EU report on the impact of AI on Learning Teaching and Education #AI #education #EU #policy

The resently published report on the impact of artificial intelligence (AI) on learning, teaching and education gives a great outline on the realities of AI, the state of the art, and the challenges as well as opportunities for those of us with an expertise in learning in general, or learning in terms of learning theory. The report is part of the JRC Science for Policy documents, and it is very well written by Ilkka Tuomi (who is renowned for his expertise in Internet, data, AI and computer science). Ilkka recorded a brief overview of the report, which can be seen below. In the report-related video, he refers to current machine learning systems as datavors, he defines (and right fully so) the term of machine learning as an oxymoron and he puts current AI in very accessible parallel, namely the Artificial Instict (as current AI is mainly about behaviourist approaches and patterns).

A very interesting perspective is that Ilkka and the report stress the importance of having someone on board of AI for learning/teaching/education on board, who has expertise in learning and learning theory.

The policy challenges mentioned at the end of the report are:

• A continuous dialogue on the appropriate and responsible uses of AI in education is therefore needed.
• In the domain of educational policy, it is important for educators and policymakers to understand AI in the broader context of the future of learning. As AI will be used to automate productive processes, we may need to reinvent current educational institutions.
• In general, the balance may thus shift from the instrumental role of education towards its more developmental role.
• A general policy challenge, thus, is to increase among educators and policymakers awareness of AI technologies and their potential impact.
• Learning sciences could have much to offer to research on AI, and such mutual interaction would enable better understanding about how to use AI for learning and in educational settings, as well as in other domains of application.
• As there may be fundamental theoretical and practical limits in designing AI systems that can explain their behaviour and decisions, it is important to keep humans in the decision-making loop.
• The ethics of AI is a generic challenge, but it has specific relevance for educational policies.
• Human agency means that we can make choices about future acts, and thus become responsible for them.  AI can also limit the domain where humans can express their agency.
• An important policy challenge is how such large datasets that are needed for the development and use of AI-based systems could be made more widely available.

This 47 page report offers the following topics:

Introduction ...................................................................................................... 5
2 What is Artificial Intelligence? ............................................................................. 7
2.1 A three-level model of action for analysing AI and its impact ............................. 7
2.2 Three types of AI ....................................................................................... 10
2.2.1 Data-based neural AI ......................................................................... 10
2.2.2 Logic- and knowledge-based AI ........................................................... 12
2.3 Recent and future developments in AI .......................................................... 13
2.3.1 Models of learning in data-based AI ..................................................... 15
2.3.2 Towards the future............................................................................. 16
2.4 AI impact on skill and competence demand ................................................... 17
2.4.1 Skills in economic studies of AI impact ................................................. 18
2.4.2 Skill-biased and task-biased models of technology impact ....................... 20
2.4.3 AI capabilities and task substitution in the three-level model ................... 21
2.4.4 Trends and transitions ........................................................................ 22
2.4.5 Neural AI as data-biased technological change ...................................... 23
2.4.6 Education as a creator of capability platforms ........................................ 23
2.4.7 Direct AI impact on advanced digital skills demand ................................ 25
3 Impact on learning, teaching, and education ....................................................... 27
3.1 Current developments ................................................................................ 27
3.1.1 “No AI without UI” ............................................................................. 28
3.2 The impact of AI on learning ....................................................................... 28
3.2.1 Impact on cognitive development ........................................................ 30
3.3 The impact of AI on teaching ....................................................................... 31
3.3.1 AI-generated student models and new pedagogical opportunities............. 31
3.3.2 The need for future-oriented vision regarding AI .................................... 32
3.4 Re-thinking the role of education in society ................................................... 32
4 Policy challenges ............................................................................................. 34

Below is the 20 minute video of Ilkka Tuomi which explains the report in easy terms.