What will AI Education Look Like in the Future?

7 min read
Skills or Professions: What AI Education Will Look Like Tomorrow

Many jobs, both in the private and public sectors, require skills that are difficult to learn at school. The usability time for using specific skills, especially those related to technology, is shortened, which causes a mismatch of skills between employees and employers. The catalogue of skills needed in the future is also changing, but the most important of them have remained unchanged for many years.

This is not only preparing young people for currently technologically fashionable professions, (programming in a specific language), but also supporting cooperation skills, cognitive flexibility and readiness for change. 

In connection with changes in the catalogue of competences and on the labor market the Career Map and Central Technology Hub organized a conference on November 18, 2019 for teachers and guidance counsellors to help understand these changes. During the conference, speakers tried to answer the following questions: 

  • How do technologies change the nature of work?
  • What are the skills of the future?
  • How can the school shape tomorrow's employees?
  • Who are the innovative companies looking to employ right now?
  • What work will your students do?
  • Is career counsellor a profession of the future?
Jerzy Bielecki during his presentation about AI in education

Sessions, workshops – what else?  

During the plenary session, Kamil Śliwowski (Central Technology Hub) presented six drivers of change and key skills needed in the workforce of the future. He also mentioned that cooperation between schools and employers, it is very important to be up to date in the field of technology and modern competences in order to avoid a mismatch of skills. 

The six drivers of change and key skills are a result of a foresight study conducted by the Institute for the Future. Their experts have chosen the following drivers of change: 

  • extreme longevity
  • rise of smart machines and systems
  • computational world
  • new media ecology
  • superstructed organizations
  • globally connected world

On this basis, the experts chose key skills needed in the workforce of the future: 

  • sense making
  • novel and adaptive thinking
  • social intelligence
  • transdisciplinarity
  • computational thinking
  • new media literacy
  • cognitive load management
  • cross cultural competency
  • design mindset
  • virtual collaboration

It is important that some of these competences are not fully independent of each other, but some are common to several drivers. For example, cognitive load management is common to the computational world, superstructed organizations and new media ecology. 

List of future work skills from 2020 Report, Institute for the Future & University of Phoenix Research Institute
Future Work Skills 2020 Report, Institute for the Future & University of Phoenix Research Institute

The speeches concerned mainly two issues, changes taking place on the labor market and challenges for vocational counsellors working with a new type of client. The other speakers gave speeches in the following order: 

The world of iGen is not simply divided into on-line and off-line and social interactions coexisting in two worlds - digital and analogue - on an equal footing. Anna Stokowska says that we should think that the iGen way of life prepares them sufficiently to become a mature, competent and digitally competent employee. The new labor market needs a multidisciplinary education to build skills for the future, including creativity and innovation.  
The classic model of “technical” education STEM (Science, Technology, Engineering, Mathematics) is now a bit out of date. For new skills and competences, which require creativity and visual thinking, this model should be completed with another component—“Arts”. In the face of frequent changes in the labor market, it’s more important to develop key competences like multilingual, digital, personal, social and learning, cultural awareness and expression competence which are very universal and could help people to quickly adapt in many situations. These skills could help people in reskilling and guarding against unemployment. 

One consequence of the described changes is the need to change the style of work of vocational counsellors. Career planning has been emphasized in the traditionally understood role of counselling. Nowadays, there is more and more talk about managing career projects. Therefore, counsellors should work with clients on a new model of competencies, which should be successfully implemented to meet the client's plan, goals and professional aspirations, e.g. openness to changes, critical thinking, design thinking etc.  
During workshops, session participants could choose two of four workshops:  

  • New ideas for a lesson with Career Map
  • Beyond the problem - elements of Solution Focused Brief Therapy (SFBT) in career counselling
  • New technologies in competence analyzing
  • Open resources in career counselling

The most interesting workshop was Solution Focused Brief Therapy, led by Anna Sowińska, which showed the background and principles of SFBT. Participants learned the basic techniques (i.e. creating questions) for use in career counselling. 
SFBT focused on achieving the client's goal, not than analyzing the problem or client deficits. SFBT’s subject of interest is not the past, but the present and future. During therapy, specialists work with the client's life history as far as his strengths, valuable experiences and ways of dealing with previous crises can be used for problem solving.  

SFBT builds the client's resources (advantages and strengths), strengthens his awareness of impact on his own life, emphasizes his value and decision-making as an equivalent partner. It helps him in finding solutions, setting and achieving goals and building motivation to achieve them. Such therapy is especially useful when working with people with low motivation or self-esteem and problems with reskilling or making decisions about which job to choose. 

AI Schools & Academy, delivered by Synerise  

I was invited for a conference to give a speech about education challenges when discussing artificial intelligence. In my presentation I had an opportunity to talk about the challenges posed by education for the development of new technologies, particularly artificial intelligence. This situation creates a need for new skills, both from teachers and pupils, such as fast learning, openness to changes, empathy, creativity, design thinking, service design, initiative and entrepreneurship.  

In my opinion, the Polish education system is not interdisciplinary enough and produces closed groups of specialists. Moreover, the use of digital technologies by students and pupils is common, but the level of ability to use them to solve problems is very low. 

I also presented the assumptions of the educational program "AI Schools & Academy" implemented by Synerise in Polish schools. This particular program was created to fill the gap of new skills on the labour market and meet the needs of society in the field of developing knowledge of young generations about artificial intelligence. The main goals of the program are: 

  • supporting for schools and teachers in conducting classes about AI
  • filling the competence gap in the field of AI in the education system
  • increasing competences of using AI by students and teachers

The program is dedicated to any type of school and divided into three levels: 

  • Enter – 3 – 10 years old, 10 hours
  • Intermediate – 10 – 13 years old, 20 hours
  • Master – 13 – 19 years old, 40 hours

The program covers the development needs of participants and the specificity of school types. The teaching concept is realised among others by following examples of learning outcomes: 

  • Enter - pupils program visually - simple situations or stories according to their own thoughts and ideas developed together with other students, individual commands, as well as their sequences controlling the object on the screen of a computer or other digital device.
  • Intermediate - in algorithmic problem solving it distinguishes basic steps: determining the problem and goal to be achieved, analysing the problem situation, developing a solution, checking the solution of the problem for sample data, saving the solution in the form of a diagram or program.
  • Master - designs and programs solutions to problems in various fields, uses: In/Out instructions, arithmetic and logical expressions, conditional instructions, iterative instructions, functions with and without parameters, tests the correctness of programs for various data.
AI schools official presentation

We strongly believe that the countries that invest today in this kind education in the field of AI will soon be at the forefront of the most developed countries in the world. Artificial intelligence is a great opportunity and if we use it well and create the proper conditions for its development, we will all gain as citizens. That is why we launched the AI Schools & Academy program.  

Summary or how bright is the future, really? 

What competencies would employers look for? What does automation really mean for the nature of work? Why should we talk about reskilling?  
Usually, conferences or seminars have a summary or collect answers to questions asked. At this conference speakers tried to answer many of the questions above. But answers are not simple and clear. Unfortunately, now we are not able to predict which qualifications or skills will be needed in the next 10, 20 years in labor market. 

In this situation, it’s more important to develop general competences like multilingual, digital, personal, social skills, cultural awareness and expression competence which are very universal and could help people to quickly adapt in many circumstances.