Tina Ehrami
Aug 29 · 9 min read

Solving tomorrow’s challenges by predicting and appreciating a wider spectrum of talent and skills

‘What am I good at? And how can I use my talents to contribute to society?’ Most people reach a point in their life when they reflect upon these questions. They evaluate their skills, interests and dreams to decide upon a career path or a purpose. In the old days, however, a farmer’s son wouldn’t dream of wanting something different than taking over his father’s profession and becoming a farmer himself one day. But those times have changed. A profession is not for life and many people start a new career once, twice or thrice in their lives. Not always because they get bored with their job, but because there are changes in their profession due to changes in economy, technology or society and they, for some reason, can’t change along with their profession or their work simply becomes obsolete. And sometimes these changes accelerate, as is the case in our current Fourth Industrial Revolution (4IR). As a result, the next question people will be asking themselves is not so much ‘What am I good at?’ but rather ‘What is my potential?’ and perhaps even ‘Which algorithm can provide me with learning path options to maximise my potential to add value?’ The next chapter in ‘learning’ and ‘professional development’ is that of predicting human potential and the ability to provide needed solutions to tomorrows challenges.

The way we used to assess our potential, until now, used to be through education and after that our human capital value on the labour market. From primary school to university people are tested on their knowledge and their skills which they have acquired through educational training. Today, however — in our 4IR — developments in expoenential technologies, such as artificial intelligence (AI), biotechnologies and nanomaterials have been accelerating in such a speed that traditional education institutes, as universities can hardly keep up with the needed change in their curriculum content to fit the demand of the labour market. Nor can these institutions find the teaching staff that is able to teach these new concepts. The moment a student is handed her or his university diploma, their knowledge and skills will already be outdated. Many companies (will) have to upskill or reskill their workforce in order to be able to survive. According to the World Economic Forum 2018 ‘Future of Jobs Report’ 75 million jobs are expected to be displaced by 2022 in 20 major economies.

There are a set of tipping points at which the technologies of the 4IR will become widespread enough to create massive societal change. This will lead to significant impacts on our lives and require shifts in employment and education.

The expected shift in education, however, will need to provide solutions which are difficult to imagine, knowing the characteristics of existing traditional learning institutions. A paradigm shift in learning and development is perhaps needed more than just a few adjustments to existing systems. Knowing the challenges that lie ahead, the value of traditional studies and traditional systems in which those studies, skills and knowledge are valued are becoming questionable. Foremostly when considering all the different set of skills that are currently enabling people to deliver cutting edge solutions. Substantial changes to the science and technology curriculum are needed to allow for students to develop skills in the rapidly emerging areas of genomics, data science, AI, robotics and nanomaterials. The Massachusetts Institute of Technology (MIT) published a report (The Future of Education Report) which strongly emphasizes the need for leveraging online courses to bridge the current knowledge and skills gap.

The problem, however, is not just lacking educational institutions, but also the most existing ‘over appreciation’ of degrees, IQ tests and other kind of ‘one size fits all’ assessments that are being used to select and recruit talent. When considering the skills and knowledge gap, these also apply to HR using outdated variables to judge candidates by. This is where Artificial Intelligence comes in. AI is not just one of those technologies creating the existing knowledge and skills gap; it is at the same time, the solution to this vast human capital problem. But to get to the good part of solutions, let’s take a few steps back and discuss the basic concepts first.

Human Potential is foreseeing human capital.
The term ‘human capital’ is mostly used in the domain of Human Resources and defines the ability of the employee to create value for the company, based on his or her perceived and proven record. But since the speed of technological development is moving beyond our ability to foresee the set of skills that will create that value, we have no means to perceive, value or nurture those skills that will be needed in the next few years.

Therefore ‘human potential’ is a better description of how we should look at the full set of skills someone has and even his or her potential skills that he or she is likely to develop, based on his or her talents, interests and mental abilities.

By considering the human potential instead of the human capital, we could learn to analyse our own behaviour, and our capacity to develop in a certain direction, which we otherwise perhaps would not have discovered. This could help us make decisions about our own career paths. For companies, having information on a candidate’s potential, by measuring resilience, adaptability and learning capacity, for example, is of great value. Foremostly in times of uncertainty and great change.

Eventhough we could think of skill sets that could help us deal with the challenges of the 4IR, being technological skills, physical, cognitive and social skills, there is still a grey space when it comes to knowing whether one is likely to develop those skills, if they don’t have those skills yet. As mentioned earlier, we could take the Darwinian survival skills as a base of prediction, such as resilience, emotional intelligence, adaptability, curiosity and learning capacity. These skills help us to navigate through uncertain situations and come up with solutions that otherwise would not have been found. So if it’s such skills that we should appreciate more, how do we use our existing tools to measure them?

