It’s widely accepted that the process of learning requires some level of difficultly. Or, to put it another way, 100% ‘frictionless’ learning isn’t learning. Separately, the generally accepted role of technology is to help us to get more done with less effort. Bring these two principles together within education, add a solid layer of market forces and you see some strange effects. The latest one being the emergence of Cognitive Surrender, which introduces the possibility of employing AI to gain educational credit while simultaneously attenuating your ability to think. This is a problem.
We could level our critique at the designers and owners of mainstream AI. That is certainly worth doing but we should also consider the character of what we offer, our education. Arguing that ‘overuse’ of digital technology is not the proper way to learn is not going to do all the heavy lifting here. The narrative of efficiency-as-success is now so dominant that any counter must be carefully constructed to avoid appearing archaic or pro inconvenience.
The friction used to be inherent, now we must explain it
As a colleague said to me recently: “You don’t need to explain why things are difficult if there is no easier option”. When the only way to find a book is to rifle through numerous pieces of cardboard in a draw, you don’t question it, you learnt how to do it as well as possible. When writing meant getting your line of argument planned out before putting pen to paper, you didn’t think ‘writing an essay is a bit linear’, you just attempted to produce a decent first draft.
What’s important here is that the friction was built into the process. You had to be intentional, or the quality of your work would suffer and there was the ever-present risk that you’d waste a lot of time taking unconsidered routes. As digital technology has improved the efficiency of many academic and creative processes that friction has been ironed out, increasing the opportunities to be un-intentionally productive, that is, to produce work without experiencing learning.
The expert can manage this, as they have the experience and knowledge to judge where to smooth the way and where to dig in and engage. The student or novice does not yet have this ability and requires the educational process to incorporate ‘designed friction’ to ensure learning takes place.
However, because old-school frictions were not understood as useful for learning, but simply part of a system with no other choices, it means that we haven’t rehearsed how to explain the value of friction in the process of education.
The role of Critical Literacy
In my recent keynote at the KRIK conference I suggested that Critical Information Literacy and associated pedagogy is a useful counter to the risks of Cognitive Surrender. The ‘critical’ aspect focusing on verifying information through experience (or knowledge of context), testing the useability of information rather than simply gaging ‘quality’, actively questioning meaning and intent.
Mainstream AI is a model of language and language is a limited expression, or model of, experience. Therefore, mainstream AI is a model of a model. Useful but operating at a significant distance from that which it appears to profess. It requires us to imbue automated outputs with meaning through the lens of our lived experience and understanding. This process is a form of Critical Literacy.
Criticality is not instinctive, it must be taught
During my talk I complained that many universities demand that students ‘think critically’ when using AI, as if that was a skill any novice could switch on at will rather than a literacy that is developed through experience, something which should be taught. I claimed that teaching Critical Literacy is crucial in the AI era and is now on par with the importance of subject specific teaching.
I argued that the subjective nature of Arts Education means that much of our pedagogy has always been a form of Critical Literacy, as the strength of student work is assessed by the ability to account for its genesis (process) and demonstrate intention in its production. In Arts Education an element of this is specific to each piece of work and therefore connected to the lived experience of the student or group.
Outside of Arts Education, the classic essay or ‘attempt’ should also function in this manner but in a massified system the practice of defending your argument has become more of a process of arguing ‘correctly’, something which can now be automated. In my view, a lot could be learn from Arts Education in the AI era as we have held onto forms of teaching and assessment which are now relevant across the sector.
Work to be done
This is not to say that Arts Education does not need to get better at explaining its own ‘designed frictions’ or that we are not vulnerable to un-intentional production. We have a responsibility to teach relevant digital skills and equip students with critical frameworks that inform where they build friction into their practices.
For libraries, the focus of my KRIK talk, I argued that the aim is not to attempt to be as seamless as AI, as this would defeat the purpose of what the library stands for. Instead, we should celebrate and explain well designed seams and frictions, one of which is the varied expertise and insights of library staff.