Call for papers: Geography of/with A.I

Still from the video for All is Love by Bjork

I very much welcome any submissions to this call for papers for the proposed session for the RGS-IBG annual conference (in London in late-August) outlined below. I also welcome anyone getting in touch to talk about possible papers or ideas for other sorts of interventions – please do get in touch.

Call for papers:

We are variously being invited to believe that (mostly Global North, Western) societies are in the cusp, or early stages, of another industrial revolution led by “Artificial Intelligence” – as many popular books (e.g. Brynjolfsson and McAfee 2014) and reports from governments and management consultancies alike will attest (e.g. PWC 2018, UK POST 2016). The goal of this session is to bring together a discussion explicitly focusing on the ways in which geographers already study (with) ‘Artificial Intelligence’ and to, perhaps, outline ways in which we might contribute to wider debates concerning ‘AI’. 

There is widespread, inter-disciplinary analysis of ‘AI’ from a variety of perspective, from embedded systematic bias (Eubanks 2017, Noble 2018) to the kinds of under-examined rationales and work through which such systems emerge (e.g. Adam 1998, Collins 1993) and further to the sorts of ethical-moral frameworks that we should apply to such technologies (Gunkel 2012, Vallor 2016). In similar, if somewhat divergent ways, geographers have variously been interested in the kinds of (apparently) autonomous algorithms or sociotechnical systems are integrated into decision-making processes (e.g. Amoore 2013, Kwan 2016); encounters with apparently autonomous ‘bots’ (e.g. Cockayne et al. 2017); the integration of AI techniques into spatial analysis (e.g. Openshaw & Openshaw 1997); and the processing of ‘big’ data in order to discern things about, or control, people (e.g. Leszczynski 2015). These conversations appear, in conference proceedings and academic outputs, to rarely converge, nevertheless there are many ways in which geographical research does and can continue to contribute to these contemporary concerns.

The invitation of this session is to contribute papers that make explicit the ways in which geographers are (already) contributing to research on and with ‘AI’, to identify research questions that are (perhaps) uniquely geographical in relation to AI, and to thereby advance wider inter-disciplinary debates concerning ‘AI’.

Examples of topics might include (but are certainly not limited to):

  • A.I and governance
  • A.I and intimacy
  • Artificially intelligent mobilities
  • Autonomy, agency and the ethics of A.I
  • Autonomous weapons systems
  • Boosterism and ‘A.I’
  • Feminist and intersectional interventions in/with A.I
  • Gender, race and A.I
  • Labour, work and A.I
  • Machine learning and cognitive work
  • Playful A.I
  • Science fiction, spatial imaginations and A.I
  • Surveillance and A.I

Please send submissions (titles, abstracts (250 words) and author details) to: Sam Kinsley by 31st January 2019.

Bernard Stiegler’s Age of Disruption – out soon

Bernard Stiegler being interviewed

Out next year with Polity, this is one of the earlier of Stiegler’s ‘Anthropocene’ books (in terms of publication in French, see also The Neganthropocene) explicating quite a bit of the themes that come out in the interviews I’ve had a go at translating in the past three years (see: “The time saved through automation must be given to the people”; “How to survive disruption”; “Stop the Uberisation of society!“; and “Only by planning a genuine future can we fight Daesh“). Of further interest, to some, is that it also contains a dialogue with Nancy (another Derrida alumnus). This book is translated by the excellent Daniel Ross.

Details on the Polity website. Here’s the blurb:

