Tag Archives: big data

Where can tell me who I am?

In September I published a few musings on the topic “Where can tell me who I am.” This was preliminary for a talk at this year’s SEDAAG meetings. Here’s a link to the talk as delivered and the slides I used are here.

Where can tell me who I am (pdf)

Our @TheAAG panel on Algorithmic Governance, San Fran

A panel session at the Association of American Geographers Annual Conference, San Francisco, March/April 2016. Organized by Andrea Miller (UC Davis) and Jeremy Crampton (Kentucky).

With Louise Amoore (Durham), Emily Kaufman (Kentucky), Kate Crawford (Microsoft/MIT/NYU), Agnieszka Leszczynski (Auckland), Andrea Miller (UC Davis), Ian Shaw (Glasgow).

“It’s time for government to enter the age of big data. Algorithmic regulation is an idea whose time has come.” Tim O’Reilly.

This panel will address the increasing concern and interest in what we here label “algorithmic governance.” Drawing on Foucault’s governmentality and Deleuzian assemblage theory, as well as the nascent field of critical Big Data studies, we are interested in investigating the manifold ways that algorithms and code/space enable practices of governance that ascribes risk, suspicion and positive value in geographic contexts.

This value often takes the form of money. For instance, Facebook’s average revenue per user (ARPU) in Q2 2015 was $2.76 globally and as much as $9.30 in North America, while, according to Apple, there are over 680,000 apps using location on iOS. However, pecuniary value derived from spatial Big Data must also be understood as inseparable from capacities of risk and suspicion simultaneously generated and distributed through data-driven relationships. More generally, the purpose of these data is two-fold. On the one hand, they allow risk and threats to be managed, and on the other hand, by drawing on these new subjectivities, they increasingly generate new modes of prediction and control. Thus, algorithmic life can be understood as “data + control,” or to use a Foucauldian term, “data + conduct of conduct,” or what we can call “algorithmic governance.”

Following Rob Kitchin’s suggestion that algorithms can be investigated across a range of valences—including examining code, doing ethnographies of coding teams or geolocational app-makers, and exploring algorithms’ socio-technological material assemblages (Kitchin, 2014), we convene this panel to explore some of the following questions in a spatial or geolocational register:

  • How can we best pay attention to the spaces of governance where algorithms operate, and are contested?
  • What are the spatial dimensions of the data-driven subject? How do modes of algorithmic modulation and control impact understandings of categories such as race and gender and delimit the spatial possibilities of what Jasbir Puar has called the body’s “capacity” for emergence, affectivity, and movement (Puar, 2009)?
  • Are algorithms deterministic, or are there spaces of contestation or counter-algorithms?
  • How does algorithmic governance inflect and augment practices of policing and militarization?
  • What are the most productive theoretical tools available for studying algorithmic data, and can we speak across the disciplines?
  • How are visualizations such as maps implicated by or for algorithms?
  • Is there a genealogy of algorithms that can be traced prior to current forms of technology (to a more “proto-GIS” era for example)? How does this tie with other histories of computation?


Kitchin, R. 2014. “Thinking Critically About and Researching Algorithms.” Programmable City Working Paper 5. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515786

O’Reilly, T. 2013. “Open Data and Algorithmic Regulation.” In B. Goldstein and L. Dyson (Eds)., Beyond Transparency. San Francisco: Code for America Press. http://beyondtransparency.org/chapters/part-5/open-data-and-algorithmic-regulation/

Puar, Jasbir. 2009. “Prognosis Time: Towards a Geopolitics of Affect, Debility and Capacity.” Women and Performance, 19.2: 161-172.

Where can tell me who I am

If in the past we could find ourselves if lost, or in a strange location, by asking of those nearby directly or indirectly (eg through social media apps) “who can tell me where I am?” then the condition now is “where can tell me who I am.”

The algorithms that parse and analyze our data shadows to control our horizon of possibilities now depend increasingly on spatial Big Data. As Dan Bouk points out in his recent history of data, the point here is not just to know; to track and to surveill where people go. Additionally algorithms are calculating machines–machinic assemblages–and what they calculate is value, derived not from you, but from your identity as given in the data.

