Apparently, organizations are struggling to find qualified candidates for AI-related positions and jobs. How can we overcome this skill gap in AI?
If companies are struggling to find the right candidates for AI related tasks, something is wrong with the underlying education system. The education system is the place in a society which is producing skilled phd students. Countries which have a lack of universities struggle in providing expert employees.
The dominant reason why a country isn't able to educate enough people and fails in educate highly skilled people are the costs. If the costs for educating a single AI experts which has a phd degree is 200k US$, only a few of them are available each year. To overcome the issue the efficiency of education has to be improved which is very easy by transforming education into a market driven business. Markets have the natural tendency to provide goods and services at a lower price.
The problem is, that the idea that education is a good which has to be provided by a company but not by a government financed university isn't very common worldwide. A market driven education would open up new chances for the masses to participate in AI related jobs.
Sometimes, it was argued that the United States have already a market driven education system in which the M.I.T. and other universities have customers. A detailed look into the government spending shows, that each year 1000 billion US$ taxpayer money are redirected into the education system which is 5% of the Gross domestic product. This demonstrates, that the government doesn't trust the market and likes to pay the bill by it's own which is the opposite of a market driven economy.
The way to overcome the skill gap in Artificial Intelligence is to overcome the gap in human intelligence — the distinct lack of introspection and the overwhelming distractions that keep most of us from observing what would be obvious about intelligence in our world. That later gap impacts more than the AI skill space, so there would be added benefits in closing it.
Organizations are struggling to find qualified candidates for most roles, for leading entire industrialized countries right down to people to deliver meals and letters to the correct address, not just AI professionals. Realizing this fact that hiring managers of all kinds from all over the world and in nearly every human industry already know we come to the crux of this question's answer.
The scope of AI is a superset of the scope of I — that is the set of things we want artificial minds to do is the set of things that human minds already do plus some things human minds can't. Another heuristic that should be considered, even if it cannot yet be proven, is that to automate something, it is often necessary to do it manually first. From these reasonable initial assumptions, it appears there cannot be general AI experts until there are general experts.
When people place "AI Expert" in their resumes, it can mean a number of things, including these.
- A gross misunderstanding about the difficulties in imbuing intelligence into machines
- Technical megalomania
- They merely mean that, once they fully understand some problem set through experience in gaining such understanding, they are experts at using existing technology and sometimes extending and customizing it to produce intelligent behaviors in machines to work with the problem set to arrive at beneficial solutions.
A firm foundation will help students of AI become this third type of person above. Of course a strong mathematical foundation is important, especially probability, since intelligence is often very probabilistic as decisions are often made with only partial information and in time and resource limited computing frames. Understanding computer science in general is important. Solid background in process engineering, biology, genetics, physics, control theory, optics, and cybernetics. See some other Q&A here for more details.
- What are examples of reference books to start with AI?
- Which areas of applied math are relevant to AI?
From the above can be seen why there are so few authentic AI professionals that can find reasonable approaches for many of the problems involving intelligence that employers would like to automate.
This is not a very objective question and as such, so is not the answer.
AI is lacking a lot of people because it had an explosion in the past few years, and every company wants to have an AI department whilst in the past it didn't exist. Since the only people actually knowing AI-based work are the few who worked with it in the past and the ones that are learning it right now in colleges or at home due to the good market offers present at the moment for that field.
In order to "overcome that skill gap", at least in Europe, recruiters don't seem to be looking for much at the beginning, it depends on the specific area. If it is more turned to Natural Language processing, Data Science, or some other theme... But in general, I would say any course on engineering, home study on online courses about the area, as long as you have some maths background, they will take you as a junior and teach you the basics, and you will learn as you go. You just need to have the right background.