Author Archives: Jeremy

Are robots eating all the jobs? Perhaps not–Andrea Salvatori

We can't blame the loss of mid-level jobs purely on robots

Andrea Salvatori, University of Essex

Several developed countries including the US, UK and Germany have seen their labour markets polarised in recent decades as the number of middle-skilled jobs has declined relative to that of low and high-skilled ones. Technology has been singled out as the main culprit: computers and automation have reduced the demand for mid-level skilled workers in production lines as well as offices, increasing that for high-skilled managers, professionals and technicians. But there has been little or no impact on the demand for low-skilled service occupations.

There is a perception that the range of tasks that can be automated is rapidly expanding thanks to fast technological development. This has exacerbated concerns on the impact of technology on the quantity and quality of jobs. But does the evidence support the view that the future of the labour market is entirely in the hands of the robots?

In the simplest version of this story, as advancements in technology lead firms to demand fewer workers in mid-skill occupations, these jobs should see both employment and wages decline relative to low and high-skill jobs. This should show up in economic data as what we might call “double polarisation”: when both employment and wages grow more in high and low-skill occupations than they do in middling ones. This double polarisation was indeed what happened in the US in the 1990s, but it did not continue into the 2000s. More broadly, wage polarisation has generally not been detected in other countries that have experienced job polarisation, such as Germany and the UK.

The simple story blaming technology alone for taking mid-skilled jobs cannot explain what we see in the data. Other factors are likely to have played an important role, as I have explored in my ongoing research on the situation in the UK.

UK boom in high-skilled jobs

The UK has seen a steady decline in middling occupations since at least 1980. As the graph below shows, growth in top occupations exceeded that in bottom ones in each of the last three decades. This has resulted in a substantial shift of employment from middling to top occupations: out of 100 employees, 19 fewer could be found in middle-skill occupations in 2012 than in 1979. Of these, 16 had moved to higher-skill occupations and only three into lower-skill ones.

Job polarisation in the UK.
Author provided

This is noticeably different from the US experience, where growth at the bottom has progressively outpaced that at the top, culminating in the 2000s when employment growth was concentrated in low-skill occupations.

A distinctive change that took place in the UK since the early 1990s is the expansion in university education which led to a threefold increase in the share of graduates among employees. The expansion of graduates in this way is different to the US, which saw no comparable increase in the share of graduates over the past 20 years. This increase in the educational attainment of the UK workforce accounts for the entire growth in top-skilled occupations and a third of the decline in middling occupations.

There is no indication that wages in middling occupations have been decreasing in the UK, as one would expect if demand was declining due to the spread of automation. It is instead the performance of wages in high-skill occupations that has deteriorated over time relative to middling ones. It was the worst in the 2000s when wages in the 10% highest-paid occupations grew 10% less than those in median occupations.

During this period, the supply of graduates in the UK continued to grow at the same time as the growth of top occupations in other similarly developed countries such as the US and Canada stalled. This stalling elsewhere suggests that there may have been a wider slow down in the (technology-led) demand for high-skill occupations in the 2000s.

These facts are highly suggestive that the improvement in the education of the workforce has contributed significantly to the reallocation of employment from mid- to high-skill occupations in the UK.

Clerical wages going up

But the evidence from the UK also highlights another possible limitation of the story in which technology simply replaces mid-skilled workers. Since the 1990s, the share of mid-level, clerical jobs in the UK has indeed slowly declined, consistent with the idea that technology reduces the need for people in these occupations.

However, over the same period the wages of clerical workers have grown at a rate similar to that of professional occupations, such as lawyers and doctors, a fast-growing group whose real wages increased by about 64%. Similarly, other studies have also found that in the US, clerical occupations have seen their wages increase in spite of the decline in their relative number.

One of the early proponents of the idea that computers displace mid-skilled workers, MIT scholar David Autor, has argued that, within the same occupation, technology might replace workers in certain tasks while complementing them in others which are more cognitive and difficult to automate – or even expand the range of tasks they can perform. So, while much of the filing work once done by secretaries might now be done by computers, the remaining secretaries are supported by computers in their other tasks and perform a range of new organisational ones that were once the domain of managerial staff.

While there is no doubt that technology is a major force at play in the labour market, the differences in experiences across countries suggests other factors play an important role as well. For the UK, several pieces of evidence indicate that the expansion in university education has contributed to changing the occupational structure of the labour market.