First we are separated from our data in multiple ways, fractionated, scattered (Williams, 2005). “Separated” because we are in an asymmetrical relationship to our data; we do not have the same access to it that algorithms have. Nor the same rights: we are not “customers” of Facebook, but “users.” We do not engage in a point of sale (POS) but rather are the commodities ourselves.

Second as with identity theft what matters is not what you have done, but what your data say you have done. (I’ve received calls from credit collection agencies about “my” spending, and had credit cards charged for visits to hotels I’ve never been to.) These data are then reassembled as dividuals, as Deleuze pointed out some time ago.

Problems with the above: (A) it appears to usher back in an originary individual from whom all else (or at least all data) springs. (B) Talk of rights is suspect:

Do not demand of politics that it restore the “rights” of the individual, as philosophy has defined them. The individual is the product of power. What is needed is to “de-individualize ” by means of multiplication and displacement, diverse combinations. The group must not be the organic bond uniting hierarchized individuals , but a constant generator of de-individualization.
Foucault, Preface to Anti-Oedipus

But that “originary” individual can be multiple too, and in relations of power. The insight of the dividual is that it is a derivative that gets traded down the line (Amoore). Its value is purely notional and can undergo crisis, whence the possibility of counter-memory. The assemblage/desiring-machine is not mechanical (it doesn’t “work” in that sense). But there are “regimes of veridiction” that constitute it and as Foucault points out the market is one such site (Foucault, 17 Jan 1979). So our task might consist in part of elucidating the market that is the site for the intersection of value, spatial Big Data, and the spatial algorithm.

[First thoughts toward an intro for Spatial Big Data and Everyday Life for Big Data & Society]

AAG 2015 Chicago recap and talks I saw


I talked about some of the sights I saw during last week’s AAG conference in Chicago in an earlier post but here I just want to mention some of the fantastic talks I attended. Quality was very high this year, and not without some controversy.

There were plenty of choices–I’ve heard there were 97 concurrent sessions. So 97 people giving papers at any one time! This is clearly ridiculous. The conference is 5 days long, papers start at 8am and go past 7pm every day. There’s also a full day of papers on the last Saturday, which everybody also complains about (it’s the day most people do their sightseeing, so sessions are lightly attended). An obvious solution to that problem is to have the conference M-F instead of T-Sat.

As for the number of sessions this is a result of the AAG policy of accepting every paper. While on the one hand there are justifications for this (geography attendees include people from government and industry who can only get funding to come if their paper is accepted, plus the origins of the AAG as an old boys’ club in the pre-war era when you could only join at the invitation of a current member), quite frankly now the system is breaking down. I would gladly look at 7 or so 250-word abstracts if it meant a less overwhelming conference. (Or, since papers are in organized sessions, do what the IBG/RGS does and give out “tokens” that specialty groups can distribute, up to a certain limit.) There are arguments for both sides of this issue, but 10,000 or so attendees is very challenging.

I began the week at a Symposium organized by Caroline Rendon, Curt Winkle and Rachel Weber of University of Illinois Chicago on urban Big Data called “The Crowd, the Cloud, and Urban Governance.” This was structured as three keynotes by Bronwen Morgan (U New South South Wales, Aus.), Matthew Zook (UKY) and Agnieszka Leszczynski (Birmingham) with responses, including one from Taylor Shelton (Clark). These were all uniformly good with plenty to reflect on.

The AAG proper then got going on Tuesday with a session on Smart Cities, including a good talk by Michael Carter (Queens) who argued that the smart city is basically the surveillant city. Perhaps nothing too new there but he tied it in with neoliberalism for a perspective no doubt not often encountered at smart city promotional events.

Wednesday I had a more mixed experience at the Critical GIS themed sessions. Unfortunately I missed the first session, but Luke Bergman (U Wash.) offered a very challenging talk on formalizing the Goodchild et al., 2007 paper on the geo-atom with some thoughts on what he called a “geo-interpretation.” This was a little over my head but perhaps provides a vocabulary for accounting for individuals as well as representing space. It got me thinking about calculation in GIS again (space is that which is subject to calculability).

