What are the jobs that will disappear in the next 10 years and that threaten to end the industry?

Updated on : December 3, 2021 by Blake Fraser



What are the jobs that will disappear in the next 10 years and that threaten to end the industry?

With technology advancing at an ever faster rate, numerous jobs have become automated or obsolete. By 2030, the number is expected to increase even more.

  • Travel agent.
  • Cashier.
  • Fast food cook.
  • Postman.
  • Cashier.
  • Textile worker.
  • Press operator.
  • Sports Referee / Referee.
  • HR roles.
  • Merchants.

Mainly, software jobs are at higher risk as machine learning has made computers code themselves and create websites and applications smoothly and 100 times better than coders.

The work is out of date. I think the future of work is very different from what we see today, and I resigned from my job as a policy advisor in the Norwegian parliament to help ensure that it happens.

In the future, everyone in the world will be able to choose to work on what they do best, when they want, from where they want and receive the global value of their products instantly, with confidence. While you can collaborate with others to solve complex tasks, you can choose to live and work with your friends and family if you wish. There will be no mandatory office hours, no travel and much less m

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The work is out of date. I think the future of work is very different from what we see today, and I resigned from my job as a policy advisor in the Norwegian parliament to help ensure that it happens.

In the future, everyone in the world will be able to choose to work on what they do best, when they want, from where they want and receive the global value of their products instantly, with confidence. While you can collaborate with others to solve complex tasks, you can choose to live and work with your friends and family if you wish. Fortunately, there will be no mandatory office hours, no commuting, and far fewer middle managers.

The odd package of work is no longer needed, because new technology tools are better at solving the coordination and matching problems that we previously needed the company to do.

1. The Internet is eliminating the role of the physical border

Today, too many people have restricted access to migration and free movement, reducing the diffusion of knowledge and the productivity of billions of talented people.

In the future we will have a new global lens through which we will see the world, where all the peoples of the world will come together online to exchange ideas and services. In doing so, they transcend borders and join global citizenship in global communities already seen today on websites like Reddit, GitHub, and many others. There are no borders in virtual reality on the Internet.

2. Emerging allocation technologies and machine tools will improve our productivity

There is an underlying megatrend in many of the phenomena we observe today: the sharing economy, the autonomous economy, and crowdsourcing. We are building nodes in what could be described as hive-minded humanity.

The first phase of the Internet was a nervous system, where we could feel what was happening in other nodes: the connected people. In the second phase we are discovering that we can perform functions in the real world by cooperating, as multicellular biological organisms once discovered. The difference between a superorganism and a real organism is that we retain our individuality; there is no central unit that makes decisions on behalf of all of us, we are all free.

My hope is that so many such functions are created for the humanity of the hive mind, which will make work a more enjoyable experience for both those who work and those who need to get things done.

Today, businesses email us office tasks and we instantly assign them to previously screened freelancers based on their skills and availability. We give them access to tools that others have created to increase their productivity, and we give them easy ways to cooperate with each other online. Gradually these tools will move towards true AI, but from our point of view, they always seem to improve on humans, and rarely replace humans.

There is still a long way to go. But already today we see the flourishing of coworking spaces, the rise of the freelance economy, and more dedicated explorers quitting their jobs to become digital nomads. In 10 years, work and jobs will look quite different from today, in a very good way; in a more equitable, free and efficient way.

Technology and AI will replace the majority.

  • Cleaning jobs will be replaced by robots
  • Food workers. You will go and place your order on the screen and a robot will do it, put it on a conveyor belt or bring it to you. If you order it online, a drone may deliver it to you.
  • Truck drivers, bus drivers, and taxi drivers (these are some of the biggest workers in the world) could possibly be replaced by self-driving cars.
  • Retail unloaders (worked rear end and unloaded trucks) could easily be replaced by machines
  • Teachers? Teaching children how to learn through the computer screen will eliminate most of the needs of t
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Technology and AI will replace the majority.

