Jrcb4 The Impact of Artificial Intelligence on Learning final

activity—which in socio-cultural theories of learning underpins advanced forms of human 
intelligence and learning—remains beyond the current state of the AI art.  
One of the most successful application areas in AI has been video processing. There will 
be strong economic interests in using video-connected AI systems in classrooms and to 
complement the collected data with data from social media and Internet of things (IoT) 
platforms. As it becomes technically possible to monitor student emotions and attention 
in real time and use such data to help teachers and students, AI privacy and security 
become important topics also in education. Similarly, AI systems are well suited for 
collecting informal evidence of skills, experience, and competence from open data 
sources, including social media, learner portfolios, and open badges. This creates both 
ethical and regulatory challenges. 
Several high-profile econometric studies on the future of work have shown that many 
occupations can be automated with current AI technologies. These studies have relied on 
task- and skill-biased models of technical change. In this report, we argue that a data-
biased model is more appropriate for current AI systems. We also explore a similar 
methodology to see how the future of the teaching profession might look like. The results 
suggest that many currently defined high-priority teacher tasks might be automated. 
However, this is based on the assumption that the role of teachers is rather mechanical 
and purely instructional with summative assessment playing a central role, reflecting 
deep beliefs about the functions of education and the social institutions around it. In 
educational systems that emphasize development and, for example, social competences, 
formative assessment might be higher on the list. As a result, there is a risk that AI 
might be used to scale up bad pedagogical practices. If AI is the new electricity, it 
will have a broad impact in society, economy, and education, but it needs to be treated 
with care.
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Readers may also be interested in “
HUMAINT
”, an interdisciplinary JRC project aiming to understand the 
impact of machine intelligence on human behaviour, with a focus on cognitive and socio-emotional 
capabilities and decision making (see 
https://ec.europa.eu/jrc/communities/community/humaint). 

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