On Counting

Kat Jung­nick­el kindly invited me to a two day meet­ing as part of her con­tinu­ing series of Trans­mis­sions and Entan­gle­ments events. Amid­st oth­ers work­ing through new meth­ods and pro­cesses, here’s what I had to say for myself on count­ing:

What is it to count and to be coun­ted?

One way I have made sense of my work over the last 10 years at Microsoft has been to see it as a way of get­ting to grips with count­ing and in some ways com­ing to terms with being coun­ted. (more…)

Presenting Data in place”

We’re present­ing a paper at CHI this year on Ten­ison Road.

Alex S. Taylor, Siân Lind­ley, Tim Regan, Dav­id Sweeney, Vasil­is Vlachokyriakos, Lil­lie Grainger, Jes­sa Lin­gel (2015), Data-in-Place: Think­ing through the Rela­tions Between Data and Com­munity, CHI 2015.

Here’s the abstract:

We present find­ings from a year-long engage­ment with a street and its com­munity. The work explores how the pro­duc­tion and use of data is bound up with place, both in terms of phys­ic­al and social geo­graphy. We detail three strands of the pro­ject. First, we con­sider how res­id­ents have sought to cur­ate exist­ing data about the street in the form of an archive with phys­ic­al and digit­al com­pon­ents. Second, we report endeav­ours to cap­ture data about the street’s envir­on­ment, espe­cially of vehicle traf­fic. Third, we draw on the pos­sib­il­it­ies afforded by tech­no­lo­gies for polling opin­ion. We reflect on how these engage­ments have: mater­i­al­ised dis­tinct­ive rela­tions between the com­munity and their data; sur­faced flows and con­tours of data, and spa­tial, tem­por­al and social bound­ar­ies; and enacted a mul­ti­pli­city of small worlds’. We con­sider how such a con­cep­tu­al­isa­tion of data-in-place is rel­ev­ant to the design of tech­no­logy.

Published Modelling Biology – working through (in-)stabilities and frictions

Just had our paper on Com­pu­ta­tion­al Bio­logy pub­lished in the online journ­al Com­pu­ta­tion­al Cul­ture.

Alex S. Taylor, Jas­min Fish­er, Byron Cook, Sam­in Ish­tiaq and Nir Piter­man (2014) Mod­el­ling Bio­logy – work­ing through (in-)stabilities and fric­tions. Com­pu­ta­tion­al Cul­ture, 1 (4).

modelling_bio

Abstract: Com­pu­ta­tion­al bio­logy is a nas­cent field reli­ant on soft­ware cod­ing and mod­el­ling to pro­duce insights into bio­lo­gic­al phe­nom­ena. Extreme claims cast it as a field set to replace con­ven­tion­al forms of exper­i­ment­al bio­logy, see­ing soft­ware mod­el­ling as a (more con­veni­ent) proxy for bench-work in the wet-lab. In this art­icle, we deep­en and com­plic­ate the rela­tions between com­pu­ta­tion and sci­en­ti­fic ways of know­ing by dis­cuss­ing a com­pu­ta­tion­al bio­logy tool, BMA, that mod­els gene reg­u­lat­ory net­works. We detail the instabil­it­ies and fric­tions that sur­face when com­pu­ta­tion is incor­por­ated into sci­en­ti­fic prac­tice, fram­ing the ten­sions as part of knowing-in-progress—the prac­tic­al back and forth in work­ing things out. The work exem­pli­fies how soft­ware studies—and care­ful atten­tion to the mater­i­al­it­ies of computation—can shed light on the emer­ging sci­ences that rely on cod­ing and com­pu­ta­tion. Fur­ther, it puts to work a stand­point that sees com­pu­ta­tion as tightly entangled with forms of sci­en­ti­fic know­ing and doing, rather than a whole­sale replace­ment of them.

Reading Not just neoliberalism...”

Ber­man, E. P. (2014). Not Just Neo­lib­er­al­ism: Eco­nom­iz­a­tion in US Sci­ence and Tech­no­logy Poli­cy. Sci­ence, Tech­no­logy & Human Val­ues, 39(3), 397–431.

not-just-neo

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?

Published Data and life on the street

We’ve pub­lished a short com­ment­ary on the Ten­ison Road pro­ject in the new Big Data & Soci­ety journ­al. Down­load it here (open access).

data_and_life

Taylor, A. S., Lind­ley, S., Regan, T., & Sweeney, D. (2014). Data and life on the street. Big Data & Soci­ety, 1(2).

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.

on Leakiness and creepiness in app space”

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. 

Irina Shk­lovski, Scott D. Main­war­ing, Hal­la Hrund Skúladót­tir, and Höskul­dur Bor­gthorsson. 2014. Leak­i­ness and creep­i­ness in app space: per­cep­tions of pri­vacy and mobile app use. In Pro­ceed­ings of the 32nd annu­al ACM con­fer­ence on Human factors in com­put­ing sys­tems (CHI 14). ACM, New York, NY, USA, 2347–2356. 

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…)