  • Cleaning jobs will be replaced by robots
  • Food workers. You will go and place your order on the screen and a robot will do it, put it on a conveyor belt or bring it to you. If you order it online, a drone may deliver it to you.
  • Truck drivers, bus drivers, and taxi drivers (these are some of the biggest workers in the world) could possibly be replaced by self-driving cars.
  • Retail unloaders (worked rear end and unloaded trucks) could easily be replaced by machines
  • Teachers? Teaching children how to learn through the computer screen will eliminate most of the teacher's needs, and the “course agenda” will be set by federal government standards that prepare what they want children to learn.
  • Web Designers / Web Developers - Although our field is booming right now, this is likely to be gone in 100 years as software engineers are creating more AI-oriented tools and 'templates', so instead of "programming" or "designing", Certainly, everything is just point and click.
  • On a bright note: the only field that is currently being addressed right now: sex workers. The whole world is still fighting the issue of "human sex slaves" and "human sex trafficking" because it is a billion dollar industry. Where there is demand and money, there are government officials and law enforcement officials who turn their heads and pretend it doesn't exist. With the advent and introduction of conventional sex robots, this will eliminate the need for people so that mostly men demanding sex have a solution that does not involve humans having to provide sex at a disadvantage, and this will Reign for a long time before someone defends the rights of robots to choose whether they want to have sex or not.
  • Physician: Right now, the leading cause of death in all hospitals is human error. From doctor to nurse mistake: people are dying at an alarming rate and it is not because of machines. Having robots diagnose and dispense the right formula for drugs and healthcare solutions will likely mean the world will become even more overcrowded, but it will also essentially eliminate healthcare worker jobs, luckily for now, for the next 100 years. 200 years. this field is booming.
  • Military: While the military will always demand workers, because human life is even cheaper to send to war than robots, eventually the military may find that robot power is much cheaper than human life. As for aerial tactics: Eventually an unmanned UAV with one or two operators is cheaper (the salary report is between $ 30k - $ 70k) and around $ 100 - $ 200 million for something like 10-20 planes .
  • Retail workers: Amazon is already experimenting with cashier-less stores. Robots could easily clean and store it, and you could have your customer go through the checkout, the doors will remain closed until that person pays or returns their things that they are not paying for. Otherwise, if they choose not to buy anything, they could go to another area that allows them to simply leave if they detect nothing on your person. Still, you could handle it with 1 or 2 workers, much less than having a full store with more than 10 workers.
  • On the subject of the product: Right now, it is still cheaper to pay workers "online" than to have robots do it.
  • Cleaning service: hotels have to hire a whole team of people to keep the rooms clean. Imagine having robots that do it? Place the robot in the room, press start, and it will vacuum, place a new set of blankets on the bed, clean and wash all surfaces, etc.

I could go on and on: if humans don't kill themselves with technology first (because humans are pretty immature to technology if we're honest with ourselves), then we might have a shot where money in the future doesn't. It matters - and I might be working toward a Star Trek future - where they care more about "human survival" and "discovery" than who has more stuff and who has more power.

After the resurgence of deep learning and the current hype of artificial intelligence forced people to believe that there would be "DOOM DAY", and before that day everything would be normal and after that day everything will change out of nowhere. In contrast to this approach, innovation, change and replacement is a gradual process. That at first it was used in laboratories but it was not viable for commercialization, then that product (here product means robotics related product) is introduced on the market with many errors and failures that make its use impractical or less useful. Then improvements are made and the product becomes poorly familiar with the product.

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After the resurgence of deep learning and the current hype of artificial intelligence forced people to believe that there would be "DOOM DAY", and before that day everything would be normal and after that day everything will change out of nowhere. In contrast to this approach, innovation, change and replacement is a gradual process. That at first it was used in laboratories but it was not viable for commercialization, then that product (here product means robotics related product) is introduced on the market with many errors and failures that make its use impractical or less useful. Subsequently, improvements are made and the product becomes little familiar with daily use. This process goes on and on and new versions are introduced to address the flaws presented in previous versions. After many iterations, at some level, the product becomes practical enough to replace or alternate an option to human labor. No one will believe if I tell you that Washing Machine is also a kind of robot that replaced or minimized human labor. ATMs (tellers), drones, ERP applications, automation-based software, industry automation are all examples of robots replacing humans. Another misconception is that people began to believe that humans were a machine when they talked about robots. Robots can be any human machine or as small as a chip or invisible as bacteria. Computer translation is already on the market and improving at a rapid rate. Therefore, human translators would be less needed and this work will gradually decline or be out of public use. The handheld smartphone is a kind of robot that provides you with the translation in any language you want. The human guide to assist you during your tours is another affected job. GPS on your phone or any GPS device made human assistance obsolete. Driverless cars will strongly affect the profit of drivers. Cleaning machines are already on the market, but a little AI turns into household items. The biggest problem with robots today is that they lack the understanding of language. Nevertheless, Recent advances in NLP and speech recognition will encourage robots to interact with humans rather than passive button instructions. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. They become household items. The biggest problem with robots today is that they lack the understanding of language. However, recent advances in NLP and voice recognition will push robots to interact with humans rather than passive button instructions. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. They become household items. The biggest problem with robots today is that they lack the understanding of language. However, recent advances in NLP and voice recognition will push robots to interact with humans rather than passive button instructions. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular. Many things are already on the market and impacted hundreds of millions of people in terms of providing luxury or snatching jobs. This impact will deepen with each step with improvements in artificial intelligence in general and deep learning in particular.

