AI and controls
ICT networks are known to change society in several predictable ways. Rainie and Lee suggest that:
“in networked societies, boundaries are more permeable, interactions are with diverse others, connections shift between multiple networks, and hierarchies tend to be flatter and more recursive*.”
Rainie, Lee; Wellman, Barry. (2012) Networked: The New Social Operating System (The MIT Press).
In a recursive hierarchy, people have different positions in different teams: a person can lead one team and be a junior member of a second team and an observer of a third team. The hierarchies are flatter because there are fewer levels of authority and there are greater opportunities for collaboration and communication between members of the group.
School classrooms tend to have a flattened hierarchy, with a teacher at the top and the students below being of equal lower status .
AI is now a member of our network and will impact on the hierarchies, relationships and the boundaries that currently exist. So, how could AI affect and be affected by visible and invisible controls?
The artificial boundary between visible and invisible controls breaks down when considering AI.
Imagine the preparation for a lesson where a teacher is using some training prompts to train AI for the students to use.
The teacher is using the prompts to place, explicit (visible) controls on AI. This is because the prompts are making explicit demands on AI.
Within the lesson, a student using the AI is not aware of these controls, which are acting invisibly.
If these controls give the teachers the confidence to allow their students to use AI in independent study, then the controls are also acting invisibly to the student.
In these circumstances, the use of AI can become a controlled element in any lesson. The use of training prompts as controls could minimise the potential for distraction and loss of teacher authority, minimising the risk of AI producing errors or hallucinations.
OpenAI give instructions for writing good prompts with AI. These include giving AI a persona, such as “You are a teacher of English to secondary age students, specialising in Shakespeare’s play “Romeo and Juliet”.
It then suggests breaking the task into smaller steps, similar to how teachers would approach the task with a class.
Give AI a clear indication of the appropriate language and the learning outcomes, as well as how the work is to be presented.
In other words, teachers should prepare AI in the same ways that they prepare their students for the task. AI is not the replacement school teacher in the room, it is just a talented student, acting as a learning support.
AI could be used to promote learning in both traditional and progressive learning classrooms if it was prepared to a sufficient level of compliance to schools’ academic and pastoral requirements.
This is not to say that students should not be challenged to critically evaluate the answers given by AI. It is imperative that they do, in the same way that they should be challenged to critically evaluate the responses given by a search query on Google. It is much easier to do this when students have some mastery of the subject being studied, and this may impact how it is used in traditional teacher-centred classes.
| Q. “Writing good AI prompts can help teachers think about how they might approach teaching a lesson with a class.” To what extent do you agree with this statement? |
Updated 16/01/24 to include end of article question.