That afternoon I was on three panels back-to-back. No doubt the most memorable will be the “Robots” panel organized by Vinny del Casino and Lily House-Peters (Ariz.). All the papers were very good; as well as the ones by Vinny and Lily my colleague Matt Wilson spoke (drawing on Haraway’s cyborg work), and Heidi Nast (DePaul, who gave a version of her work on love dolls and sexbots). If you’ve seen Heidi speak you know it is usually a fascinating tour de force and this was no different, especially some of the material she’d dug up. I was sat right in front of the screen and every time I looked back over my shoulder were pictures of female topless love dolls. I swear in one video clip she showed that the doll was producing sake out of one breast while a man palpated the other!

Another panel was one I’d co-organized with Agnieszka called “Where’s the Value? Emerging Digital Economies of Geolocation” which featured presentations by Elvin Wyly (UBC, who’d also been at the UIC workshop on Monday), Rob Kitchin (Maynooth), Agnieszka, and Julie Cupples (Edinburgh). All of these were excellent, and I’ve placed an audio recording of it online here:

Where’s the Value (link to audio).

The last session was the paper I’ve been working on with Sue Roberts (UKY) on “Drone Economies.” I feel this paper is finally getting into the shape of what we want to say now. Here are the slides:

The other paper I really enjoyed in that session was by Caren Kaplan (UC Davis) who spoke on air power at home–a very good history of air power as policing.

Thursday was a bit of a mix (and a mix-up). Turns out that as well as two sessions on Big Data I’d co-organized with the ever-patient Agnieszka, I was simultaneously booked as a discussant for Joe Bryan and Denis Wood’s new book Weaponizing Maps. I was sorry to miss this and heard that Denis was in fine form, so here is a pic of him from a session Annette Kim’s new book, Sidewalk City.


I was very pleased with our two sessions, despite being at 8am the morning after the night before (aka the Wildcats party). Session I and Session II links are here. We’re hoping to get some written versions of these soon so I’ll post separately on that. Thanks to the participants in these sessions! And thanks too to the conference gods who gave us a room with big bright windows on a sunny day so that we could look out over the city.

Thursday was also the day of the reception at the Newberry Library for the latest volume of the History of Cartography, Volume 6 The Twentieth Century (edited by Mark Monmonier). It was amazing to see Roz Woodward again:


And Mark Monmonier:


And this nice pic of Roz and series editor Jude Leimer:


After this was the Penn State party on the top floor of the Swissôtel (43rd) where I had a good chat with Rob Roth, Lucky Yapa, Cindy Brewer and others.

Somewhere in there was a very full session on David Harvey’s new book, the latest in his Marx Project as he called it, Seventeen Contradictions. A lot of people noted that this was largely done by his good friends and colleagues, but this is to ignore the very trenchant comments by my colleague Sue Roberts, who called him out on his dismissal of Gibson-Graham’s work on feminist critiques of capital, to which he admitted with a surprisingly childish retort (basically “they started it” meaning they didn’t cite his work, which several people have told me is just incorrect…you may follow this link and judge for yourself).

As I understand it Gibson-Graham critiqued the “capital centric” understandings of capitalism as being too exclusionary of other non-capitalist approaches within the global economy, and since Harvey’s book is deliberatively about contradictions of capital per se (rather than capitalism) he had to dismiss them, though not, as Sue pointed out, by name. So that all seemed a bit shabby of Harvey, but I guess he doesn’t have to care at this point.

The last session I attended was on Friday featuring Lauren Berlant on “Sensing the Commons” forthcoming in Society & Space. This was quite a different style of talk–she totally captivated the large audience–and well outside my area of expertise, or even ways of thinking. I think many people are familiar with her work but it was new to me and I’m very glad I went.