Across countries, there is generally little evidence to support the idea that automation has been dramatically disrupting the labour market in recent times. Instead, there are clear indications that the story is likely to be a nuanced one, where the complex interaction between changes in the skills of the workforce, technology and the way different tasks are bundled into jobs means that the fate of those occupations that might appear most at risk might not be quite sealed yet.

The Conversation

Andrea Salvatori is Research Fellow, Institute for Social and Economic Research at University of Essex.

This article was originally published on The Conversation.
Read the original article.

John Krygier reflects on Brian Harley’s Deconstructing the map (full text)

John Krygier has a piece in the latest issue of Cartographica reflecting on Brian Harley’s famous paper “Deconstructing the Map.” John’s full text is available here.

It’s a great piece, because, a la Harper’s Annotations, John annotates his actual notes he took reading Harley’s paper. See below:

Pages from krygier_harley_reflection_2015

AUVSI holds major drone conference

The Association for Unmanned Systems International, known as AUVSI, recently held its annual conference in Atlanta. The Drone Center at Bard University has a good write-up.

One thing to note: AUVSI has always resisted using the word “drone,” favoring the military term UAV or UAS, but seems to be looking at it more favorably as drones enter the civilian market.

Papers from “Where’s the Value? Emerging Digital Economies of Geolocation” session

The written texts from the AAG panel session I co-organized with Agnieszka Lesczczynski entitled “Where’s the Value? Emerging Digital Economies of Geolocation” are now available. The panelists were Elvin Wyly (UBC), Rob Kitchin (National University of Ireland at Maynooth), Agnieszka Leszczynksi (University of Birmingham) and Julie Cupples (University of Edinburgh).

Two were posted to blogs (linked below) and two are reproduced below. Although I posted links to a couple of these previously, this blog entry collects them all. (Two panelists, Sam Kinsley and David Murakami Wood, were regrettably unable to attend.)

Thanks again to all!

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Elvin Wyly: “Capitalizing the Records of Life” (see below)

Rob Kitchin “Towards geographies of and produced by data brokers

Agnieszka Leszczynski “What makes location valuable? Geolocation as evidence, meaning, & identity” (see below)

Julie Cupples “Coloniality, masculinity and big data economies

And here again is the audio from the session.

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“Capitalizing the Records of Life”
Elvin Wyly, UBC

Let me begin with a confession.  I did some homework reading the cv’s of my colleagues on this panel, and this is where I found the answer to our central question, “Where’s the value in the emerging digital economies of geolocation?”  I.  Am.  In.  Awe.  It’s here, right here, right now, in the intersecting life-paths of extraordinary human geographers coming together to share the results of labor, creativity, critical insight and commitment.  Julie Cupples’ work on decolonizing education and geographies of media convergence intersects with Agnieszka Lesczynski’s inquiry into the gendered dimensions of the erosion of locational privacy and the “new digital spatial mediations of everyday life,” and Sam Kinsley’s ‘Contagion’ project on the movement of ideas through technologically mediated assemblages of people, devices, and algorithms.  David Murakami Wood’s Smart Cities project and editorial assemblage in the journal Surveillance and Society respond directly to the challenges and opportunities in Rob Kitchin’s (2014) call in The Data Revolution for “a more critical and philosophical framing” of the ontology, epistemology, ideology, and methodology” of the “assemblage surrounding” the production and deployment of geolocational data.  And many of these connections have been the subject of wise anticipatory reflections on Jeremy Crampton’s Open Geography, where the adjective and the verb of ‘open’ in the New Mappings Collaborative give us a dynamic critical cartography of the overwhelming political and knowledge economies of spatialized information.

As I read the cv’s of my panelists, it became obvious that the value of a record of a life — that’s the Latin curriculum vitae — is the new frontier of what James Blaut (1993) once called The Colonizer’s Model of the World, and what Kinsley (2014) has diagnosed as “the industrial retention of collective life.”  Smart cities, the social graph, the Internet of Things, the Quantified Self, the Zettabyte (270 bytes) Age analyzed by Kitchin:  all of this signifies a new quantitative revolution defined by the paradox of life in the age of post-humanist human geography.  In the closing lines of Explanation in Geography, David Harvey announced “by our models they shall know us” — a new generation of human geographers bearing the models and data of modern science; today, it’s the algorithms, models, and corporations that arrive bearing humans — millions and billions of them — whose curricula vitae can be measured, mapped, and monetized at scales that are simulteneously perrsonalized and planetary.  Facebook alone curates more than 64 thousand years of human social relations every day (four-fifths of it on mobile devices and four-fifths of it outside the U.S. and Canada) and LinkedIn CEO Jeffrey Weiner (quoted in MarketWatch, 2015) recently declared, “We want to digitally map the global economy, identifying the connections between people, companies, jobs, skills, higher educational organizations and professional knowledge and allow all forms of capital, intellectual captial, financial capital, and human capital to flow to where [they] can best be leveraged.”

