Berman, E. P. (2014). Not Just Neoliberalism: Economization in US Science and Technology Policy. Science, Technology & Human Values, 39(3), 397 – 431.
The title of this paper says it all really. It’s good though to have a cogent argument about the relations between ideology, policy and the changes in how science is being done. I for one very easily slip into an accusatory refrain when talking about and usually criticising what I’ve seen to be the neoliberal (non)interventionist and policy direction in education and science. Elizabeth Berman presents a much more measured position and convinces me that it’s better understood as an economization, as she calls it, where the broader shift is towards prioritising scientific research and innovation vis-a-vis the economy and specifically seeing them as economic inputs. This recognises the tensions and complications and the competing interests that have run through the changing status of the sciences (in the US, but similarly, I think, in the UK).
Something I think Berman leaves open is the relationship between science and innovation. She makes it clear that science and innovation become inexorably linked when science is seen in economic terms. I want, though, to better understand the nexus. Indeed, but conflating science and technology (“S&T” as Berman refers to it), I think there are further complications here that need unraveling, ones pointing to the entanglements of science and technology, and where progress or innovation sits between (or around) them. Can we talk of technology without innovation? If S&T are two-parts of a unit, how can we disentangle innovation?
Abstract: What does the abundance of data and proliferation of data-making methods mean for the ordinary person, the person on the street? And, what could they come to mean? In this paper, we present an overview of a year-long project to examine just such questions and complicate, in some ways, what it is to ask them. The project is a collective exercise in which we – a mixture of social scientists, designers and makers – and those living and working on one street in Cambridge (UK), Tenison Road, are working to think through how data might be materialised and come to matter. The project aims to better understand the specificities and contingencies that arise when data is produced and used in place. Mid-way through the project, we use this commentary to give some background to the work and detail one or two of the troubles we have encountered in putting locally relevant data to work. We also touch on a methodological standpoint we are working our way into and through, one that we hope complicates the separations between subject and object in data-making and opens up possibilities for a generative refiguring of the manifold relations.
I recently had an email exchange with Irina Shklovski in which she kindly sent me the paper she presented at the CHI conference this year. It’s a great paper, with some carefully thought through insights into the data we produce and (often inadvertently) share when using smart phones.
The paper got me thinking about some broader (and long-standing) issues I’ve been working through myself related to the researcher’s agential (and often inadvertent) role in empirical research. What follows are some slightly amended comments I’ve shared with Irina. (more…)
Wasn’t expecting the digression into spirits and performance art, but I do like Thrift’s continual efforts to write about expansive human/agent capacities and extending the .
...the claim is being made that, as computational objects have developed, cities are able to take on new forms of vitality (Stern, 2010), forms of vitality which can develop over time. Perhaps one way in which we might consider this ques- tion is precisely through looking at how vitality devel- ops when computational things are explicitly included in the contours of experience. Then it becomes clear that it has only gradually arisen, line by line, algorithm by algorithm, program by program.
Really helpful paper from Matthew Wilson on the interminglings of data and geography. Although more concentrated on a particular aspect of community life (namely reporting problems or damage to local facilities etc.), the paper has some strong relevances for the Tenison Road project. Especially useful are Wilson’s thoughts on mattering in relation to feminist technoscience and of course
Wilson cites: Haraway D J, 1991 Simians, Cyborgs, and Women: The Reinvention of Nature (Routledge, New York)
Haraway D J, 1999, “Knowledges and the question of alliances”, in Knowledges and the Question of Alliances: A Conversation with Nancy Hartsock, Donna Haraway, and David Harvey (Kane Hall, University of Washington, Seattle, WA)
After a tremendous about of work with Lara Houston, I’m delighted to have finally gone live with our data policy site: data-policy.info. It attempts to detail, in various formats and cuts, the discussions at the day of dialogues on data, policy and civic life, held at Microsoft Research Cambridge. More than this though, we want the site to promote further discussion and expand the ways we might think of the relations between data, social/civic life, and policy. For me, the inspiration here has been the work a few of us have been doing with Tenison Road in cambridge and a community’s efforts to make sense of and use its data. I’d like to think something small and local could make a difference in these big discussions
Next Tuesday a few of us at Microsoft Research are hosting a day-long dialogue to discuss the interminglings of data and social/civic life. We’re bringing together a mix of social theorists, commentators and policy advisers with the hope of drawing out possibilities for doing policy making (as well as technology design) differently. Our preamble for the event follows (a printable PDF can be downloaded here): (more…)
A few of us working at the intersection of data, civicmedia and citizenship are taking a look at this article by AbdouMaliq Simone. Some rambling comments follow:
First, just a short point about style: I’m delighted to see Simone’s unapologetic use of rich descriptions of Jo’berg’s streets. They are in striking contrast to what I see to be the standard ethnographic account in HCI papers. What I find tedious is the usual preamble in HCI works — explaining method — and then the use of participants’ quotes as a kind of ‘proof’ of particular points. Also, both point to a curious idea of what it means to demonstrate evidence or proof. Simone bothers with none of this. He gets straight to the stories, to the rich descriptions of inner city Jo’berg and its underbelly. (more…)
Stories about big data are everywhere. We’re being told how significant the impact of big data will be on our lives by all kinds of people in the know. And yet I’ve been grappling with what (big) data might really mean to people who aren’t fully signed up members of the digerati, those shapers, makers and moders of technological futures. I’ve pondered, in short, on two simple questions: how does data matter to ‘people on the street’, and how might they want it to matter. In this talk, I’ll reflect on a project we’ve been building up at Microsoft Research to begin working through these questions. I want to discuss our efforts to ground a technological imaginary in ordinary life or, to put it another way, to enable a productive re-imagining of ‘big data futures’ — to coin a phrase — from ‘the street’. I’ll describe how we’ve taken this challenge quite literally. Just over three weeks ago we began working with one street in Cambridge, Tenison Road. For at least a year, we plan to think through what data means for the Tenison Road community and in some cases to enable ways for the community to intervene in the future imaginaries. Although this won’t be a talk or for that matter a project about austerity, I certainly think it is one in which austerity and its repercussions will come to matter. My aim, then, will be to reflect on how this is a project concerned with futures, futures that are heavily concentrated in the minds of the technological elite, but also some that are more pedestrian that might just offer alternative possibilities for what (big) data could mean and what we might do with it.