When we talk about learning, in this context, we mean the ability to identify complex patterns in a sea of data. In reality, it is not the machine that actually learns, it is an algorithm that reviews the data and is able to predict future behaviour.
It seems logical to be busy with this task, because in a society where cost reduction and efficiency have become key factors, having machines or computers that perform certain functions is crucial.
But what are those patterns of activity in which machines are better than humans? There are mainly three: in those actions that are repetitive, that involve specialized work, and that involve the handling of data. When there are jobs or actions in which these three factors coincide, machines are undoubtedly much better and more efficient than humans. Moreover, once instructions have been given, they comply with orders blindly and do not ask for any remuneration.
Coincidentally, many of the jobs performed by a significant portion of the workers in our society meet these three requirements. Therefore, it is not unreasonable to think that this new industrial revolution will mean a replacement of jobs performed by machines that will do the same function, but with greater precision, efficiency, safety and at a lower cost. It has been estimated that this effect will displace some 75 million people from their jobs. It should be noted that in the last crisis in 2008 some 30 million workers were made redundant.
However, it is not all bad news. As in other industrial revolutions, this paradigm shift will lead to an increase in jobs, estimated at around 120 million people. Jobs that will require different knowledge and skills from those possessed by machines. And it is here that we need to reflect on education.
Today, even though important advances have been made, the education system and its evaluation parameters are based to a significant extent on three criteria: learning data by heart, performing repetitive exercises, specialising in one thing and following orders. Incidentally, the four things for which the machines are best prepared. In 2017, in the entrance exams to one of the best Asian universities, a robot already scored better than 80% of the students who applied.
It is necessary to make a reflection in the educational world, because it does not make sense in the immediate future to continue training young people to do tasks that machines can do much better. Perhaps we should train our young people in how to learn to live with intelligent machines. To this end, education should focus on enhancing the most human characteristics of people, those that are difficult to replicate in machines. Curiosity, critical spirit, creativity and the ability to improvise. Machines are capable of analyzing millions of pieces of data and offering answers to problems posed, but who is asking the questions and defining the problems?
It is scientifically proven that the action of thinking tires, consumes a lot of energy from our body, so we have to leave much of that task to the machines and focus on what is specific to the human being.
Each one of us has a talent; the main function of education is to discover that talent and to enhance it to the maximum. This talent can be multiplied by the capabilities offered by machines. However, it is essential to take advantage of and enhance the fact that human beings are sensitive to more transcendent aspects such as beauty, truth, goodness and justice. These values, complemented by creativity, a critical spirit and curiosity, should help us to build a more humane and sustainable planet in a world full of machines.