Capitalized curricula vitae, however, are automating and accelerating what Anne Buttimer once called the ‘dance macabre’ of the knowledge economies of spatialized information, because the deceptively friendly concept of ‘human capital’ is in fact a deadly contradiction:  capital is dead labor, the accumulated financial and technological appropriation of surplus value created through human labor, human creativity, and human thought.  Buttimer’s remark about geospatial information being “a chilly recording by a detached observer, a hollow rattle of bones” hurt — because this is what she said in a conversation to the legendary time-geographer Torsten Hägerstrand, who in the 1940s spent years with his wife Britt in the church-register archives of a rural Swedish parish to understand “a human population in its time and space context.  Here’s what Hägerstrand (2006, p. xi) recalls:

 “[We] worked out the individual biographies of all the many thousands of individuals who had lived in the area over the last hundred years.  We followed them all from year to year, from home to home, and from position to position.  As the data accumulated, we watched the drama of life unfold before our eyes with graphic clarity.  It was something of stark poetry to see the people who lived around us, many of whom we knew, as the tips of stems, endlessly twisting themselves down in the realm of times past.”

Hägerstrand wrote that he was disturbed and alarmed by Buttimer’s words, and I am too, because Allan Pred (2005, p. 328) began his obituary for Hägerstrand by quoting Walter Benjamin, emphasizing that it is not only knowledge or wisdom, but above all real life — “the stuff stories are made of” — which “first assumes transmissible form at the moment of …death.”  But just as “every text has a life history” (Pred, 2005, p. 331) that comes to an end, now Allan Pred’s curriculum vitae has also assumed transmissible form of the market-driven, distorted sort you can track through the evolving Hägerstrandian time-space prisms of the digitized network society.  Hägerstrand is dead, but he has a Google Scholar profile that’s constantly updated by the search robots, and the valorized geolocatable knowledge of his citations put him in a dance macabre of apocalyptic quantification:  he is “worth” only 1.093 percent of the valorization of another dead curriculum vitae, that of Foucault, who’s also on Google Scholar.  The world is falling in love with geography, but we don’t need more than just a few human geographers to do geography, thanks to the self-replicating algorithms and bots of the corporate cloud of cognitive capital.

The geolocatable knowledge economy is thus a bundle of contradictions and the endgame of the organic composition of human capital.  Human researchers spending years in the archives to build databases are now put into competition with the fractal second derivatives of code:  how do I balance my respect and reverence for our new generation of geographers screen-scraping APIs and coding in R, D3, Python, and Ruby on Rails without giving up what we have learned from the slow, patient, embodied labor of previous generations working by hand?  I see the tips of stems, not just in Hägerstrand’s small Swedish parish, but right here, in this room.  Tips of stems, endlessly twisting down in the realm of times past — but in today’s times where each flower now faces unprecedented competition in every domain:  jobs, research support, academic freedom, human care, human recognition, human attention.  Tips of stems, endlessly twisting through time-spaces of a present suffused with astronomical volumes of geographical data in what the historian George Dyson (2012) calls the “universe of self-replicating code.”  Tips of stems, tracing out an entirely new ontology of socio-spatial sampling theory defined by the automated mashup analytics that now combine Hägerstrand’s time-space diagrams with Heisenberg’s observational uncertainties, Alan Turing’s (1950) ‘universal machine,’ and Foucault’s archaeology of knowledge blended with Marx’s conception of the “general intellect” and Auguste Comte’s notion of the ‘Great Being’ of all the accumulated knowledge of intergenerational human knowledge, tradition, and custom.  Tips of stems, tracing lifeworlds of a situationist social physics that treats smartphones as “brain extenders” (Kurzweil, 2014) converging into a planetary “hive mind” (Shirky, 2008) while reconfiguring the observational infrastructures and human labor relations of an empiricist hijacking of positivism:  if Chris Anderson (2008) is correct that the petabyte age of data renders the scientific method obsolete, then who needs theory?

