Information technology creates more high-skill jobs and can automate lower-skill ones. For Turkey, rapid growth of the domestic information technology sector has been correlated with more youth with higher education degrees being employed. The number of youth with higher education degrees grew even faster, so there were also more unemployed youth with higher education degrees.
There are serious employment problems for those with higher education degrees in India even as the software sector, already the largest private employer, is expected to continue to create jobs. In countries like US which are at the forefront of technological development, the fear is that increasingly higher-skill jobs are being automated while student debt is exploding.
Part of the problem is that the increased demand for education can lead to oversupply. The number of universities in Turkey has doubled in less than a decade. In India, Ph.D. may be the easiest degree to get. Even in developed countries standards may need to be relaxed to fill seats. Still, employers worldwide cite lack of appropriate skills as a major concern. There are open positions but no one appropriate to fill them.
So what does it mean for you as a student? It means that a degree could be very important as it could get you shortlisted for the interview. After that, what you know will make the difference. Use your university time to gain a good understanding of your chosen field and how technological development can impact it. Use class material as background to put practical issues and trends in context. You may even want to try setting up something on your own, and given the employment situations goverments are promoting entrepreneurship. What if you already have a job lined up in your family company? It is even more important that you know what you are doing because if something were to go wrong the consequences could be much more severe.
For policymakers it means that promoting information technology does not, by itself, solve employment problems. Economic and educational policies need to be coordinated with policies promoting technology. This is easier said than done even though we now have enough computing power to predict outcomes using complex models and large data-sets.
The record thus far has not been all that great. Complex financial models designed to reduce risk, combined with well-intentioned laws to prevent discrimination, led to the 2008 financial crisis. In the US 2.6 million jobs were lost, making it the worst year for employment in more than 50 years. Youth unemployment in 2013 was close to its crisis peak at 12.6% globally; and at 18.1% in Developed Economies and EU, 28.3% in the Middle East and 23.7% in North Africa in 2012, potentially leading to a "lost generation." Wealth disparity is growing in most countries, Turkey has been an exception. The 62 wealthiest individuals, newer esimates are in single digits, now hold as much wealth as the bottom 50% of humanity even as the population keeps growing, and the top 1% of the population holds more than the remaining 99% combined. Less than a thousand companies control most of the resources in the world.
Why not create more detailed models to get more accurate predictions? As models get more complex, it becomes increasingly difficult to tell whether their predictions can be trusted. For engineering models which deal with physical quantities, it is entirely possible to get reasonable looking results when the model is quite wrong, such as discussed here and here. Still, in physical sciences we can keep testing models under different conditions to find their limits. For social sciences the problem is much more severe. Experimental conditions cannot be changed at will and we are restricted to historical data for testing. The historical values used to test models themselves depend on belief in particular models. If you define the price of a stock as what someone will pay you for it, and everyone believes it is worth $100, then by definition that is what they will pay you and that becomes the price. In fact it does not even have to be everyone, just those who have enough money to move markets. The person who started computerized trading realized that to make money he did not have to predict the correct stock price, if such a value were to even exist, but only the price large financial institutions would calculate using their models. There is increasing discussion in literature whether mathematical models for such complex systems have any predictive value at all. With increasing computing power agent-based modeling is becoming popular as an alternative to complex mathematical models. It just shifts the complexity to modeling agent behavior: peoples' beliefs and how such beliefs form and evolve; their decision-making processes; their goals; psychological factors; and how what is considered succesful behavior changes over time. Even the rules of the game are endogenous and people may not even follow them as these are not the laws of nature which are satisfied automatically.
We cannot wait for the centuries-old discussion between egalitarianism and libertarianism to resolve itself based on even more modeling and testing, especially if the results are always going to be open to contention. Perhaps we need a different approach to socioecenomic policy.
Why not create employment for yourself and for others, and make sure your family is a part of the 1%, or the 0.1%, or whichever level is in? Governments are promoting entrepreneurship. The success rate of startups is low enough and repeated attempts typically do not improve chances. What happens if you do succeed and set up a company that survives for 20 - 30 years? It was said of family businesses thousands of years back that the father creates, the son preserves and the grandson destroys. The situation has not really improved, since. Across countries, the chance of success, post-succession, is between one-in-four and one-in-three. In Turkey about 30% can manage the first succession through to the next, 12% the second and only 3% of such companies continue past the third generation. The problems are related to human nature, often intra-family issues which make such companies more difficult to manage. Information technology can help with this, if applied properly.
What good would economic development do if the environment could no longer support us? Information technology is the first technology that can actually reverse the environmental damage caused by development. Did you know that monitoring energy usage can not just save your company money, it could even save your company ?
Visit the Is IT Green website to start to learn how to conduct your own ICT energy audit and get tips on how to make your information technology infrastructure greener. While there play the game, attend the online course on moodle, and get your certificate.