regular trips to the bank. For instance, some digital banks operate purely through an online interface without any physical interaction required to open and manage an account. Artificial Intelligence is often used to verify the eligibility of applicants when opening a new account.

Stock market illustration

Pretty much all banks have gone digital and provide online services via mobile apps. It’s no secret that finances are highly managed by computers.

Stock Market

Quants are programmers that use Machine Learning and mathematical conditions to write programs that can respond to stock market trends. The software can execute trades at blistering speeds, before humans can even identify the fluctuations in the market.

Cryptocurrency

Cryptocurrencies like Bitcoin and Etherium have quickly risen in popularity due to the decentralized nature of the currency. There are no banks involved at all between cryptocurrency transfers. Instead, crypto relies on crowdsourcing the processing power of “miners”.

Miners are people around the world with computers that have a powerful GPU. A GPU (Graphics Processing Unit) is capable of performing the rigorous mathematical operations required to verify the integrity of transactions. Although the crypto craze of 2017 is far behind, Bitcoin is back on the rise. Companies like Microsoft have begun officially accepting Bitcoin payments in limited cases.

Credit Cards

Have you ever had your credit card locked due to “suspected fraudulent activity”? Well, it wasn’t a human that triggered the lockdown. It was an artificial intelligence model that had been trained from the data of historically fraudulent activity.

The fraud detection technology isn’t perfect. But many credit card owners can appreciate the extra layer of security provided by the technology. Leveraging the speed of computers to check millions of financial transactions per day saves investigators time. An insurmountable amount of time.

At the end of the day, one can hardly say that automation is taking away jobs in finance. The merging of finance with computational automation has created a plethora of new jobs.


Health Care

Doctor working on a computer

Computers have been used for decades to track the health history of patients around the world.

Insurance

Health insurance quotes are often estimated by software. Calculations can be made based on formulas to estimate the cost and risk of covering a patient. Obviously, age and pre-existing conditions are key factors in determining risk. But by using software that leverages Machine Learning, hundreds of additional data points can be used to more precisely tune the quote.

Predicting Cancer

The ability to detect diseases before they become malignant is a top priority in the medical sector. It can save millions of lives if automated by computers.

Therefore, classification is often used in this field of study. Classification is a common method of Machine Learning that takes into account the medical history of a large sample of patients. It uses that data to make future predictions about individual patients.

Computers can analyze hundreds of dimensions of data points for pattern recognition to detect patterns that go unnoticed to the human eye. Even factors like diet, hereditary disorders, and beyond can be taken into consideration to make predictions.

About 12% of women in the US prone to being diagnosed with invasive breast cancer at some point in their life. As a result, alignant cancer detection is at the forefront of Machine Learning and Artificial Intelligence research. Researchers have access to thousands of historical medical records that they provide to a Machine Learning model for analysis.

Challenges

Some experts are saying that the limitations of Machine Learning and Artificial Intelligence are still a hurdle in the way of progress. In order to extract good results from Machine Learning, researchers must use a very large set of unbiased data.

Data from hospitals is implicitly biased due to the varying socio-economic makeup of the patients. But also by different mammogram screening machinery and image formats. When biased data is used for Machine Learning, the predictive accuracy of the model is reduced.

Ultimately, these prediction algorithms are just that- nothing more than predictions. While sometimes very accurate, the results of these algorithms should be treated with scrutiny.

In the field of medicine, automation is not taking jobs away at all. If anything, the cross-disciplinary fusion of medicine and computers is creating new jobs.


Trucking & Logistics

Einride self-driving truck
Einride self-driving truck

Goods have to be shipped from factories in order to be made available for sale to consumers. With over 70% of US freight being moved by truck and nearly 8 million trucking employees in total, the logistics sector marks one of the most critical parts of the US economy.

Self-Driving Trucks

Swedish companies Volvo and Einride are pushing the trucking industry forward with self-driving trucks. Volvo has taken incremental steps toward autonomy by equipping its flagship human-driven trucks with self-driving features.

But Swedish competitor Einride has gone all-in for full AI-driven autonomous driving capabilities by crafting a truck with no cabin and no windows. It seems to have come straight out of a futuristic sci-fi film.

If self-driving trucks were to take stage, it could be economically devastating for truck drivers. We can expect the effect of automation taking jobs from millions of truck drivers across the country, if not the world.


How To Survive The Age of Automation

Man thinking

As we can see, automation has already caused a heavy amount of disruption across various industries. And there’s still more to come. But does this mean that you will lose your job?

Once a technology is deemed to be safer, cheaper, and faster than humans, there will be little need for human labor. Outside of supervising and maintenance, robots and computers can perform many redundant business operations.

One industry that seems to never go out of fashion is computer programming. Software and hardware need to be designed, built, and maintained by computer programmers. Coding is an area full to the brim of opportunities and it’s not as hard as people think.

If you embrace any STEM field (Science, Technology, Engineering, Math), then it is unlikely that your job will ever be in jeopardy. Ironically, your job will likely lend a helping hand in automating away the more labor-intensive jobs. But if you aren’t interested in a STEM career, there is nothing to fear!

The Truth About Automation

The truth is that automation isn’t just taking jobs away. It’s also creating new types of jobs- and not just in tech.

Automation allows people to focus on higher-level thinking. Instead of needing to spend time on redundant activities, we can focus on designing and architecting new things. Creativity is at an all-time high as a result.

There are so many skills that only humans can perform well. Writing, making music, film making, legal consulting, teaching, fitness coaching, and many more. Even if technology could automate those areas, it would never match up to the creativity of the human mind.

What do you think about automation and artificial intelligence? Do you embrace the benefits of these technological advancements? Or does it seem like technology is on the brink of going too far?

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