We all need theory — we humans.  Theory is the intergenerational inheritance of human inquiry, human thought, and human struggle.  Let me be clear:  I mean no disrespect to the extraordinary achievements of the new generation of data revolutionaries represented by my distinguished panelists, and all of you who can code circles around my pathetic do-loop rusty routines in FORTRAN, Cobol, and SAS.  Tips of stems, twisting themselves down into the realms of human history:  take a look around, at one of the last generations of human geospatial analysts, before we’re all replaced by algorithmic aggregation.  Yesterday’s revolution was humans doing quantification.  Today’s revolution is quantification doing humans.


Anderson, Chris (2008).  “The End of Theory:  The Data Deluge Makes the Scientific Method Obsolete.”  Wired, June 23.

Blaut, James (1993).  The Colonizer’s Model of the World.  New York:  Guilford Press.

Dyson, George (2012).  “A Universe of Self-Replicating Code.”  Edge, March 26, at

Hägerstrand, Torsten (2006).  “Foreword.”  In Anne Buttimer and Tom Mels, By Northern Lights:  On the Making of Geography in Sweden.  Aldershot:  Ashgate, xi-xiv.

Kitchin, Rob (2014).  The Data Revolution:  Big Data, Open Data, Data Infrastructures and Their Consequences.  London:  Sage Publications.

Kinsley, Sam (2014).  “Memory Programmes:  The Industrial Retention of Collective Life.”  Cultural Geographies, October.

Kurzweil, Ray (2014).  Comments at ‘Will Innovation Save Us?’ with Richard Florida and Ray Kurzweil.  Vancouver:  Simon Fraser University Public Square, October.

MarketWatch (2015).  “LinkedIn Wants to Map the Global Economy.”  MarketWatch, April 9.

Pred, Allan (2005).  “Hägerstrand Matters:  Life(-path) and Death Matters — Some Touching Remarks.”  Progress in Human Geography 29(3), 328-332.

Shirky, Clay (2008).  Here Comes Everybody:  The Power of Organizing Without Organizations.  New York:  Penguin.

Turing, Alan M. (1950).  “Computing Machinery and Intelligence.”  Mind 59(236), 433-460.


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“What makes location valuable? Geolocation as evidence, meaning, & identity”
Agnieszka Lesczcynski, University of Birmingham

I want to invert the question that Jeremy and myself posed to the panel when organizing this session by asking, rather than ‘where is the value’ in geolocation, what is it that makes geolocation valuable? In contending that there are particular kinds of economies emerging around location, it is because geolocation itself is somehow intrinsically valuable, and I’d like to make some preliminary propositions to this end.

Over the last few years I have been particularly interested in the ways in which emergent surveillance practices of the securities agencies, made broadly known to us through the as yet still-unfolding Snowden revelations, are crystallizing around big data – its collection, mining, interception, aggregation, and analytics. And specifically, I’m particularly interested in the ways in which locational data is figuring as central within these emergent regimes of dataveillance. Indeed at the close of 2013, Barton Gellman and Ashkan Soltani, reporting in the Washington Post, identified at least ten American signals intelligence programmes or SIGADs that explicitly sweep up locational data – i.e., where location data is the target or object of data capture, interception, and aggregation.

  • Under a SIGAD designated HAPPYFOOT, the NSA taps directly into mobile app data traffic that streams smartphone locations to location-based advertising networks organized around the delivery of proximately relevant mobile ads, often unencrypted and in the clear. This locational data, which is often determined through mobile device GPS capabilities, is far higher-resolution than network location, allowing the NSA “to map Internet addresses to physical locations more precisely than is possible with traditional Internet geolocation services”
  • Documents dating from 2010 reveal that the NSA and GCHQ exploit weaknesses in ‘leaky’ mobile social and gaming applications that veil secondary data mining operations behind primary interfaces, piggybacking off of commercial data collection by syphoning up personal information including location under a signals intelligence program code-named ‘TRACKER SMURF’ after the children’s animated classic
  • In perhaps the most widely publicized example, the NSA collects over 5 billion cell phone location registers off of cell towers worldwide, bulk processing this location data through an analytics suite code-named CO-TRAVELLER which looks to identify new targets for surveillance on the basis of parallel movement with existing targets of surveillance – i.e., individuals whose cell phones ping off of the same cell towers in the same succession at the same time as individuals already under surveillance.
  • Just a few months ago, it was leaked that the CSE, or Canada’s version of the NSA, was tracking domestic as well as foreign travelers via Wi-Fi at major Canadian airports for up to two weeks as they transited through the airports and subsequently through other ‘nodes’ including other domestic and international airports, urban Wi-Fi hotspots, transport hubs, major hotels and conference centers, and even public libraries both within Canada and beyond in a pilot project for the NSA;
  • and, most recently, under a SIGAD code-named LEVITATION, the CSE has been demonstrated to be intercepting data cable traffic to monitor up to 15 million file downloads a day. Particularly significant in the leaked CSE document detailing this programme is that the CSE explicitly states that it is looking to location data to improve LEVITATION capabilities for intercepting both GPS waypoints and “[d]evices close to places” so as to further isolate and develop surveillance targets, including those carrying and using devices within proximity of designated locations.