Not really. This is a giant fallacy, this fear of automation "taking over." I'll explain why this won't happen as briefly as possible:

  • Robots and automation are complex achievements, mainly because robots have "zero common sense." If incorrectly positioned or several tens of thousands of small requirements are not met, the robot's work is useless and likely to harm the other robots and the workspace / assembly it operates.
  • Automated processes are rigid. They cannot change easily, or if they are designed to allow change they are significantly more complex and then even more difficult to change beyond "
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Not really. This is a giant fallacy, this fear of automation "taking over." I'll explain why this won't happen as briefly as possible:

  • Robots and automation are complex achievements, mainly because robots have "zero common sense." If incorrectly positioned or several tens of thousands of small requirements are not met, the robot's work is useless and likely to harm the other robots and the workspace / assembly it operates.
  • Automated processes are rigid. They cannot change easily, or if they are designed to allow change they are significantly more complex and then even more difficult to change beyond the “allowed changes”.
  • An economy with a significant amount of automated services becomes too rigid and vulnerable to "supply chain attacks": Enemies attack the supply chain of the automated society and that automated society is on its knees rather quickly.
    • This danger exists as soon as the automated society becomes slightly dependent on its automation, as interrupting its work causes all other sources of this service / product to be overwhelmed, stopping that society's ability to function normally.

Basically, automation creates innovation stagnation, because automation wants stable processes to automate. Once an automated process is institutionalized, society becomes dependent on it and all other sources of that product / service die. Leading to enormous enormous vulnerability for that society. Our planet does not have enough peace and respect for other nations to allow automated societies. They are simply too rigid in the face of the vulnerabilities of economic and political warfare.

To get to the answer to the question, we must first define: What is a data science project?

Data Science Project
To get a measurable boost from any data science activity, you need to follow a process. Here's a view of the process (evolved based on Jeremy Howard's article): Designing Great Data Products


An example of this process for a project that involves Improving Customer Retention could be the following.


Now the skills required in the various stages of the project are different. Here's a look at the skills throughout each stage.


Today, data science is primarily defined as the box that talks ab

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To get to the answer to the question, we must first define: What is a data science project?

Data Science Project
To get a measurable boost from any data science activity, you need to follow a process. Here's a view of the process (evolved based on Jeremy Howard's article): Designing Great Data Products


An example of this process for a project that involves Improving Customer Retention could be the following.


Now the skills required in the various stages of the project are different. Here's a look at the skills throughout each stage.


Today, data science is primarily defined as the box that talks about modeling.

Fast forward to 10 years
My view is that the task of creating models is becoming increasingly automated and black box.

With new software like Torch 7, H20, MLLib, Wutpal Wabbit, etc., the people writing the modeling software will need high math skills. For people solving business problems like "Cross-selling" or "Propensity to buy models", the greatest need will be to frame the problem statement and orchestrate the correct data for the problem so that it can be fed into this modeling software.

Note that Kaggle focuses more or less on the modeling aspect only in the life cycle of a data science project. And, more and more contests are being won by people who master software such as Wowpal Wabbit, H2o, etc.

Government and political authority.

The reason for this is that many of them argue about the welfare of their citizens.

