In the future, all companies will switch to a 12-hour work week. Thanks to the development of technology, people will no longer need five days: only three days a week will be enough, and not 8 hours, as now, but four. Computers will replace workers, for example, in jobs that require good memory and the ability to perform repetitive tasks. This assumption was made by Jack Ma - the founder and head of one of the largest Chinese corporations Alibaba, which includes the AliExpress online store.
Are we waiting for unemployment, large-scale protests and similar mass unrest? According to Mr. Ma, there is no need to be afraid of the future: artificial intelligence will help people, not deprive them of their earnings. At the same time, a successful businessman is confident that in order to achieve new goals, it is necessary to change the education system. “If we don’t change our education system, we will all have problems,” he said.
So how should it be changed? Already now we can get an answer to this question, and teachers Anton Bogomolov - Data Scientist at Tado (a German IoT startup) and Candidate of Biological Sciences Maria Lipchanskaya - Content Producer at the SkillFactory School, which trains data scientists and IT products.
Distance learning
Today, distance learning is quite capable of replacing "live" lectures by teachers. There are many examples in Russia when people of all ages master IT professions and learn foreign languages completely remotely, often without any contact with the teacher at all. In universities there is a lot that is superfluous, and much does not work optimally, but in general, lectures, tests, exams, laboratory tests and practice are needed, and they do a good job with their task: to teach people. It is too early to say that traditional lectures will disappear altogether. At the same time, distance learning is an excellent addition to live lectures, allowing the student to delve into precisely those aspects of the subject that are most interesting to him.
Unlike state universities, the SkillFactory school has the ability to very quickly rebuild programs, forms of work, course content, if in the course of work it turns out that some of the ideas did not work or were unsuccessfully implemented. The school does not have an "entry threshold" for admission to the course. Of course, if a person only knows how to type in Word and wants to take a Deep Learning course, then he will be advised to start with "Python For Data Analysis". At the same time, 100% of beginners are accepted in Python (according to statistics, there are about 30% of them in school), and with the help of additional materials, webinars, the help of the support team in Slack, they are trying to bring them to a level acceptable for studying DS.
Promotional video:
How to check knowledge?
New teaching methods imply new approaches to knowledge testing. For certification, ranging from matriculation exams to professional certification exams, tests will most likely continue to be used, because such an exam is standardized and transparent. All of this provides some protection against potential lawsuits from uncertified individuals. From more technological trends, it can be assumed that systems based on artificial intelligence will play an increasing role in verifying the results of oral and written exams, which will take into account all the details of the examination work, will not abuse power and suffer from fatigue and inattention.
For screening, for example, tests are best suited to quickly determine whether a person understands a topic as a whole. For a deeper test, you need to set tasks for a person and see how he will solve them, and for control and in order to be confident in a person's knowledge, interviews are needed. When hiring in many serious firms, all these methods are used, so the most effective way to test students' knowledge is to combine all these forms.
In SkillFactory, students are assessed automatically by the training platform: you get points for the correct answer, and you don't get a point for the wrong one. There are more complex mechanisms for assessing the correctness of decisions, for example, in the ML course, there are tasks where it is necessary to create a model and then the code embedded in the platform evaluates its effectiveness, and points are given in proportion to the obtained quality of the model. In more humanitarian courses, which require a creative approach to the solution, students are often asked to evaluate the work of fellow students, thereby students learn not only individual tools, but evaluate other works and different views, learn to give feedback and look at the issue from a different angle.
Internet: Knowledge Base or Big Cheat Sheet?
Modern people are divided into two camps: some believe "down with traditional education, now everything can be found on the Internet", others - "because of the Internet, children are stupid and do not know elementary things, down with the Internet!" However, if you approach the assessment professionally, you can highlight a very important trend: the availability of a large amount of information, which is not always of high quality, requires each person to work with large amounts of information and a good level of development of critical thinking. The development of these skills should be given special attention at all levels of education. And the Internet and the information in it is just a tool that can bring both good and harm, depending on the skill of the one who uses it. It is important to train people to manage information competently and then the Internet will be a scientific tool for them.
When to start studying professionally?
In one of the areas of developmental psychology, there is a theory of leading activities. According to this theory, in each age period a person has a predominant type of activity, due to which this person develops in many ways. Educational and professional activity dominates in adolescence (15-19 years), before that, few people seriously think about their future profession and preparation for it. If human nature does not change dramatically, most likely, the majority will continue to apply for professional education after the end of adolescence.
Already now, for children and even preschoolers, there are many offers for additional education in programming, robotics and other disciplines. Most schools (in Moscow) are focused on some specific area: biology and chemistry, legal, linguistic, technological, and so on. Although narrowly focused disciplines begin after the 9th grade, the school that has chosen a certain direction invites younger students to study certain disciplines in more depth. To become a specialist in any field, we need more and more knowledge, which pushes the age forward. On the other hand, professions are becoming more and more highly specialized, which reduces the amount of basic knowledge required.
What to learn?
The most demanded specialties in the future will be those associated with the fastest progress - this is electronics and, underlying it, solid state physics, biochemistry and genetics, as well as programming. At the same time, one of the most popular areas can be distinguished from IT specialties: data engineers, machine learning engineers and data scientists, because the amount of data in the world is growing exponentially.
In the foreseeable future, with the development of quantum computers, specialists in quantum algorithms will be in demand. By the way, you can already familiarize yourself with them on Wikipedia and be in the forefront when they “shoot”. Artificial intelligence research is likely to gain momentum, i.e., neural network architects / developers will be needed. After all, this is, in the end, what we are heading for - the creation of artificial intelligence, which is not inferior in strength to human intelligence.
The next couple of years will require big data specialists who can write programs to structure this data, because most of the data (about 80%) is unstructured data, and this share persists over time. You will also need people who support the entire infrastructure for storing and processing this data - data engineers, DevOps. Regardless of the time, creativity and creativity will remain in demand, because it is not yet possible to replace them even with artificial intelligence: without creativity you cannot create something fundamentally new, and without novelty there is no progress!
