Is computational thinking the best way to protect your employability?
Without being constantly open to learning and growth, we all risk obsolescence. Business needs digital, people and knowledge working together and the answer may be computational thinking, says former Google France CEO Jean-Marc Tassetto
Without being constantly open to learning and growth, we all risk obsolescence. The world, after all, keeps changing – self-driving car engineer, blockchain developer, growth hacker – these were not job roles that existed even five years ago.
As the World Economic Forum’s 2016 Future of Jobs report and the OECD also found, among many sober analyses of the future, AI will take over more and more tasks. Some authors claim that only as little as 35% of current skills will still be relevant in five years, others put it less. But it will still be significant.
What, then, will future-proof your career? Ensuring a workforce is fit for the future means addressing ‘soft skills’; in other words personal attributes such as communication, teamwork and problem solving. As the robots move into our factories, homes and hospitals, our job roles will change, and with it the necessary skills set to keep relevant.
Clearly, in this digital age, everybody will need to have skills complementary with digital technology. But not everybody will be in need of core programming skills; people and knowledge working skills associated with the cloud, mobility, big data, Internet of Things (IoT) and blockchain will also be important. At the same time other sorts of non-technical skills will also finally be recognised, like leadership, participatory management and social and environmental responsibility.
Smart companies demand that their employees take time out for education. In response, business needs to make the right skills a focus of their own continuous learning programmes. To ensure success, they also need to get away from the top-down approach of old, else their efforts will be in vain.
Reflecting the reality of how people learn, enhanced and in short bursts, always available remotely and at one’s convenience and own pace is how the world of business needs to carry out training.
The old method of scheduling fixed hours needs to be discarded, in favour of a learner-chosen model and a virtual learning environment, in which all lessons and material are online.
To maximise learning it is thus vital to go digital, and digital lessons mean a trip to a coffee shop can become a half-hour learning session; the car becomes a podcast lecture theatre. In addition, in our ‘kidadult’ age, incorporating features like quizzes or rankings increases uptake and engagement.
Christelle Burgy, Capgemini Consulting’s learning & development manager, incorporates such features in its digital training and notes that 70% of its cohort log on each month. She told us: “This has been the first time that we have seen such high rates of adoption from users of all different grades. Users find it engaging and even addictive.”
Computational thinking (CT), where the focus is not on the machine but on the human whose thinking and learning is enhanced by the machine, is a great example of what that modern approach translates to. That’s because it is useful not only to understand what the computer does – such as algorithms, the way a computer can learn from the data it gets, the limits of computation and so on – but also to shape what the person does, like preparing a relevant data set for machine learning, dividing a problem into useful chunks resolvable for a computer, detecting configurations where automation and parallelisation can be introduced, designing digitally and so on.
Governments are beginning to make this sort of reskilling a goal. The US, for instance, is among the early adopters of such a forward-looking approach, with the National Research Council working intensively on CT from 2010. Major US tech university Carnegie-Mellon has its Microsoft-sponsored Center for Computational Thinking that provides seminars, workshops and research activities on computational thinking in any domain of life. Leading European Higher Education institutions are also going this way, like the Federal Institute of Technology in Lausanne, Switzerland, introducing dedicated Computational Thinking lessons in all entry level courses across all disciplines. And Google is militating for the democratisation of CT for early years to 12 in education globally, providing a variety of teaching material to educators.
All this has to be all about the user experience, so as to encourage learners to develop all their skills to their full potential and to future-proof their careers. The verdict’s clear; employers and employees alike need to offer skills like computational thinking if they want to thrive in our complex world.
As the robots move into our factories, homes and hospitals, our job roles will change, and with it the necessary skills set to keep relevant