Since the dawn of human civilization we've been developing technologies to improve or ease our productivity. If we take a quick look at history we can see that from time to time there have been crucial moments during which the appearance of a new technology had such a profound impact that it brought huge expectations, and a bit of chaos.
In times like those old methodologies can suddenly be perceived obsolete and everything has to be learned again.
New technologies very often require new skills and frequently shake up our entire mindframes. It’s not easy today, and it wasn’t easy in the 19th century when the first Industrial Revolution took place ushered by the steam engine. What is undoubtedly clear is that what made the difference between those who were able to harness the new technologies and those who couldn't was their education.
Today banks, commerce and industry, are all incorporating AI, machine learning and autonomous cloud technology—our modern steam engine—in such way that there is currently a shortage of qualified and experienced staff to develop these programs and run these systems.
Industry is competing with banking and academia for the best talents and, by many accounts, currently winning: it can afford to pay them better.
At the present time, any bank IT operator job description appears to look for a problem solver-cum-mechanic who can feed paper to the copiers, who can be nice to people in the bank and keep them operating. The immediate and near future need is for artificial intelligence operators and scientists who can manage operating software for AI programs and applications, someone who has mastered an understanding of the theory, implementation and application of not just basic AI theory but also of unsupervised and reinforcement learning algorithms.
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Where are the short-term future operators of any bank's IT department?
A number of universities, most of them in developed economies, are offering existing computer science graduates advanced courses to teach students the theory and implementation of bio-inspired machine learning algorithms which include unsupervised learning in neural networks, and reinforcement learning, that is, the KEEL (Knowledge Extraction based on Evolutionary Learning) sub-set of AI. According to Forbes magazine, demand for computer science courses in the USA has out-stripped the supply of professors because the tech industry hoovers them up.
According to the Global Education Network, even in the most advanced economies, there is a distinct shortage of professors to teach AI to graduate computer science students, because industry offers better pay and better conditions than academia.
Many universities in the USA, for example, have such a severe shortage of computer science faculty members that some faculties have been forced to close entirely. A common argument is that there is currently a shortage of good computer scientists whilst the universities themselves complain about the lack of emphasis placed in schools on mathematics and basic computer programming skills.
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Why investing in computer sciences education will make banks thrive
The real problem appears to be the quality of programmers and developers as opposed to the quantity. If someone is to develop and operate autonomous systems which can actually self-learn, i.e. adjust automatically, with little or no human intervention, then he or she requires more skills than simply being able to program.
This implies a breadth of human knowledge, understanding, and perception that most programmers never had the opportunity to develop and many accelerated courses neglect. Target Jobs actually warns graduates that employers are looking for more than just the computer science degree.
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So how can the banks compete with industry for the brightest and best talent?
Given the time needed to develop the skills that are required, the banks need to start now encouraging these skills at different levels, in schools, on computer science courses and in AI graduate courses, nurturing the potential future employees with scholarships, apprenticeships and internships, etc.
Possibly the best place to locate such future talent is in the developing economies where opportunities are scarce, especially since, in many countries, only the wealthier have access to higher education.
Certainly, the banks cannot sit and hope that the educational system will feed them the talent they need, with the qualities and in the numbers that they require. In order to compete for that talent, they need to be proactive, and start today.
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