We could blindfold people, drop them in the woods and see how they find their way back. This is in fact a reslience practice used by children’s scouting groups in The Netherlands. But a different — and perhaps a little less extreme — measure would be to assess candidates in game settings. We could monitor candidates’ emotional intelligence and creative problem solving skills through laboratory setting games. But since these elaborate and expensive settings are only applied in a corporate recruitment procedure, after a first selection of candidates has been made, they’re not often applicabe for ‘screening’, nor are they accessible for candidates who want to self-assess or explore their options to begin with. And then there is the question of just how reliable behaviour is in a game setting when one is known to be monitored for recruitment purposes.

The key is using broad spectrum information on behaviour, talent and skills to analyse the potential of skills and knowledge that one could develop and apply that to what kind of learning and career perspective possiblities would fit the future needs of the labour market.

Human potential based automated career path prediction.
Since behaviour is not always registered in real life (unless you live in China) we would need sources to acquire data which we could use. The kind of data we already have, is data on our digital behaviour and content analysis. Patterns in these two categories of digital behaviour could provide sufficient data for psychological analysis of one’s character. Content development and content use portray interest, abstract cognitive understanding and drive, while digital search and click behaviour could be translated to traits as general IT knowledge, creativity, curiosity and multidisciplinarity.

In fact, algorithms using content and digital behaviour could provide full cognitive, social and emotional analyses of an individual, as input to portray multiple potential future learning and career paths. Such AI applications yet need to be developed, though applications as IBM Watson’s Talent Match imply an already existing commercial interest. This application uses unstructured digital information on candidates’’ indirect skills — that are not explicitly specified on a resume’. For a more predictive model, other than a ‘talent matching’ tool, we would need to await Artificial General Intelligence or perhaps even Artificial Super Intelligence to present more accurate analyses.

Of course we are more than just our digital behaviour, and there are certain talents that are not (yet) registered digitally. But nevertheless our digital behaviour does reveal certain aspects of our personality, which could be used to elobarate further analayses on. Traits as agreeability, intelligence, emotional stability, extraversion, conscientiousness, openness as well as openness to new experiences and neuroticism are already detectable through machine learning. Why not put those analyses to use and apply them to generate options for future learning and career paths?

For some the idea of having an algorithm decide upon possible future career paths based on their digital behaviour is difficult to digest. Having no real ‘influence’ over such important decisions is indeed scary. Though of course there should be meriad of possible outcomes that could be expected, and there is no force to follow any instructions AI would provide. Being able to maintain a sense of agency over one’s fate, however, does seem to be preferred.

Luckily, there is a possibility to gain more agency in this process and provide a more meaningful input for AI to come up with scenario’s for our possible future professional development. There is indeed an important source of digital input we already could use that could indicate in a more concrete and straightforward manner (without the digital psychoanalysis) what we have potential for, namely the use of microcredentials.

Microcredentials as an important ingredient for predicting human potential.
When considering that our behaviour online could exemplify an underlying potential we perhaps yet need to manifest in our everyday life, why not reconsider the status of an online course we put time and effort into? Unlike the traditional studies we do, with pre-selected curricula, which we had little say in and perhaps were not so passionate about, but needed to accomplish anyway, we do choose our online courses ourselves. There is an intrinsic motivation and drive that brings us to the computer, laptop or smartphone for hours on end to follow an online course in a certain subject we are interested in. This implies a talent or at least an interest in that subject and the perseverance to pursue more knowledge about that subject. This could indicate potential to a possible learning path that yet needs to be developed, but would apply to our learning needs and abilities.

So, in short, our digital behaviour, online courses, or micro credentials (these could also be gathered through e-learning, volunteering, projects, testimonials or ‘badges’) could be used to assess skills as learning capacity, adaptability and resilience , which then could be used to provide a wider ‘human potential assessment’ to various future learning and development paths. This could ease the recruitment process for companies in search of talent, but it could also empower highly talented and resilient people who otherwise would not have been able to perceive their own full potential. Both parties win.

But how do we turn online courses and our digital behaviour into automted scenario’s and digital psycholoanalyses that would help us choose a learning and career path that would not only fit our learning capability, interest and character, but also the needs of society?

In part two of this series I will elaborate on the mechanisms of behavioural science, psychology, learning theories and artificial intelligence behind the idea of automated human potential scenarios with AI. Stay connected!

The Hague Pioneers

Stories by change-makers, idealists and opportunists in the international city of peace and justice.

Tina Ehrami

Written by

The Hague Pioneers

Stories by change-makers, idealists and opportunists in the international city of peace and justice.

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