So that’s about it in terms of formal sessions, but there were many other chance encounters and chats in bars and hotel lobbies especially with bright grad students. I also got to interview Stuart Elden about our 2007 book Space, Knowledge and Power: Foucault and Geography (Ashgate) which should soon be posted on the publisher’s website. I’ve listened to the 14 minutes or so of the discussion and I think many people will enjoy hearing about the origins of the book and some of Stuart’s more recent work on Foucault. Good to see Stuart again.

Apologies to all those I missed and I wish I could have seen more. AAG has become a larger than life event and by day 4 I usually need some quiet time! It was great to see friends old and new as well as colleagues whose work I’ve been reading but hadn’t met before (the benefits of organizing sessions!). Next year will be another big one–it’s in San Francisco.

Talk at Colgate University on Big Data

Today I’m giving a talk at Colgate University, in New York. It was a bit of toss-up if the weather would allow me to get here (snow and flight cancellations), but thankfully I’m here safely.

My talk is entitled “Big Data Narratives: Surveillance and Privacy in the Age of the Algorithm.”

Thanks to my hosts Peter Scull, Adam Burnett and the geography department. The talk is made possible by the Dennis Fund endowed lecture series in the social sciences at Colgate.

PS: small historical note. Colgate was the place Peter Gould was evacuated to during WWII when he was a child.

World Economic Forum: privacy is not dead

A post on the World Economic Forum by someone from the SAS Best Practices team says the following five beliefs are wrong:

  • “I’ve got nothing to hide.”
  • Privacy policies apply to data, not users.
  • A single privacy policy will suffice for all your data.
  • Anonymized data keeps my personal identity private.
  • Privacy is dead.

The last one is particularly interesting since it is heard all the time. While there isn’t a true rebuttal on the site, the following comment is offered:

Hence, a more accurate statement would be: Privacy is not dead. Yet. The focus on big data privacy issues is escalating rapidly – and as more people begin to understand what’s at stake, things will change and are beginning to change.

More here.

Did the CIA’s failed torture program have its roots in Big Data thinking?

Did the CIA’s failed torture program have its roots in Big Data thinking?

That is the provocative question asked in a new piece by Jer Thorp “The Three Vs of Enhanced Interrogation.” (The “three Vs” are a common way of describing Big Data: volume, velocity, variety.)

I’ve discussed this connection between intelligence and Big Data previously in a paper here.

Encountering Her

In the movie Her we are treated to a vision of a near-future society in which a new operating system (voiced by Scarlett Johansson) demonstrates such a competent degree of consciousness that not only could it (or rather, she) easily pass a Turing test, but the protagonist of the movie (Joaquin Phoenix) falls in love with her.

Although this is far from the first visualization of an artificial lifeform (depending on how you define it you could go back to Frankenstein or Greek myth where the gods take human form) the way the movie (directed by Spike Jonze) handles the day-to-day interaction makes a big difference. The OS is not physically present, even in image form (no floating faces etc). Like HAL in 2001 (another obvious precursor) you interact via voice control, speaking in natural sentences. The encounter becomes a conversation with a friend.

A couple of months ago Amazon offered the opportunity to sign up for a new gadget called the Echo (shown above). It’s a solid cylindrical device that operates via voice control (and an associated app), and promises to learn as you continue to talk to it. It can play the radio, your music, give you a news briefing (it’s connected to the Internet of course) or answer factual questions. I thought I’d get one and try it out.

The Echo (or “Alexa” as you must call her, somewhat cutely after the Alexandrian Library) is far from being the Her OS. You can be flexible in how you ask for something (it doesn’t just respond to set phrases). You can set where you want your news to come from, and it can play any radio station on TuneIn. It can do basic math, and can translate words into other languages (although the result only appears in the app). It can tell you a joke or connect via Bluetooth to your mobile device. But you certainly can’t hold a conversation, though you might express feelings for it.

My own feelings at the moment are of ambivalence. It’s a pretty exciting piece of technology which is obviously useful. I keep thinking of improvements for the next version, or an upgrade. Alexa should be able to read to you from a book you own on the Kindle. Connecting via your phone it should be able to track you and provide directions and locational information. She should be available in all rooms throughout the house. In fact, she should be part of the house, remotely controlling lights, temperatures, surveillance cameras… and you can see where this might go (think: Skynet). Right now, it saves your voice commands (where? who has access to them?) in order to learn. (You can delete them but it gets less smart if you do since it/she learns your voice and tastes.) It complicates any notion of privacy.

