This is rather good.
An interesting project from Mushon Zer-Aviv, with shades of Canguilhem:
This ‘deepfake’ video of lots of current and former world leaders and other famous people is interesting and provokes all sorts of questions. Some suggest legislation against them, which is what the US seems to be pursuing, but that of course asks further questions about how to ‘police’ them and who has agency. There are, perhaps, some interesting resonances with the increasing use of performance holograms to re-animate dead performers – but there, of course, the legal issues are different. Nevertheless, all sorts of ideas, aesthetic, ethical and otherwise, about ‘authenticity’ crop up (e.g. this from New Scientist, or this on trust in ‘evidence’ re ‘deepfakes’), which we will increasingly be provoked into discussing.
It is interesting, I think, that while those of us in what we call ‘critical’ social sciences or humanities have been developing fairly nuanced articulations of identity and subjectivity, arguing they are not necessarily essential and acknowledging how they are performed (for example), contemporary digital/ social media, and our uses of them, have forged new norms of ‘authenticity’ in relation to identity. Facebook wants ‘true’ names, for instance. “Finsta” (‘f’ denoting ‘fake’), the phenomenon of setting up hidden, often pseudonymous, Instagram accounts – only for selected friends (as opposed to your curated “rinsta” account (‘r’ denoting ‘real’)) shows how these two understandings of the performative nature of identity and the construction of a normative insistence on ‘authenticity’ collide. We might reasonably ask, for instance, why the ‘finsta’/’rinsta’ labels don’t actually mean the reverse if the more public of the two accounts is heavily curated and the ‘secret’ one is in some senses then more ‘authentic’.
‘Deepfakes’ are, amongst other things, a sensory ‘trick’, an attempt to somehow fool the conscious and sub-conscious habitual discernment of what feels whatever it is we mean by ‘authentic’, ‘genuine’ or ‘real’. In some senses, ‘deepfakes’ reveal back to us the extent to which digital media may have shifted how we pay attention and how we feel (about ourselves, others and the world around us) with and through them. Digital media cultivate attention in different ways, many of them perhaps oriented towards a capitalist imperative, also, perhaps, with them we cultivate forms of paying attention. If this is the case then, as was argued in terms of the potency of TV advertising, we may begin to ‘see through’ the ‘tricks’ precisely because we are bombarded with them (for example, the Putin bits in the video above are not very convincing to my eye). Or, to be pessimistic, we may simply begin to assume nothing can be trusted, that all media is created in bad faith, which of course prompts discussions of a crisis of democracy because how can a population make informed decisions without ‘trustworthy’ sources.
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.
…when first we practice to deceive…Walter Scott
Prof Noel Sharkey has written a thoughtful, informative and entertaining piece for Forbes (so, for a general audience) that does some unpacking of ‘Sophia’ with reference to the history of ‘show robots’ (such as the Westinghouse show robots of the the mid-C20, like Elektro, and of course Honda’s Asimo). It’s worth reading the piece in full but here’s a couple of choice clips:
Sophia is not the first show robot to attain celebrity status. Yet accusations of hype and deception have proliferated about the misrepresentation of AI to public and policymakers alike. In an AI-hungry world where decisions about the application of the technologies will impact significantly on our lives, Sophia’s creators may have crossed a line. What might the negative consequences be? To get answers, we need to place Sophia in the context of earlier show robots.
The tradition extends back to the automata precursors of robots in antiquity. Moving statues were used in the temples of ancient Egypt and Greece to create the illusion of a manifestation of the gods. Hidden puppeteers pulled ropes and spoke with powerful booming voices emitted from hidden tubes. This is not so different from how show robots like Sophia operate today to create the illusion of a manifestation of AI.
For me, the biggest problem with the hype surrounding Sophia is that we have entered a critical moment in the history of AI where informed decisions need to be made. AI is sweeping through the business world and being delegated decisions that impact significantly on peoples lives from mortgage and loan applications to job interviews, to prison sentences and bail guidance, to transport and delivery services to medicine and care.
It is vitally important that our governments and policymakers are strongly grounded in the reality of AI at this time and are not misled by hype, speculation, and fantasy. It is not clear how much the Hanson Robotics team are aware of the dangers that they are creating by appearing on international platforms with government ministers and policymakers in the audience.
Let’s begin with a postulate: there is either no “AI” – artificial intelligence – or every intelligence is, in fact, in some way artificial (following a recent talk by Bernard Stiegler). In doing so we commence from an observation that intelligence is not peculiar to one body, it is shared. A corollary is that there is no (‘human’) intelligence without artifice, insofar as we need to exteriorise thought (or what Stiegler refers to as ‘exosomatisation’) for that intelligence to function – as language, in writing and through tools – and that this is inherently collective. Further, we might argue that there is no AI. Taking that suggestion forward, we can say that there are, rather, forms of artificial (or functional) stupidity, following Alvesson & Spicer (2012: p. 1199), insofar as it inculcates forms of lack of capacity: “characterised by an unwillingness or inability to mobilize three aspects of cognitive capacity: reflexivity, justification, and substantive reasoning”. Following Alvesson & Spicer [& Stiegler] we might argue that such forms of stupidity are necessary passage points through our sense-making in/of the world, thus are not morally ‘wrong’ or ‘negative’. Instead, the forms of functional stupidity derive from technology/techniques are a form of pharmakon – both enabling and disabling in various registers of life.