So the question is, why geolocation? Why is it of such great interest to the securities agencies? And here I want to argue that it is of interest because it is inherently valuable, and uniquely so amongst other forms of PII. And this value is latent in the spatio-temporal and spatial-relational nature of geolocation data.

  • the spatio-temporal nature of many spatial big data productions means that it may be enrolled as definitive evidence of our complicity or involvement in particular kinds of socially disruptive events or emergencies by virtue of our presence, or as in the case of CO-TRAVELER, co-presence and co-movement, in particular spaces at particular times
  • furthermore, longitudinal retention of highly precise, time-stamped geoloational data traces allow for the reconstruction of detailed individual spatial histories, which like the CO-TRAVELER example, similarly participate within what Kate Crawford has recently characterized as emergent truth economies of big data in which data is truth;
  • the relational nature of spatial big data productions, in which our data may be used to discern our religious, ethnic, political and other kinds of personal affiliations and identifies on the basis of the kinds of places that we visit and the ability to establish linkages with other PII across data flows;
  • and, in this vein, the ways in which locations are inherently meaningful – for example, they may be as revealing of highly sensitive information about ourselves as our DNA. For instance, on the basis of the specialty of a medical office that we visit, this information may be revelatory of the fact that we may have a degenerative genetic disease and the nature of that disease – information that socially we otherwise understand as some of the most private information about ourselves.
  • and, of course, the ways in which location is not only revealing of identity positions, but it is identity – for example, a group of researchers determined that unique individuals could be identified form the spatial metadata of only four cell phone calls at a very high confidence level.

So in asking where is the value in geolocation, my take is that it is valuable – to both the intelligence apparatuses that I have highlighted here but also corporate entities – because it is uniquely sensitive – revealing and identifying – amongst other forms of PII.

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Will Periscope, a Mobile App, Open Up Academic Conferences?


Kris Olds on the recent AAG conference and the possibilities and consequences of live streaming sessions. In GlobalHigherEd.

Originally posted on GlobalHigherEd:

Link here for the Inside Higher Ed version of this entry which can more easily be shared & printed.


Nearly 9,000 people, myself included, attended the annual conference of the Association of American Geographers (AAG) in late April 2015. The size of the conference has been growing over the last several decades and it has become a de facto international gathering despite the ‘American’ moniker; a trading space of sorts to present papers, share ideas, formulate collaborative research proposals, source prospective faculty, share gossip, have good times, etc. Of the 8,950 people who flew/drove/trained it to Chicago this April, 5,716 came from the US, 726 came from Canada, 666 from the UK, 257 came from China, and nearly equivalent numbers (35 vs 37) came from Singapore vs Mexico. All told, attendees came from 84 countries in total and they’re mapped out below courtesy of my department’s Cartography Lab

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Rob Kitchin: Towards geographies of and produced by data brokers

Rob Kitchin has posted his remarks from our AAG panel here in a piece entitled “Towards geographies of and produced by data brokers.” The panel itself was entitled “Where’s the Value? Emerging Digital Economies of Geolocation.” My thanks to Rob for participating.

(This follows up the previous post where I noted that Julie Cupples’ contribution for the same panel is also now online.)

Julie Cupples: Coloniality, masculinity and big data economies

Good news: Julie Cupples has placed the text of her talk “Coloniality, masculinity and big data economies” which she gave at the recent AAG meetings for the panel session I co-organized with Agnieszka Lesczczynski “Where’s the Value? Emerging Digital Economies of Geolocation.” My thanks to Julie for participating.

via Julie Cupples: Coloniality, masculinity and big data economies.