“Legal and policy solutions focus too much on the problems under the Orwellian metaphor — those of surveillance — and aren’t adequately addressing the Kafkaesque problems — those of information processing” p.26
Solove’s point here is that much of the legal wranglings and policy making surrounding privacy are based on the premise that people have something to hide. Thus the aims have, by and large, been tied to securing protections against surveillance — operating within the rubric of an “Orwellian metaphor”.
The broader argument Solove makes is that this treatment of privacy is missing the proverbial trick. As a concept, privacy doesn’t simply entail people wanting to hide things. For starters, according to Solove, “[m]any people don’t care about concealing the hotels they stay at, the cars they own, or the kind of beverages they drink.” p.25 “[M]uch of the data gathered in computer databases isn’t particularly sensitive, such as one’s race, birth date, gender, address, or marital status.” P.25
It isn’t so much the gathering of information that matters, Solove contends. It’s what agencies like governments are doing with it — the “information processing” — that counts. The allusion is to a Kafkaesque world in which the relations between agencies and individuals are managed and controlled through the analysis of information or data. The power, so to speak, is held by those who can both access the data and subject it to sophisticated analysis. I take this use of information processing to be analogous to big data analytics and certainly most of the examples Solve refers to support this.
I don’t know what Solove’s sources are for suggesting “most people” don’t care about the content of the information being gathered about them (this recent Guardian article appears to confirm this). I do get his broader point though. Certainly, it’s limiting to see privacy as exclusively based on the premise that people have something to hide. Moreover, the possibilities big data analytics open up for discovering some pretty personal things about people do seem daunting, if perhaps over-hyped.
Yet, without wanting to discount Solove’s argument, I want to propose a different way of thinking about this issue of information processing. Seen from the ground up, we might also start to ask what people themselves want to say through their data and using analytics. When Solove writes about “most people” I think we need to begin thinking about what this actual means and if there are ways of making claims like this actionable. So, a counter to the “nothing to hide argument” could be that most people — given the knowledge and tools — have “something to say”. That is they may want to have some say over how their information is distributed, aggregated, analysed and interpreted and, ultimately, how it is productively put to work. This certainly won’t solve the multiple problems surrounding privacy, but it may at least redistribute the power and, in the process, give people some new ways of expressing themselves.
Oh, and as it happens, this question of how to enable people to have some sort of say and control over what gets done with their information is one of the motivations for the new project we’re ramping up in my group at Microsoft Research.
* A thank you to Jessa Lingel for pointing me to the first quote above from Solove.
Finally posted some flyers to announce the launch of the big data project we’ll run for a year. We hope to work with the residents and proprietors on Tenison Road in Cambridge to better understand how big data matters and what people on the street want it to be. This is a project that is aiming to get at the interminglings of data and locality, and to intervene in the entanglements in productive ways. That’s the hope! ... Fingers crossed.
Some significant changes to the UK’s Freedom of Information Act were enacted yesterday that give people to right to request and, critically, reuse data. It’s probably easy to overlook the implications of this. The way I see it, everyone (including commercial bodies) now have the right to access FoI regulated data and (re-)use it for analysis, analytics, building apps, etc. Whether that’s good or bad, it seems pretty profound to me. See a summary of the changes here on the Information Commissioner’s Officeblog.
A brilliant CHI paper by Steven Jackson and Sarah Barbrow. How many papers presented at CHI cite St. Augustine of Hippo and, to boot, succeed in drawing out relevant reflections on scientific modelling tools in ecology. Seeing ecology through the lens of both infrastructure and the ‘vocational calling’ provides a productive view onto what ecologists do and how their practices are changing. Jackson and Barbrow illustrate this nicely by writing of the changing notion of ‘the field’ for ecologists. I see a strong parallel here between ecology and biology. Biology is a field very much in transition and the changes have much to do with the material encounters in biological work — with for example the changing nature of biologists’ work at ‘the bench’ and with experimental apparatus. The turn to machines, computation and algorithms is not only reshaping the practices but also refiguring what biologists know and how they see their phenomena (something we also tried to get across in At the interface of biology and computation at CHI). A similar conclusion is being drawn out in this papers as it captures the entangled relations between the tools, practices and ways of knowing in ecology.
The phrase “always already” is, in the main, attributed to the poststructuralist philosopher Jaques Derrida. It has, however, come to be a trope for the new materialists and it is in this usage that I modestly take it on. Specifically, my guiding sources are from the feminist technoscience scholars Donna Haraway and Karen Barad, both of whom make heavy use of the phrase to trouble the binaries abound in science and technology (subject-object, mind-matter, inside-outside, past-present, etc.).