How do you stay relevant when technology is disrupting our work and education system?

One of the things that always fascinated me about scholars and intellectuals throughout history is the diversity of their knowledge and expertise. When you read about someone like Averroes (Ibn Rushd), for example, you notice that he is described as a scholar of philosophy, theology, medicine, astronomy, physics, psychology, mathematics, Islamic law, and linguistics all at once. The same can be observed when reading about Avicenna (Ibn Sina), Isaac Newton, Benjamin Franklin, René Descartes, and many others. They might be more famous for a certain field (e.g., Newton for physics), but you always find that they have published some work on other areas of knowledge such as philosophy or linguistics.

On the other hand, experts today are usually known for a very specific area of knowledge such as "theoretical physics", "consumer psychology", "machine learning", and so on. Society went from a general approach to education and expertise to a more specialized one.

Why did this happen?

The answer to that is simple: progress and economic evolution. The movement from generalization to specialization did not happen by accident. It was a natural outcome of events such as the agricultural and industrial revolutions and the rise of capitalism. Those events gave rise to ideas like division of labor and the introduction of factory assembly lines which naturally had a huge impact on the world's economy, as well as the education system that is responsible to produce labor to support that economy. I won't be able to cover those details in a short article but if this interests you, then I urge you to read Wealth of Nations by Adam Smith, or the history of Ford Motor Company when its founder, Henry Ford, introduced the assembly line in his car factories in the early 1900s.

Dividing labor, and sometimes countries, into specified categories and tasks was a necessity for the economic growth and globalization. Today, you wake up and brush your teeth using a toothpaste made in Poland, drive a car manufactured in Germany, to get to your office where you sit on a chair made in Italy. You do that so you can interview a candidate for a job that requires a degree in a specialized field like finance or marketing to do a specific a job, so that the company can function properly and achieve its goals.

This model has been quite effective for the past few centuries for both people and organizations. It has been effective for people because they can go to school, specialize in something useful, and get a job where they can make a living and provide for their families. It has also been effective for companies because they can influence the education system to train and prepare people to meet their professional needs. However, with the advancement of technology and the introduction of concepts such as AI, robotics, and machine learning, I believe this model is about to break down and face some serious challenges.

Technology will disrupt most of today's specialized jobs

For the purpose of this article, I define a specialized job as one where you can train someone to do it by following a methodology or a list of instructions. The easier it is to train someone to do a job, the more specialized it is under this definition. Therefore, when you think about it, all jobs today fall on a spectrum from most to least specialized. For example, it is easier to train someone to be a cashier than a truck driver. But it is easier to train someone to be a truck driver than an accountant. Therefore, if we order those three jobs on that specialization spectrum, from most to least specialized, the order would be: cashier, truck driver, then accountant.

With the rise of technology, the first jobs to be automated are the highly specialized. If you don't believe me, just look around you. Automated cashiers and vending machines in supermarkets, ATMs in Banks, automated customer service in Service Providers. What do all these jobs have in common? They are extremely specialized as they require minimal training. Will automation stop there? No, but for the next wave of less specialized jobs to be automated, technology needed to be advanced further. To automate personal assistants, for example, speech and voice recognition technologies needed to be developed (Siri and Alexa). To automate doormen and physical security at residential buildings, facial recognition technologies needed to be advanced (CCTV and 5G processing). To automate drivers, self-driving car technologies needed to be improved (Tesla self-driving cars).

Therefore, using the same logic, I believe that the next wave of endangered specialized jobs include driving, accounting, financial modeling, medical imaging, and so on. Why would a company hire an accountant if a future software can audit its financial statements within seconds at a lower cost? They might have someone to verify the data in the beginning, but eventually, even that person can be dismissed. This pattern will reemerge as long as technology advances, and technology always advances. The message is very simple, if a computer can be trained to do your job, then that job will be automated sooner or later. I recently watched a podcast where Garry Kasparov, a chess grand master who was defeated by IBM's Deep Blue machine, stated the same message; you cannot beat a machine at its own game. So, what do we do then?

What does that mean for the future of work and education?

I started this article by highlighting how scholars in the past were very diverse. I like to tell myself that the future of education and knowledge will turn full circle and go back to that state. But reality is more complicated than that. Nobody can predict the future, but I can't shake the idea that everything that can be trained will be automated. So the question now is, what should you do if your job falls under those highly specialized categories? Or if you are about to choose a major to study in school?

The short answer is; I do not know. My goal here is to make you think about those questions rather than telling you what to do. I do, however, have some guidelines that I follow in my personal life and education. They are based on my own opinions, and I don't claim that they are for everyone. But here they are:

1- Always complement your specialized technical knowledge (e.g., technology or engineering) with a diverse set of generalized knowledge (e.g., history, psychology, or philosophy)

2- Try to mix areas of expertise that are not usually mixed (e.g., Steve Jobs mixed arts and personal computers to revolutionize the concept of user experience)

3- Use 1 and 2 to build specific knowledge that cannot be trained. Here is a great article on the definition of specific knowledge by Naval Ravikant.

4- Work in areas that sharpen your soft skills and where your daily challenges are rarely the same (e.g., sales, consulting, or entrepreneurship)

I may write about those in more details in the future, but for now I just wanted to share them. I like those guidelines because they make it hard for anyone to box you in a certain area. Again, they are just guidelines that I use and tweak as I go to make sure that I can add value wherever I go; a value that no machine can replicate easily.

I hope you enjoyed this article. If you did, please share it and let me know your thoughts!

Regards,

Abdullah