關(guān)于終身學(xué)習(xí)的認(rèn)知局限
By Eduardo Campanella
As new technologies continue to upend industries and take over tasks once performed by humans, workers worldwide fear for their futures. But in the labor market is not the robots themselves, but rather our own minds, with all their psychological biases and cognitive limitations.
In today's fast-changing labor market, the most in demand occupations - such as data scientists, app developers, or cloud computing specialists- did not even exist five or ten years ago. It is estimated that 65% of children entering primary school today will end up with jobs that do not yet exist.
Succeeding in such a labor market workers to be a agile lifelong learners, comfortable with continuous adaptation and willing to move across industries. If one profession becomes obsolete - a change that can happen virtually overnight - workers need to be able to shift nimbly into another.
Lifelong learning is supposed to provide the intellectual flexibility and professional adaptability needed to seize opportunities in new and dynamic sectors as they emerge, as well as the resilience to handle shocks in declining industries. Training centers, the logic goes, simply need to identify the competencies that companies will look for in the future and design courses accordingly.
Yet, in the euroxoe, only about 10% of the labor force undertook some type of formal or informal training in 2017,? and the share declined sharply with age. If lifelong learning is the key to competing in the labor market, why are people so reluctant to pursue it ?
Lifelong learning is viewed as extremely costly in terms of time, money, and effort, and the returns are regarded as highly uncertain, especially amid technological disruption. Such views Amy be reinforced by the feelings of depression and hopelessness that often arise when workers lose their jobs or face career crossroads.
Human beings experience a decline in cognitive performance relatively early in life, with fluid intellectual abilities - associated with working memory, abstract reasoning, and the processing of novel knowledge - beginning to decline around age 20. After middle age, these abilities deteriorate substantially, making the acquisition of new skills increasingly challenging. Only our crystallized congnitive abilities, related to communication and management skills, improve later in life.
This reflects centuries of evolution. In almost any society, age is associated with wisdom, experience, and growing social status. Youth was the time for learning the fundamentals of the profession that one would practice throughout adulthood. Once in that job, a worker would refine their skills as they gained experience, but they would probably not have to learn new competencies from scratch.
Today's training programs are ineffective partly because they usually target fluid intellectual ablilities. For companies, the conclusion seems to be that retraining a workforce is too challenging, so when new skills are needed, it is better to pursue alternatives like automation, offshoring, and crowdsourcing.
The assumption that workers, regardless of their age and educational background, will independently do what it takes to keep up with technological change is a fallacy that risks creating an army of unemployed. Such an approach can be expected only of the most highly educated and qualified workers - those whose jobs are usually not even at risk from automation.
This may change in the future, because younger generations are growing up with expectation of lifelong learning. But, in the meantime, policymakers should take steps to mitigate the complicated mental processes at the root of many people's professional inertia.
As we develop robots with increasingly human-like capabilities, we should take a closer look at our own. Only be learning to overcome- or at least evade- our cognitive limitations can we have long and fruitful careers in the new global economy.
