In Which Beth Writes a Book Review For the First Time In Months!
You know there’s been a lot going on in my life the last few months (the fire, the moving as a result of the fire, the debilitating depression, the grad school, the second anniversary of John’s death, and other stuff I haven’t talked about – changes at work, progress on some writing project fronts and setbacks on others) and there are a bunch of books I read this summer and fall that are never going to get reviewed at all because I just can’t. So I’m starting again where I’m at.
Also, big change: I bought a car! I’m no longer spending two and a half hours a day on public transit! Which means no more two and a half hours a day of uninterrupted reading. I’m trying to find where to fit a good chunk of reading time back into my life, but it hasn’t been happening for the last couple of months. I finished one book in the month I bought the car. From an average of three a week, this is devastating and will not stand. So I’m fighting to carve time for reading out from other parts of my life, and it’s hard, but I know that I need it. In the next week or so I’ll also be rebooting my annual challenges and some other housekeeping.
So reviews are definitely coming back, I promise, but not at the same frequency anytime soon. But I read some really great stuff over the break that I want to talk about!
Data for the People: How to Make Our Post-Privacy Economy Work for You (2017) / Andreas Wigend
Making Sense of the Alt-Right (2017) / George Hawley
Undisciplining Knowledge: Interdisciplinarity in the Twentieth Century (2015) / Harvey Graff
Y’all, Data For the People has been on my TBR pile since I was in the Michael Stephens Hyperlinked Library class going on a year ago. I finally got to it, and I’m so glad I did.
It’s very similar in structure to Delete: laying out the hisory and context of the basic structural problem, describing how that structural problem manifests in the tools we’re increasingly dependent upon, developing some theoretical models about what could mediate the problem, and then describing specific macro-level policy and individual-level practice actions that could support the theoretical model to move toward a more egalitarian, personal agency-based model of big data.
The basic problem is that big-data-driven online services – data refineries, Wigend calls them – are predictive and prescriptive by design. They attempt to predict what you’re going to do and then manipulate you into doing it. That’s the point. That’s how they work, and they will collect all the data that makes the predictive algorithms more effective. And what works better than anything else to keep people clicking is other people. Social networking works because it feels engaging – every click, every like, every refresh feels like reaching out to maintain meaningful relationships. Of course, what’s being pushed to the top of the feed is not what’s actually most important or meaningful to you, but what keeps you clicking. It’s adaptive for interestingness, not for value, and it’s ruthless.
None of this is new information – this conversation is pervasive. But Wigend’s analysis is nuanced, thoughtful, attentive to the complexities of the problem, particularly the problems of entanglement and identifiability. The industry practices he recommends could go a long way toward both preventing data breaches and mediating the damage of them, while giving users much more agency and control.
(The recommendation that I find most interesting is “the right to experiment with the refineries” – they experiment on us, so why shouldn’t we be able to experiment on them? The algorithm is adaptive by design, so give us control over at least some of those adaptive functions. How different an experience would Facebook be if we had slider controls over, for example, how hard to promote posts from people who haven’t posted in a while? What about on the basis of how many images there are in the comments? What if those controls were right on the main page where we could adjust them at will? Push light-hearted gif-parties to the top today; push them down in favor of more substantive conversations tomorrow.
The trend, unfortunately, seems to be in the other direction. I think the angriest I have ever been at a social networking platform functionality change was when Pandora removed the “move this song to another station” function – I valued that, and losing it lessened the value of the whole service for me. It’s my content, damn it! If you want me to consume more of it, give me control over how it presents.)
But it still ultimately comes down to digital literacy. It always has, and it continues to. Users who click through an end-user license agreement without so much as glancing at it today are not going to start demanding data security audits and privacy efficiency ratings from their favorite social networking sites tomorrow. And on the flip side, in library work I see so many people just opting out because the tech intimidates them and they’d rather not participate than tackle the learning curve – and then struggle when they have no choice. (Give Gmail your damn phone number, people, seriously.) We are responsible for curating our own digital footprints, and understanding the effects of the choices we make. We must, we must accept that responsibility in order to claim the power that comes with it.
