The Rise of an Irrelevant Class

 Amazon, an e-commerce retailer made a net revenue of 178 billion dollars with just 5.5 lakhs of employees in 2017. On the same year, 5.5 lakhs of Nepalese working population contributed a share of just 0.8 billion dollars to the nominal GDP. The main cause behind this huge difference is that Amazon heavily makes use of technology; primarily Artificial Intelligence. Such a huge gap is suggesting that human labor force is far less important to the economy than the machine labor.

   Yuval Noah Harrari, in his book 21 Lessons for 21^st century writes that with Artificial Intelligence taking over, there may remain very few jobs for humans to do. And if so, what will the rest of the population that get displaced do?

 While most of the economics textbooks have contained only about the high class, middle class and low class of people, it seems that an even more serious class i.e. an irrelevant class of humans is already emerging. As machines perform better than humans, there will be a large bulk of population that will not be needed in the economic cycle and hence they will have to remain jobless.

 What is even more serious about this phenomenon is that once it starts to happen, it is likely to happen at a tremendous speed. The moment government approves of AI doctors; hospitals are going to adopt them as fast as possible primarily because of three reasons: i) AI doctors will be far more precise and do not make human errors. It is also much easier to keep them updated. It would only take a fraction of second to make all the AI doctors around the world to take in new information. Ii) AI doctors are going to be incredibly cheaper than human doctors. Iii) and AI doctors can work 24/7.  Similar reasons apply to other professions that are vulnerable to AI.

 As this happens to many other professions, one does not need a PhD in Economics to understand that human labor will contribute a very small fragment to the economy. And, once this happens, it is also not hard to understand that a very large bulk of population is going to be irrelevant to the cycle of economics.

How will this affect Nepal?

  Nepal’s current economy is based upon remittance, agriculture, industry and services. Speaking of remittance, it is likely to be affected the most. The sort of jobs that Nepalese people do abroad is that of cleaning floors and dishes, driving, salesperson, security and construction works. The work of cleaning dishes and floors have already been mastered by AI robots; they only need to be manufactured at a large scale so that such robots will be cheaper than human labor. Companies like Tesla and Uber have developed self driving vehicles which are far more efficient than human drivers. The rise of internet retailers will wipe out the job of salesperson at a glance. And finally, there are already robots for works like brick-laying which will set a goodbye to a huge number of construction workers.

 On the part of agriculture, a total of 30% people are involved in Nepal. This can easily be brought down to less than 2%. The proof is the agriculture system of developed countries where less than 5% of population is doing agriculture.

 The jobs of industry are also not very safe. The fact that most of the industry jobs are routine styles that require speed working with hands is enough for automation to take over.

Speaking of service sector which consists of a very wide range of tasks, it highly depends on the nature of those tasks in determining whether it is vulnerable to Automation or not. For example, a job of a cashier in a bank is vulnerable because of its routine nature. In fact, according to Vikram Pandit; an ex Citigroup CEO, more than 30% of jobs in banking sector are likely to be wiped out. Stock brokering will not be a job of humans at all. It is already the case in developed stock markets around the world. However, if your job involves emotional intelligence, subjective feelings and cannot be done using mathematics and precision; your job is more secure from AI. The examples could be of a Manager, Lobbyist, social workers, etc. The reason that these jobs are more secure is that they involve tasks related to human emotions which machines really suck at.

This phenomenon of AI taking over is going to be of a very interesting experience yet a painful one.