Half a century ago Horkheimer and Adorno argued, with great prescience, that our increasingly rationalised and Westernised world was witnessing the emergence of a new kind of barbarism, thanks in part to the stultifying effects of the culture industries. What they could not foresee was that, with the digital revolution and the pervasive automation associated with it, the developments they had discerned would be greatly accentuated and strengthened, giving rise to the loss of reason and to the loss of the reason for living. Individuals are overwhelmed by the sheer quantity of digital information and the speed of digital flows, and profiling and social media satisfy needs before they have even been expressed, all in the service of the data economy. This digital reticulation has led to the disintegration of social relations, replaced by a kind of technological Wild West, in which individuals and groups find themselves increasingly powerless, driven by their lack of agency to the point of madness.
How can we find a way out of this situation? In this book, Bernard Stiegler argues that we must first acknowledge our era as one of fundamental disruption and detachment. We are living in an absence of epokh? in the philosophical sense, by which Stiegler means that we have lost our noetic method, our path of thinking and being. Weaving in powerful accounts from his own life story, including struggles with depression and time spent in prison, Stiegler calls for a new epokh? based on public power. We must forge new circuits of meaning outside of the established algorithmic routes. For only then will forms of thinking and life be able to arise that restore meaning and aspiration to the individual.
Concluding with a substantial dialogue between Stiegler and Jean-Luc Nancy in which they reflect on techniques of selfhood, this book will be of great interest to students and scholars in social and cultural theory, media and cultural studies, philosophy and the humanities generally.

“The good robot”

Anki Vector personal robot

A fascinating and very evocative example of the ‘automative imagination’ in action in the form of an advertisement for the “Vector” robot from a company called Anki.

How to narrate or analyse such a robot? Well, there are lots of the almost-archetypical figures of ‘robot’ or automation. The cutesy and non-threatening pseudo-pet that the Vector invites us to assume it is, marks the first. This owes a lot to Wall-E (also, the robots in Batteries Not Included and countless other examples) and the doe-eyed characterisation of the faithful assistant/companion/servant. The second is the all-seeing surveillant machine uploading all your data to “the cloud”. The third is the two examples of quasi-military monsters with shades of “The Terminator”, with a little bit of helpless baby jeopardy for good measure. Finally, the brief nod to HAL 9000, and the flip of the master/slave that it represents, completes a whistle-stop tour of pop culture understandings of ‘robots’, stitched together in order to sell you something.

I assume that the Vector actually still does the kinds of surveillance it is sending up in the advert, but I have no evidence – there is no publicly accessible copy of the terms & conditions for the operation of the robot in your home. However, in a advertorial on ‘Robotics Business Review‘, there is a quote that sort of pushes one to suspect that Vector is yet another device that on the face of it is an ‘assistant’ but is also likely to be hoovering up everything it can about you and your family’s habits in order to sell that data on:

“We don’t want a person to ever turn this robot off,” Palatucci said. “So if the lights go off and it’s on your nightstand and he starts snoring, it’s not going to work. He really needs to use his sensors, his vision system, and his microphone to understand the context of what’s going on, so he knows when you want to interact, and more importantly, when you don’t.”

If we were to be cynical we might ask – why else would it need to be able to do all of this? –>

Anki Vector “Alive and aware”

Regardless, the advert is a useful example of how the bleed from fictional representations of ‘robots’ into contemporary commercial products we can take home – and perhaps even what we might think of as camouflage for the increasingly prevalent ‘extractive‘ business model of in-home surveillance.

Automating inequality – Virginia Eubanks and interlocutors [video]

Still from George Lucas' THX1138

This Data & Society talk by Virginia Eubanks on her book Automating Inequality followed by a discussion with Alondra Nelson and Julia Angwin is excellent. This seems like vital empirical analysis and insights that flesh out what is, perhaps, frequently gestured towards by ‘critical algorithm studies’ folks – ‘auditing algorithms’, analysing what’s in the black box, how systems function and what is their material and socio-economic specificity and what then can we learn about how particular forms of actually existing automation (and not simply abstract ideals) function.

Eubanks talks for the first 20-ish minutes and then there’s a discussion that follows. This is really worth watching if you’re interested in doing algorithm studies type work and in doing ‘digital geographies’ that don’t simply lapse into ontology talk.

