Jrcb4 The Impact of Artificial Intelligence on Learning final

Executive summary 
At the November 2017 Gothenburg Summit, the Commission presented the 
Communication 'Strengthening European Identity through Education and Culture', that 
set out a vision for a European Education Area and announced a dedicated Digital 
Education Action Plan
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, which aims to foster digital skills and competences for all citizens. 
The Action Plan focuses on implementation and the need to stimulate, support and scale 
up purposeful use of digital and innovative education practices. It has three priorities: 
making better use of digital technology for teaching and learning; developing relevant 
digital competences and skills for the digital transformation; and improving education 
through better data analysis and foresight. Artificial Intelligence (AI) will have an impact 
on all these, and in the last priority the Communication specifically invites to explore its 
impact in education and training through pilots. This policy foresight report suggests 
that in the next years AI will change learning, teaching, and education. The 
speed of technological change will be very fast, and it will create high pressure to 
transform educational practices, institutions, and policies. It is therefore important to 
understand the potential impact of AI on learning, teaching, and education, as well as on 
policy development.
AI is currently high on the political agendas around the world. Several EU Member States 
have declared it as a political priority. Influential studies now suggest that perhaps one in 
two occupations in the industrialized countries is likely to become automated using 
already existing AI technologies. Policy makers at the European Parliament have 
highlighted the importance of the issue, and the European Commission, in its 2018 
annual work programme, sets its wish to make the most of AI, which will increasingly 
play a role in our economies and societies
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. AI is now often called “the next 
electricity.” The transformative impact of general purpose technologies, like AI, 
however, becomes visible only gradually, when societies and economies reinvent 
themselves as users of new technologies. Technological change brings social and cultural 
change that is reflected in lifestyles, norms, policies, social institutions, skills, and the 
content and forms of education. 
Wide availability of cheap processing power and vast amounts of data in recent years 
have enabled impressive breakthroughs in machine learning and created extraordinary 
commercial and research interest in artificial neural networks, i.e. computational models 
based on the structure and functions of biological neural networks. Neural AI, and 
machine learning methods associated with it, are now used for real-time language 
processing and translation, image analysis, driverless cars and autonomous vehicles, 
automated customer service, fraud detection, process control, synthetic art, service 
robots, and in many other applications. Although some of this excitement may be