The word smart is overused (and incorrectly used since many dumb things are called smart) but Alexa is clearly another algorithmic construction of our experience. By “experience” I mean the way we encounter the world, and what is available, and crucially not available, to us. Not everything is available to us–in any circumstance–but it becomes all the more critical when you are increasingly dependent on particular sources. There is a vast amount of information out there–this is the promise of Big Data. But it is increasingly channelized and hierarchically findable. These asymmetries are a Grand Challenge of our times, and increase daily with increasing prevalence of “software sorted” and Big Data living.

CFP: Spatial Big Data & Everyday Life (AAG 2015)

Call for Papers: Spatial Big Data & Everyday Life
American Association of Geographers Annual Meeting
21-25 April 2015

Agnieszka Leszczynski, University of Birmingham
Jeremy Crampton, University of Kentucky
“What really matters about big data is what it does” (Executive Office of the President, 2014: 3).

Many disciplines, including the economic and social sciences and (digital) humanities, have taken up Big Data as an object and/or subject of research (see Kitchin 2014). As a significant proportion of Big Data productions are spatial in nature, they are of immediate interest to geographers (see Graham and Shelton 2013). However, engagements of Big Data in geography have to date been largely speculative and agenda-setting in scope. The recently released White House Big Data report encourages movement past deliberations over how to define the phenomenon towards identifying its material significance as Big Data are enrolled and deployed across myriad contexts – for example, how content analytics may open new possibilities for data-based discrimination. We convene this session to interrogate and unpack how Big Data figure in the spaces and practices of everyday life. In so doing, we are questioning not only what Big Data ‘do,’ but also how it is they realize particular kinds of effects and potentialities, and how the lived reality of Big Data is experienced (Crawford 2014).

We invite papers along methodological, empirical, and theoretical interventions that trace, reconceptualize, or address the everyday spatial materialities of Big Data. Specifically we are interested in how Big Data emerge within particular intersections of the surveillance, military, and industrial complexes; prefigure and produce particular kinds of spaces and subjects/subjectivities; are bound up in the regulation of both space and spatial practices (e.g., urban mobilities); underwrite intensifications of surveillance and engender new surveillance regimes; structure life opportunities as well as access to those opportunities; and/or change the conditions of/for embodiment. We intend for the range of topics and perspectives covered to be open. Other possible topics include:

• spatial Big Data & affective life
• embodied Big Data; wearable tech; quantified self
• algorithmic geographies, algorithmic subjects
• new ontologies & epistemologies of the subject
• spatial Big Data as surveillance
• Big Data and social (in)equality
• “ambient government” & spatial regulation
• spatial Big Data and urbanisms (mobilities; smart cities)
• political/knowledge economies of (spatial) Big Data

We welcome abstracts of no more than 250 words to be submitted to Agnieszka Leszczynski (a.leszczynski@bham.ac.uk) and Jeremy Crampton (jcrampton@uky.edu) by August 29th, 2014.

Crawford K (2014) The Anxieties of Big Data. The New Inquiry. http://thenewinquiry.com/essays/the-anxieties-of-big-data/

Executive Office of the President (2014) Big Data: Seizing Opportunities, Preserving Values. The White House. http://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_may_1_2014.pdf

Graham M and Shelton T (2013) Guest editors, Dialogues in Human Geography 3 (Geography and the future of big data, big data and the future of geography).

Kitchin R (2014) Big Data, new epistemologies and paradigm shifts. Big Data and Society (1): In Press. DOI: 10.1177/2053951714528481. http://bds.sagepub.com/content/1/1/2053951714528481.


Mapping all NYC’s taxi rides


Fascinating patterns are revealed by this unusual data set: all of the taxi rides captured by GPS in New York City–some 173 million trips. Mapbox has some maps and analysis.

Note also this warning: the data were “de-anonymized” fairly easily.