‘Pax Technica’ Talking Politics, Naughton & Howard

Nest - artwork by Jakub Geltner

This episode of the ‘Talking Politics‘ podcast is a conversation between LRB journalist John Naughton and the Oxford Internet Institute’s Professor Phillip Howard ranging over a number of issues but largely circling around the political issues that may emerge from ‘Internets of Things’ (the plural is important in the argument) that are discussed in Howard’s book ‘Pax Technica‘. Worth a listen if you have time…

One of the slightly throw away bits of the conversation, which didn’t concern the tech, that interested me was when Howard comments on the kind of book Pax Technica is – a ‘popular’ rather than ‘scholarly’ book and how that had led to a sense of dismissal by some. It seems nuts (to me, anyway) when we’re all supposed to be engaging in ‘impact’, ‘knowledge exchange’ and so on that opting to write a £17 paperback that opens out debate, instead of a £80+ ‘scholarly’ hardback, is frowned upon. I mean I understand some of the reasons why but still…

Reblog> New paper: A smart place to work? Big data systems, labour, control, and modern retail stores

Gilbreth motion studies light painting

From the Programmable City team, looks interesting:

New paper: A smart place to work? Big data systems, labour, control, and modern retail stores

The modern retail store is a complex coded assemblage and data-intensive environment, its operations and management mediated by a number of interlinked big data systems. This paper draws on an ethnography of a superstore in Ireland to examine how these systems modulate the functioning of the store and working practices of employees. It was found that retail work involves a continual movement between a governance regime of control reliant on big data systems which seek to regulate and harnesses formal labour and automation into enterprise planning, and a disciplinary regime that deals with the symbolic, interactive labour that workers perform and acts as a reserve mode of governmentality if control fails. This continual movement is caused by new systems of control being open to vertical and horizontal fissures. While retail functions as a coded assemblage of control, systems are too brittle to sustain the code/space and governmentality desired.

Access the PDF here

Roadside billboards display targeted ads in Russia

racist facial recognition

From the MIT Tech Review:

Moscow Billboard Targets Ads Based on the Car You’re Driving

Targeted advertising is familiar to anyone browsing the Internet. A startup called Synaps Labs has brought it to the physical world by combining high-speed cameras set up a distance ahead of the billboard (about 180 meters) to capture images of cars. Its machine-learning system can recognize in those images the make and model of the cars an advertiser wants to target. A bidding system then selects the appropriate advertising to put on the billboard as that car passes.

Marketing a car on a roadside billboard might seem a logical fit. But how broad could this kind of advertising be? There is a lot an advertiser can tell about you from the car you drive, says Synaps. Indeed, recent research from a group of university researchers and led by Stanford found that—using machine vision and deep learning—analyzing the make, model, and year of vehicles visible in Google Street View could accurately estimate income, race, and education level of a neighborhood’s residents, and even whether a city is likely to vote Democrat or Republican.

As the camera spots a BMW X5 in the third lane, and later a BMW X6 and a Volvo XC60 in the far left lane, the billboard changes to show Jaguar’s new SUV, an ad that’s targeted to those drivers.

Synaps’s business model is to sell its services to the owners of digital billboards. Digital billboard advertising rotates, and more targeted advertising can rotate more often, allowing operators to sell more ads. According to Synaps, a targeted ad shown 8,500 times in one month will reach the same number of targeted drivers (approximately 22,000) as a typical ad shown 55,000 times. The Jaguar campaign paid the billboard operator based on the number of impressions, as Web advertisers do. The traditional billboard-advertising model is priced instead on airtime, similar to TV ads.

In Russia, Synaps expects to be operating on 20 to 50 billboards this year. The company is also planning a test in the U.S. this summer, where there are roughly 7,000 digital billboards, a number growing at 15 percent a year, according to the company. (By contrast, there are 370,000 conventional billboards.) With a row of digital billboards along a road, they could roll the ads as the cars move along, making billboard advertising more like the storytelling style of television and the Internet, says Synaps’s cofounder Alex Pustov.

There are limits to what the company will use its cameras for. Synaps won’t sell data on individual drivers, though the company is interested in possibly using aggregate traffic patterns for services like predictive traffic analysis and the sociodemographic analysis of commuters versus residents in an area, traffic emissions tracking, or other uses.

Out of safety concerns, license plate data is encrypted, and the company says it will comply with local regulations limiting the time this kind of data can be stored, as well.

Well that’s alright then! 😉