7 Careers To Doomed Because Of AI
The majority of Americans now believe that within the next 50 years, robots and computers will be taking away our jobs. Whether this is a good or bad thing is debatable because we really cannot predict what exactly will happen with the workforce in the next half of the 21st century. What we do know is that most work can be easily automated thanks to advancements in machine learning and robotics. For this reason, researchers are putting a lot of effort in trying to predict which jobs can be replaced by computers and robots and which ones are better done by humans, at least for now. Furthermore, while some see the future of AIs as being detrimental to human survival, others see the increase in automation as a positive change that can make our lives easier.
1. Drivers
In a research carried out by a market research company called Forrester, the prediction is that robots will eliminate an estimate of 6% of all jobs in the US. According to their predictions, the transportation industry will be hit hardest due to companies like, Uber, Google, and Tesla that are working hard on developing automated, driverless cars. These cars will drive better than humans because they have sensors that predict objects within 20 feet away and this will reduce the number of accidents which mostly occur due to human error. What this also means is that jobs like a taxi driver, bus driver, delivery drivers, and similar will be gone. Futurists researcher, Thomas Frey has similar predictions, but he also believes that this type of change in the transportation industry will create new jobs such as driverless operating system engineers and there will be a greater need for delivery dispatchers.
2. Retailing
The retail industry is one of the largest industries worldwide employing a large number of the world’s population. In the US alone, nearly 14.8 million people were employed in retail in 2011 which is around 10% of the total US labor force. Seeing the need for human resources in retail disappear due to AI automation may seem rather devastating. As McKinsey and Co report, retailing is one of those sectors with a high potential for automation. The report estimates that up to 53% of work done in retail can be easily automated. Examples include packaging, maintaining sales records, gathering product and customer information, and data collection activities in general.
3. Educators
Futurist speaker Thomas Frey stated at the TEDxReset Conference in Istanbul that 2 billion jobs will disappear by 2030. This is roughly 50% of all jobs done by humans worldwide. While his prediction seems scary and shocking, Frey sees these changes as being neither positive or negative. According to Frey, teachers, trainers, and professors may no longer be needed in the future. Since the OpenCourseWare movement first started, more and more academies are joining in on the movement. As Frey explains it, teachers only need to teach once, record it, and move on to another topic. The recorded material can be downloaded by anyone, anywhere, making education easily accessible. What this all means is that education is shifting from a teaching model to a learning model which might not be a bad thing after all.
4. Doctors
Artificial Intelligence is already being widely used within the medical fields and for good reasons also. Diagnosing and treating dangerous illnesses like cancer can be tough and requires keen observation. Human error in such cases tends to be unforgiving. Technologies like Imagia is aiming to bring AI technology in the diagnosis and treatment of cancer. By using cancer data, Imagia technology aims to ensure that all cancer present in imaging is detected each and every time.
5. Pilots
As with drivers of land vehicles, automation in airplanes is likely to take place as well. As explained by Mary Cummings who is a director of the Humans and Autonomy Lab (HAL) at Duke University, becoming a pilot will soon seem like a dead end job in the near future. She also sees problems in automation of vehicles, including aircraft. Humans will have to watch over automated systems which seem like a rather boring job. Because humans have a tendency to become jaded when they’re not doing something useful, she sees automation in transportation industries as causing more accidents which is the opposite of what we were thought to believe.
6. Predictable manual labor
Not long ago, machines have replaced human labor in agriculture. The same scenario is taking place in manufacturing industries where welding and assembling is currently being done by robots. McKinsey and Co state that all predictable physical jobs have a 78% chance of disappearing due to automation technologies. On the other hand, construction, forestry, and raising animals has a much smaller chance of becoming automated at only 25% according to the firm’s research.
7. Personal assistants
You’re probably already familiar with the emergence of virtual assistant technologies. Well, this type of technology may reduce the need for personal assistants in many industries. An example of such a technology is Mya, an AI recruiting assistant that can make managing large candidate pools easier. Mya is capable of searching large numbers of resumes and applications while informing both candidates and employers on where they stand in the employment process. A similar platform is Echo Box which is an AI social media assistant that can help companies with social media marketing.
Conclusion
While it is quite obvious that our world is becoming increasingly automated, that does not necessarily mean that there will be no more need for human labor. Even though machine learning and artificial intelligence are advancing at a fast pace, humans need to monitor the activities of such technologies in order to minimize error. Besides this, the changes taking place in our working environment is more than likely to create new opportunities and needs so we’ll probably be witnessing old jobs disappearing and new ones appearing. This shift in our economy has already been taking place for a long time now and whether it is a good or bad thing is hard to predict.
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