A colleague recently said to me, “You just go and do your magic.” It was intended as a compliment, however it left me wondering about what it means for people to think about work as ‘magic’.
Wikipedia defines magical thinking as follows:
Magical thinking, or superstitious thinking. is the belief that unrelated events are causally connected despite the absence of any plausible causal link between them, particularly as a result of supernatural effects.
Growing up, I remember being wowed watching magicians on television. However, what interested me more were the shows that unpacked the various tricks and illusions. More than slight of hand, I was interested in the steps that made such acts possible.
I guess it is often easier to wed yourself with the mystery, rather than do the heavy lifting. This is something Cory Doctorow captures in discussion of Kirby’s film Trump, QAnon and The Return of Magic:
In a world of great crisis – pandemic, climate inequality – it’s not crazy to want to feel better. For all that magical thinkers cloak themselves in “skepticism” their beliefs are grounded in feelings. Evidence is tedious and ambiguous, emotions are quick and satisfying.
For many, technology is full of magic and wonder. However, often such perceptions are produced by our willingness to give ourselves over to the narrative. As Doctorow explains in his response to Shoshana Zuboff’s book The Age of Surveillance Capitalism:
Surveillance capitalists are like stage mentalists who claim that their extraordinary insights into human behavior let them guess the word that you wrote down and folded up in your pocket but who really use shills, hidden cameras, sleight of hand, and brute-force memorization to amaze you.
Rather than handing myself over to a world of magic and mentalists, I am more interested in trying to be more informed. For me this come by asking questions, learning with others and continuing to challenge myself. As Clive Thompson touches on in regards to coding, this often involves repetitive work done over time.
You should try to do some coding every day—at least, say, a half hour.
Why? Because this is just like learning Spanish or French: Fluency comes from constant use. To code is to speak to a computer, so you should be speaking often. Newbies often try to do big, deep dives on the weekends, but that’s too infrequent.
This repetition is not only about understanding simple processes, but also building on this to join the pieces together to how they maybe interconnected. One way of appreciating this is using the SOLO Taxonomy, a learning model that focuses on quality over quantity. It involves a progression of understanding from the task at hand to more generalised leanings.
The model consists of five levels of understanding:
- Pre-structural – The task is not attacked appropriately; the student hasn’t really understood the point and uses too simple a way of going about it.
- Uni-structural – The student’s response only focuses on one relevant aspect.
- Multi-structural – The student’s response focuses on several relevant aspects but they are treated independently and additively. Assessment of this level is primarily quantitative.
- Relational – The different aspects have become integrated into a coherent whole. This level is what is normally meant by an adequate understanding of some topic.
- Extended abstract – The previous integrated whole may be conceptualised at a higher level of abstraction and generalised to a new topic or area.
Doug Belshaw talks about levels of understanding in regards to moving from competencies to literacies.
In a similar vein to the SOLO taxonomy I believe there’s a continuum from skills through competencies to literacies. As individuals can abstract from specific contexts they become more literate. So, in the digital domain, being able to navigate a menu system when it’s presented to you — even if you haven’t come across that exact example before — is a part of digital literacy.
This is something I tried to get capture in my presentation at K-12 Digital Classroom Practice Conference a few years ago where I explored ways in which different Google Apps can be combined in different way to create a customised ongoing reporting solution. It was not just about Docs or Classroom, but about the activity of curating, creating, distributing and publishing.
John Philpin approaches this problem from a different angle. Responding to the question as to whether we should all learn to code, he suggests that appreciating how technology works is actually an important part of any business. This does not mean you need to have written all the code, but it does mean you have an awareness of how things work.
You wouldn’t think about running a business if you didn’t have the fundamental understanding of law and accounting, why would you assume that it is ok not to understand technology.
This touches on Douglas Rushkoff’s point about programming or being programmed.
Coming back to my work, I feel appreciating these pieces is not only helpful in understanding the ways in which technology is a system, but also the way strategic risks can be taken when approaching something new. In Black Swan, Nassim Nicholas Taleb talks about measured risks:
It is much more sound to take risks you can measure than to measure the risks you are taking.
For me this means taking risks based on prior learnings and experience. I may not have all the answers, but I think I am good at capturing particular problems at hand and with that drawing on past practice to come up with possible solutions. I am going to assume this is why people come to me with such diverse questions and quandaries.
I am not saying all this because I feel that I know and understand everything. However, I cannot help but feel that references to ‘magic’ are often attempts to cover up the hard work, sacrifice and opportunity that produce such moments. As always, comments welcome.
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Work and Magic – On the Wonder of Technology by Aaron Davis is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
I think you are so right David. I was recently told that what I do was magic. As I wrote, I simply believe that I have spent more time caring and trying to make sense of the particular problem at hand than somebody else. This is not necessarily a knowledge or a skill, but rather an attitude.
It really is an attitude Aaron.
Reading your post last night, I was struck by this:
That is a shift in thinking from, ‘they come to me as an expert’, to ‘I’ve demonstrated an ability to problem solve in this domain’. And so attitude matters more than skills and knowledge.
Cory Doctorow discusses the magic that is predictive policing.
Doctorow explains that all this tells the police is “how many crimes to charge the child with between now and their 21st birthday.”
I appreciate your honesty David about the effort involved in technology.
It is not about magic, more about curiosity, care and as you suggest attitude.
Clive, it feels like the ‘magic‘ of coding may well be patience and persistence?
So it would seem that human’s ‘automating’ and producing productivity gains is the future of automation? Less magic and more hard work.
I really like Dave Winer’s point about the dangers of ‘simple user interface’. I am reminded of the idea of magic and technology.
Ryan Barrett reflects upon the the potential of the blockchain and the importance of human trust.
For me, this touches on the association between technology and magic.