AKA “I read all those damn Daily Stormer posts so you don’t have to.” I don’t even want to review Making Sense of the Alt-Right; I just want to press it into the hands of anyone who stands still long enough for me to catch. Seriously, it’s only 217 pages; just go read it. This is the most intelligent, thoughtful, concise, useful explanation of where the alt-right came from, what alt-right actually means (it’s more complicated than “just call them Nazis, you’re enabling them by giving them a new label”), how wide-spread and influential (and competent) they actually are, what the left did wrong (and is continuing to do wrong to this day), and what we can do. I just really, really appreciate this book.
“Interdisciplinarity” and “transdisciplinarity” are words with specific meanings in a narrow context, but they’re also words that have been and are used so freely and broadly that those meanings are muddied and neutered, and that’s… really damaging. In Undisciplining Knowledge, Dr. Graff sets out to reorient that, to restore some context and specificity to the use of these words in academia (and, by extension, in industry and policy and popular culture).
What it really is, is a history of the evolution of academic disciplines – and I use the word evolution very intentionally, because central to the story is the process of differentiation, speciation, reinforcement, dominance, decline, and re-differentiation. Through six case studies, he describes the processes and challenges of breaking conceptual new ground, starting with biology and sociology in the 1890s and ending with biosciences and literary studies today.
We would never think of sociology or biology as interdisciplines today; they’re just about at the center of what we think of as established, canonical core disciplines – but of course there was a time when that wasn’t true. At the time that the idea of biology as a field of study was being invented – this was between 1890 and 1910 – botany, zoology, and medicine were pretty much completely siloed and separate from each other, and the idea of cross-training, cross-researching, and cross-theorizing between those fields to create AN EMPIRICAL UNDERSTANDING OF ALL LIFE was a genuinely new way of looking at the problem. And so was the integration of biology, chemistry, physics and eventually information science into what eventually became biosciences over the course of the next hundred years. At each stage, we expanded our definition of what we needed to understand in order to understand life, and the borderlands between the core disciplines became rich and fertile places for discovery, critique of old theoretical models, and paradigm shifts – and that’s another phrase that’s overused and misused, synonymized with “a big deal development” when what it actually means is a fundamental, epistomological change in understanding, making possible discoveries that simply were not possible before.
The same thing happened in sociology (AN EMPIRICAL UNDERSTANDING OF ALL HUMAN SOCIAL EXPERIENCE) and the humanities. And continues to happen, and will continue to happen, because it’s a continuous process. And that’s what gets forgotten in any conversation about Seriously!!New!!Ideas!! – there’s always this tension between the border territories and the center. There’s no inter/cross/trans/metadiscipline without the foundational disciplines, and eventually the interdisciplines become the disciplines and a new generation of interdisciplines develops to push back against what’s become calcified. (And the reverse. There’s some amazing, exciting, forward-thinking work being done in sociology right now that’s a direct response to critiques from breakaway disciplines). There is nothing new under the sun, and the canons have value.
Both of my programs have been interdisciplinary programs. My undergrad is in interdisciplinary liberal arts – it says so right there on the diploma! – and no one has ever conclusively pinned down where in the hell library science fits into anything (literally, it’s not even on the list), but it draws on so many fields. In my MLIS coursework, I’ve done information architecture and design, cognitive science, education, history – bringing so many different areas of study together into one integrated whole. I realize, reading Graff, that both of these programs should be more correctly described as metadisciplinary or even adisciplinary. LIS in particular just rejects the idea that siloing knowledge into disciplines is meaningful or valuable, and that’s part of what attracts me to it, but there is value in going deep into a specialty of knowledge too, even if that specialty isn’t (yet) articulated and institutionalized in a particular academic discipline.
And as I think forward to what comes after the MLIS, it occurs to me: I have no canon foundation in anything. I jumped right to the Big Ideas and never did the foundational work. Sociology 101? Never took it. Fundamentals of literary analysis whut? Composition? Nobody taught me how to write; I was busy writing. And I don’t regret that, but I do realize that if I’m going to go further, I have some remediation to do, and I need to think about what that’s going to look like. I’m thinking about Great Courses, I’m thinking about MOOCs. I have a copy of DIY MFA sitting on my bookshelf and I do intend to work through it at some point, but I think I need some undergrad-level literary analysis underpinnings too. I need to think about what I need, and how to even find out.