My Journey into AI Part 1



After chatting with Oli Trussell on #Episode 31 of the podcast, I was intrigued again by Artificial Intelligence, bots and the impact these could have on education. Coincidentally, I also noticed a great tweet from another former guest, Scott Hayden, about a free online course #ElementsofAI from the University of Helsinki. Not only that, but we are really looking forward to interviewing Aftab Hussain, the ILT Manager from Bolton College who iss part of a team that has won a heap of awards for their use of chatbots in education. With all this correlation, I signed up for the course Scott recommended immediately! This series of blog posts will review my experience of the course and what I am learning. I will also try and apply this learning to what it means for us as educators.


Chapter 1 was entitled 'What is AI?' which I am guessing is a great place to start! I love how it focuses on the definition of the term and how we probably need to start with what AI isn't and then to have a great philosophical debate about the implications and why the public debate around it is so 'nebulous'.


I love these two key terms and there is so much about how these can apply to the classroom. Every educator (and I refrain from using the term 'teacher' here because of how the classroom is evolving) needs to have an element of autonomy and adaptivity in their practice.

Autonomy - AI performs complex tasks without constant guidance; educators need to provide opportunities for students to learn and perform without constant guidance. This could be with the use of Google Assistants or the like for automated searches but could also be through great initiatives like C3B4ME.

Adaptivity - AI is known to learn based on experience - it remembers what your preferences are, how you behaved last time you shopped on this site and then personalises your experience accordingly. In the classroom, there are endless opportunities for having an adaptive approach: educators who allow a variety of ways to 'present' evidence and then using assessment data to inform future planning, perhaps using the pre-mortem model advocated by Gary Klein and propagated by Andy Griffith and others in teacher training.

I love how each section is completed by a little self-marking quiz (nice use there!) and the whole notion of whether something is AI or not is often not a black-white dichotomy, it has elements of grey.


I had never considered the definition of a robot either. I often didn't put AI, machine learning, data science and robotics together as they should be. This little description of a robot below is really important in terms of what the ultimate aim of AI really is: making our lives easier.


I also learned about Euler diagrams which are very similar to Venn diagrams but have a greater level of complexity and inter-relatedness. This helped me quantify some of the other important ideas relating to AI: machine learning, data science, deep learning and robotics.


My favourite part of Chapter 1 though has to be the Philosophy of AI, me being a former RS & Philosophy teacher and all. Learning about how the Turing Test (Imitation Game - the film was based on his theory) and the Chinese Room Test help us to understand intelligence and consciousness. To be able to define AI in our terms is one of the final tasks - it also then requires this answer to be peer reviewed (as you also anonymously peer-review others' comments). Here is what I came up with:

Artificial intelligence is the ability to automate processes and adapt to input data that makes workflow more efficient.

Chapter 2 awaits...but as a little finisher, here is how Google AI recently passed the AI test. If you haven't seen it, prepare to be amazed; if you have, enjoy it again!


#AI #adaptivity #autonomy #euler #deeplearning #robotics #consciousness #philosophy #Turing #Automation

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