I was an academic for 10 years. Here’s how I escaped.

This is not a “how to”. I’m an over-privileged white guy lucky enough to have researched and taught in an area that translates fairly well to industry practices. Nonetheless, this is my story. Maybe it can help you think through your own.

I never intended to be an academic.

I studied computer science as an undergrad in Brisbane. It was the late years of last century. I learned to program in Smalltalk (which no-one uses), Ada (which the US Military uses) and C (which everyone uses). Towards the end of my degree I got interested in human-computer interaction (HCI), artificial intelligence and multi-dimensional databases (together these are the design and engineering roots of any “uber-for-X” startup). My honours supervisor said to me that I was “good at this stuff” and should stick around for a PhD. I declined because I wanted to go and earn lots of money being an IT consultant.

After graduating I got a job at a Very Large Consulting Firm. It was 2001 and the dot-com bubble was bursting. There was no work. I spent ten months “on the bench”. Eventually I learned a little ABAP so I could do something. The firm, in their wisdom, decided I would best be used as a programming problem solver for consultants who were actually working on projects. I quit instead.

I ended up in Canberra and for something to do I enrolled in a PhD. (It was now the post-bubble crash so there was no work. I was lucky enough to get a scholarship for my PhD and to be newly married. My wife was working her way up the federal public service ladder so between my scholarship and her salary I was very fortunate to be able to afford to treat my PhD as a 9-5 job. I imagined I would be doing a traditional design-build-test computer science/HCI PhD. My primary supervisor was a speech recognition engineer so I made that my application focus.

As I dug into how people talk to computers it became clearer that I needed more people than engineering in my research and I picked up a sociologist as a co-supervisor. She was a Latourian, more or less, and insisted that I teach sociology of science with her so that I could understand everything that Latour, Callon, Akrich, Suchman and the rest were on about. I learned to talk to end-users of products and software and to analyse it with reference to theory and in a “grounded” way. My PhD thesis ended up being more sociology than computer science or even HCI.

Eventually it was time to get a post-PhD job and we were a bit over the cold of Canberra. A job as a research fellow came up at a university in Brisbane in a design school. The ad used synonyms for what I thought I did, so I applied. I imagine I was up against people with actual design backgrounds but I was the successful applicant.

And suddenly I was an academic. Specifically, I was a research fellow, working with industrial design researchers. I used to say to people that I had all the privileges of being a lecturer without having to actually lecture.

With a background in understanding how people talk to computers, it was natural that the first research I did in my academic job was to try to find out how to determine expertise, or the lack of it, in nurses banding people’s legs. (That’s a joke. It took me about six months of floundering about to trust that this was my job and my professor wanted me to do it my way, rather than my interpretation of her way.)

That project led to others. I was always on someone else’s “soft money” so the projects were varied. I was very fortunate that the contracts were long. My colleagues and I tried to figure out how doctors would use stethoscopes over video conference and what those stethoscopes should be like. My professor and a bunch of others won a huge grant about airports so I followed people around airports for four years and helped five other people get their PhDs in following people around airports, too.

Somewhere in there the soft money ran out. I was still on a contract so the Dean at the time decided I needed to teach to be able to pay my way. I’m organised (through sheer force of will — I’m actually an inveterate procrastinator) so I was able to cope with the management side of teaching. And I’d been tutoring since 1999 so I was fairly accustomed to being in front of a class. It was not as difficult a transition as it could have been.

After teaching for while, and still researching, I applied for what was basically my current job but in a permanent capacity. I didn’t get it (neither did anyone else who applied). When I asked why I was told I was both over experienced and under performing. And so I went full shields down.

I still had a contract. I still had undergrad teaching commitments. I still had PhD students. And I started looking to get into industry.

I had maintained contact with a bunch of people who I had tutored with during my PhD. They had become fairly senior in the user experience (UX) industry in Australia. Some of them had started a conference, UX Australia, that had become highly respected. Because I like to hang out with them, I’d presented at it a few times. Because I’d been on-stage, a lot of industry people knew me, or at least knew of me. That made it vastly easier to start looking for jobs because I could see what it was they did and find parallels in my experience so I could explain it to them.

After near enough to ten years in basically the same job my resume looked a little thin compared to industry people who switch jobs every 1-3 years. But, if I presented my experience in a skills-based way, suddenly I had people paying attention. I was getting interviews at least. I could have moved to Sydney or Melbourne and got work but my wife and I, and our kids, wanted to stay in Brisbane.

