You cannot be serious
If you have ever seen or heard me present on AI, I will usually talk about the importance of connections. I will emphasise how much our knowledge of possibilities, of what and why things are happening in AI education come from discussions, conversations, sharing of experiments, techniques, research, use cases and examples. I benefit immensely from the hefty amount of material that comes my way. Yet, from time to time, there is that one piece that resonates, stops me in my tracks and makes me wonder far more deeply than the actual piece intends. This is one of those and it does not feature education at all. If you haven’t seen this already, click on the image below and take a couple of minutes to see the role that AI played in the Australian Open in 2024:
Next-Level Elite
First off, this got me thinking about what it is going to mean in this sport to be elite. It could be argued from a negative stand point, that this technology is directing tennis towards sterility. It becomes too predictable, a sport where at the elite level, every player’s moves, shots, actions and reactions are known, therefore winning requires near-perfect execution of a formula. Others would argue that for a long time, big money sports have been using data analysis to do similar; AI just adds another layer of sophistication. I believe, to a point, such finite and thorough analysis, modelling and accuracy in predictions mean that the players take elite play to the next level. Surely, all of this means that they are developing in more targeted ways, training and upskilling with less of a haphazard approach. That can only be a good thing in terms of raising standards.
However, I am of the opinion that the above description of next-level elite only works to a point. At some stage players have to and will do things differently, to beat the system. They will recognise and know that formulas are being applied and that in order to not be predictable, they have to alter their game with shots and movement that is…you guessed it…unpredictable. Of course their unpredictability will also become part of the data training set that gets fed back to the model so that in itself has to be further considered in wider development by these players and coaches. Surely diversity in decisions made, lessens probability in this case so developing a greater range of shots and movements, some of which are ‘abnormal’, will be vital. I would argue that creativity is going to be crucial in winning at the highest level in AI enhanced tennis.
I appreciate, though, that there are people who love tennis, who spend good money watching it and are of the opinion that this is not what they want the sport to be. In my favourite sport, football (the round ball version), teams like Man City are facing criticism for very much the same thing, being too formulaic, almost too perfect that games they play in become too predictable. And, don’t think for a minute that the level of data analysis is any less or the growing use of AI is any less in the Premier League. This raises questions of values:
How much involvement do we want from intrusive technologies such as AI?
As we see in Formula 1 racing, do their need to be rules enforced so that technology advancements do not guarantee victory and driver skill is still essential?
Applying all this to education, for example, students in high schools, the same developments are easy to foresee and similar discussions can be had. Data analytics is currently being developed in various schools around the world that can enable forecasts to be made about student future achievements and pathways. The same data can be used for intervention work. Using AI, will enable larger data sets to be analysed, greater accuracy to occur. Hence, if we look at such work in schools in the same way as the tennis scenario, the following should occur:
Achievement standards in students should improve. Although, what measures we use is far more debatable than how many grand slams a player wins, so let’s be careful here.
Creativity will be vital for students who want to forge their own pathways, go beyond data/AI predictions that highlight less than attractive outcomes for students. It could also be argued that creativity will be vital in provision and offerings that schools provide. If students are to change their destiny, this may require rethinking in terms of what is on offer to enable students.
Values will be front and centre in decisions about education that young people are entered into. Those decisions usually come from parents in respect of school age children but at some point, usually teenage years, students drive that agenda, also. To my mind, this will create diversity in education offerings with more choice as to what kind of education is demanded. Be it local, national, international, offline, online, technology-free, technology-enhanced, AI-free, AI-enhanced….the melting pot will get significantly bigger with more ingredients.
The Simple Model Approach
The other stream of thought this video set off for me was around the fact that relatively speaking, tennis is not very complex and how much does that enable AI to influence the game. If we look at a team game, there is of course, more than one player on the field. In tennis singles, there is only one on each side. Therefore, the amount of possibilities of where the player can move to, the shots that a person can play are much less than, for example, rugby. It is also a game where hitting the ball with a racquet is required. If we go back to football aka soccer, the ball can be hit with various parts of the body, by eleven different players on each side and then one of the players of that eleven, the goalkeeper is different. This is far more problematic in terms of predicting what will happen. Lastly, the rules in tennis are not overly complex. As far as I know there is no offside rule in tennis and if you want something to figure out, then try the short pass rule in netball. Given all this, we have a scenario with tennis that enables to be developed with relative ease.
Applying that to education, I wonder whether we are approaching the use of data and AI in the wrong way. I am not talking about GAI in the guise of chatbots, image generators and the like, being used by teachers and students. I am referring more to the aforementioned developments in using data to track, forecast, enable interventions. I appreciate that large pools of data are needed to enable accurate modelling but in the experimentation and application of this, would it not make more sense to focus on an individual or a few individuals, at least to begin with? Surely this would be mimicking the simple model approach that tennis shows us. Of course, unlike in tennis, there is a requirement to scale the use of AI to enable a large amount or all students to be provided the same opportunities but, at least, in the early instances, creating simpler test cases can make it more manageable.
Conclusion
These are my ‘thought trains’ after watching that video. You may have different ones. I hope you do. Let’s just say that this video is further proof of AI’s influence in our lives right now, AI’s continued developments and increasing power/accuracy. It also highlights that values, what we actually want is front and centre. To all of this, my answer is, “rightly so”!