When help is provided, it is often provided without activity requirements, thinking that buying on the same system that produced the need for help will be restorative. This simply places those who receive help at a lower level in society and generationally generates those who expect this lifestyle.

The “dollar vote” is effective, if you try a product once and don't like it, you won't buy it again.

I wonder if a flat sales tax might be the new norm. This means w

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Government and political authority.

The reason for this is that many of them argue about the welfare of their citizens.

When help is provided, it is often provided without activity requirements, thinking that buying on the same system that produced the need for help will be restorative. This simply places those who receive help at a lower level in society and generationally generates those who expect this lifestyle.

The “dollar vote” is effective, if you try a product once and don't like it, you won't buy it again.

I wonder if a flat sales tax might be the new norm. This means that when a wealthy person wants to make a major purchase, a tax will be charged even if the item or location is for business purposes. It also means that growing a business will help the humblest people in society who simply pay taxes on everyday items and could implement programs to help them do better.

This isn't likely to be built overnight, but it could be scheduled on a five-, ten-, or twenty-year plan and of course that would give those managers huge sums of money to strategize. Your success will be better guaranteed if your goal is to help people.

Coming back to the question, I think corporate commodities (beer, groceries) are falling into the hands of artisanal and widespread infiltration of small businesses. Employee-owned businesses of this size and structure are an asset in creating change within a culture and will naturally use the dollar vote.

  1. Software Engineer (SWE): It is an ever-changing field. AI, robots, etc. need SWE to program it. In the future, general practitioners, general surgeons, nurses, policemen, firefighters, etc. they can be replaced by robots. But robots can't replace SWE, we just don't write code for that :)
  2. You will still need specialized doctors, surgeons, firefighters and police, who have more advanced skill sets and can train these robots and help SWEs develop better robots and perform tasks these robots do not do; after all, they are robots.
  3. Engineers (civil, mechanical, automotive, aviation, etc.) - you still need your roads,
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  1. Software Engineer (SWE): It is an ever-changing field. AI, robots, etc. need SWE to program it. In the future, general practitioners, general surgeons, nurses, policemen, firefighters, etc. they can be replaced by robots. But robots can't replace SWE, we just don't write code for that :)
  2. You will still need specialized doctors, surgeons, firefighters and police, who have more advanced skill sets and can train these robots and help SWEs develop better robots and perform tasks these robots do not do; after all, they are robots.
  3. Engineers (civil, mechanical, automotive, aviation, etc.) - you still need your roads, bridges, airways, etc. Robots cannot replace them except for certain repetitive tasks.
  4. Medical examiner, funeral parlor, etc. - Humans are still deadly
  5. Artists, entertainers, etc. - humans are only humans after all
  6. Sales Personnel: You must sell all these robots to other robots or humans.
  7. Then there will be many protected professions like Realtors, who will refuse to be replaced by Robots for the case of any automation.
  8. Casino Employees - Who Wants To Play With Robots? For that you have your smartphones
  9. Older professions will still be there.

Well, this may not be as specific as you wanted, but certainly advances in artificial intelligence / machine learning will eliminate many of the areas that humans work in.

Just as robotics has affected jobs based on repetitive physical actions (for example, welding car bodies or sorting parts), AI will take over cognitively repetitive jobs. Data entry jobs will disappear… as will “skilled” jobs like public accountants.

Many people don't realize that a large percentage of the buy / sell decisions on Wall Street that people used to make are now made using artificial intelligence algorithms ... no humans are needed.

Basically if a job is based on formulas ... if x happens th

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Well, this may not be as specific as you wanted, but certainly advances in artificial intelligence / machine learning will eliminate many of the areas that humans work in.

Just as robotics has affected jobs based on repetitive physical actions (for example, welding car bodies or sorting parts), AI will take over cognitively repetitive jobs. Data entry jobs will disappear… as will “skilled” jobs like public accountants.

Many people don't realize that a large percentage of the buy / sell decisions on Wall Street that people used to make are now made using artificial intelligence algorithms ... no humans are needed.

Basically, if a job is formula-based ... if x happens, then y must happen ... that's one area that AI / robotics, like logistics, will likely absorb. AI is particularly well suited for moving items from one location to another, be it products in a warehouse or global parts distribution for a multinational corporation.

Get creative folks!

The careers that are in demand now and in the future are shown below.

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