In 2015 when I was presenting at UX Australia I took some almost-finished PhD students along and was shopping them around to people I knew. I found myself waiting for a session to finish, making small talk with someone from a UX consulting firm that was fairly established in Sydney and Melbourne and had just opened a Brisbane office. I asked if they’d take me on. Remarkably, they didn’t immediately say that was ridiculous.

Eighteen months of coffee meetings and a Skype interview later, I was in my head of school’s office saying that I’d had an offer and I wanted to quit.

Universities tend to be reluctant to let lecturers go too quickly. In my case there were 80 undergrads, five tutors and a couple of research students I was responsible for. Technically I was required to give four months notice. The firm wanted me to start in two weeks. I negotiated two weeks left full time and then six weeks of part-time at both the university and the firm.

And that’s how I escaped.

White and Le Cornu’s Digital Visitors and Residents

The “digital natives” and “digital immigrants” dichotomy is decreasingly useful if not outright wrong.

White and Le Cornu’s Visitors and Residents typology (or continuum) is far better.

Visitors understand the Web as akin to an untidy garden tool shed. They have defined a goal or task and go into the shed to select an appropriate tool which they use to attain their goal. Task over, the tool is returned to the shed. It may not have been perfect for the task, but they are happy to make do so long as some progress is made.

You can be a digital native and still be a digital visitor.

Residents, on the other hand, see the Web as a place, perhaps like a park or a building in which there are clusters of friends and colleagues whom they can approach and with whom they can share information about their life and work. A proportion of their lives is actually lived out online where the distinction between online and off–line is increasingly blurred.

Can you be a digital resident and still be a digital immigrant? I think so. If being a digital resident is about community, then it doesn’t matter if you’re native or not as long as you have that community aspect.

One thing that the visitors/residents distinction lets you do is ask questions about how the users of a new website, app or “place” online will use that new thing. Are you making a tool, or are you making a community?

On treating data as a material and the resulting multiplicity

Via Justin Pickard, in a book called Imagining Classrooms by Vicki Macknight, a few interesting passages on the value of treating data as a material:

Remembering advice given in the qualitative research methods texts I had studied as an undergraduate, I made a set of file cards. Onto each, I stuck a picture drawn by a child in response to the task ‘a time you used your imagination’.

I then set about trying to make sense of these pictures, looking carefully and laying them out in piles and rows on my desk, and sometimes on my floor. In doing so, I was making patterns of similarity and difference. I was using these cards to transform a set of pictures drawn by a hundred different children, some of whom shared a classroom and others who would never meet, into categories of imagination that made sense in and as theories. I was hoping that through my actions the correct theory of what imagination is would emerge.

In fact it was theories – plural – that emerged. I could pile these cards in many ways, all of which made sense in terms of previous theoretical posi- tions and that seemed accurate in terms of classroom life. I noticed this as first one, then another, way of piling the cards made me feel discomforted. I did not wish to endorse some of these ways of piling nor the theories that they implied. I made one theory, then another. (p69-70)

But Macknight almost immediately presents this multiplicity of theory-building as problematic:

the problem with the ways I find to pile my data is not that they are bad representations of the world or of what goes on in the world. In fact, each seems correct in certain ways and is used to structure school life. However, each carries with it implications that are distasteful to me for ethical reasons. Each makes me discomforted when I think of what this would mean for particular children if applied back into classrooms as the single truth. So the problem with each way of piling my data is that as theories they would be bad interventions. They are embedded in, and would further embed in schools, a worrying politics. (p71)

By the end of the chapter, Macknight has resolved the problem with multiplicity by embracing it as a resource for thinking through how a particular phenomenon or situation emerges in practice.

Multiplicity, I have gone on to say, is not in itself a problem. Rather it is something we should think carefully about how to deal with. (p89)

Don’t be like Dick; be like Rick

The Centre for Urban Pedagogy has a great primer on social impact design. It’s the story of Dick and Rick. Dick is a bit obnoxious and thinks that he knows best how to solve a community’s problems. But he’s really out for his own self-aggrandisement.

Rick takes the time to learn from the community and helps them learn to design for themselves. Rick leaves the community in better shape than he found it, mostly by surfacing skills already in the community.

It’s really a lovely document and it’s available to download for free.

(I found out about this from Alice. Thanks, Alice!)