AI or not to AI: Insights from WEF Report

I finished reading this insight report from World Economic Forum on AI and education. It talks about solutions for the education system using AI.

What I liked in the report

? The focus on the need for teachers and bringing attention to the teacher shortage that needs to be addressed. No amount of AI integration is going to replace the critical role that teachers need to play in the teaching learning process.

From the report: "By freeing educators from routine tasks, AI empowers them to focus on building relationships, understanding individual student needs and fostering motivation. This synergy not only improves teaching effectiveness but also underscores the indispensable human element in education."

? The Education 4.0 framework for designing learning experiences and systems. Image inserted for the framework.

? I liked the case studies in the report which show instances of how AI is being used across different contexts for different purposes - developing literacy to career exploration to virtual mentoring to responsible use of AI for creating solutions. What caught my attention was how the different initiatives have articulated their success metrics and the framing is done as 'expected impact' and not as impact already seen. Most of the initiatives are still in the testing phase so the jury is still out on solutions based on AI.

?? Ponder points ??

Teaching as future of work

The section on teacher shortage in the report also mentioned how teaching is going to be one of the jobs in the future. It made me think how we need to have more conversations to position teaching as 'future of work'. As a sector we need to have more informed conversations and apply the future thinking thought process to imagine the future of teaching as a profession. Based on that imagination we need to backcast to what we need to start doing today.

Making AI inclusive - who is responsible for that?

While AI might have a lot of potential when it comes to personalising learning, most of the data AI solutions are working on is in English. It made me think of the kind of collaborations we need to make AI more inclusive - if a student in Odia has to use AI for learning better, then how do we enable that - to make sure they can give prompts in their local language, to make sure that references come in which are relevant to their context - what kind of LLMs need to be built to enable this? Who will build these? If anyone is working on this already, would love to know more.

Let's take time to learn and build together

Given all the case studies are still in the testing phase, maybe as the education sector we need to acknowledge that we need time to test the potential for AI for learning solutions. Given the attraction that is there for 'scalable' solutions which lead to impact - there is a need to invest time and resources to test models. We should be okay with that as investors and as practitioners. Acknowledge that we don't know enough, that there might be potential and that we need time to figure this out.

The tendency is also for us as organisations to want to have the 'first movers advantage'. If there is a way for us to overcome this and truly collaborate to build solutions using AI rather than all of us trying something in a piecemeal fashion maybe we might be able to do much more. There are initiatives under Project Tech4Dev which are attempting this. We need more such initiatives to problem solve and build relevant solutions together.

Link to the report: https://www3.weforum.org/docs/WEF_Shaping_the_Future_of_Learning_2024.pdf