Given such a postulate, we might categorise “AI” in particular ways. We might identify ‘AI’ not as ‘other’ to the ‘human’ but rather a part of our extended (exosomatic) capacities of reasoning and sense. This would be to think of AI ‘organologically’ (again following Stiegler) – as part of our widening, collective, ‘organs’ of action in the world. We might also identify ‘AI’ as an organising rationale in and of itself – a kind of ‘organon’ (following Aristotle). In this sense “AI” (the discipline, institutions and the outcome of their work [‘an AI’]) is/are an organisational framework for certain kinds of action, through particular forms of reasoning.
It would be tempting (in geographyland and across particular bits of the social sciences) to frame all of this stemming from, or in terms of, an individual figure: ‘the subject’. In such an account, technology (AI) is a supplement that ‘the human subject’ precedes. ‘The subject’, in such an account, is the entity to which things get done by AI, but also the entity ultimately capable of action. Likewise, such an account might figure ‘the subject’ and it’s ‘other’ (AI) in terms of moral agency/patiency. However, for this postulate such a framing would be unhelpful (I would also add that thinking in terms of ‘affect’, especially through neuro-talk would be just as unhelpful). If we think about AI organologically then we are prompted to think about the relation between what is figured as ‘the human’ and ‘AI’ (and the various other things that might be of concern in such a story) as ‘parasitic’ (in Derrida’s sense) – its a reciprocal (and, in Stiegler’s terms, ‘pharmacological’) relation with no a priori preceding entity. ‘Intelligence’ (and ‘stupidity’ too, of course) in such a formulation proceeds from various capacities for action/inaction.
If we don’t/shouldn’t think about Artificial Intelligence through the lens of the (‘sovereign’) individual ‘subject’ then we might look for other frames of reference. I think there are three recent articles/blogposts that may be instructive.
First, here’s David Runciman in the LRB:
Corporations are another form of artificial thinking machine, in that they are designed to be capable of taking decisions for themselves. Information goes in and decisions come out that cannot be reduced to the input of individual human beings. The corporation speaks and acts for itself. Many of the fears that people now have about the coming age of intelligent robots are the same ones they have had about corporations for hundreds of years.
Second, here’s Jonnie Penn riffing on Runciman in The Economist:
To reckon with this legacy of violence, the politics of corporate and computational agency must contend with profound questions arising from scholarship on race, gender, sexuality and colonialism, among other areas of identity.
A central promise of AI is that it enables large-scale automated categorisation. Machine learning, for instance, can be used to tell a cancerous mole from a benign one. This “promise” becomes a menace when directed at the complexities of everyday life. Careless labels can oppress and do harm when they assert false authority.
Finally, here’s (the outstanding) Lucy Suchman discussing the ways in which figuring complex systems of ‘AI’-based categorisations as somehow exceeding our understanding does particular forms of political work that need questioning and resisting:
The invocation of Project Maven in this context is symptomatic of a wider problem, in other words. Raising alarm over the advent of machine superintelligence serves the self-serving purpose of reasserting AI’s promise, while redirecting the debate away from closer examination of more immediate and mundane problems in automation and algorithmic decision systems. The spectacle of the superintelligentsia at war with each other distracts us from the increasing entrenchment of digital infrastructures built out of unaccountable practices of classification, categorization, and profiling. The greatest danger (albeit one differentially distributed across populations) is that of injurious prejudice, intensified by ongoing processes of automation. Not worrying about superintelligence, in other words, doesn’t mean that there’s nothing about which we need to worry.
As critiques of the reliance on data analytics in military operations are joined by revelations of data bias in domestic systems, it is clear that present dangers call for immediate intervention in the governance of current technologies, rather than further debate over speculative futures. The admission by AI developers that so-called machine learning algorithms evade human understanding is taken to suggest the advent of forms of intelligence superior to the human. But an alternative explanation is that these are elaborations of pattern analysis based not on significance in the human sense, but on computationally-detectable correlations that, however meaningless, eventually produce results that are again legible to humans. From training data to the assessment of results, it is humans who inform the input and evaluate the output of the black box’s operations. And it is humans who must take the responsibility for the cultural assumptions, and political and economic interests, on which those operations are based and for the life-and-death consequences that already follow.
All of these quotes more-or-less exhibit my version of what an ‘organological’ take on AI might look like. Likewise, they illustrate the ways in which we might bring to bear a form of analysis that seeks to understand ‘intelligence’ as having ‘supidity’as a necessary component (it’s a pharmkon, see?), which in turn can be functional (following Alvesson & Spicer). In this sense, the framing of ‘the corporation’ from Runciman and Penn is instructive – AI qua corporation (as a thing, as a collective endeavour [a ‘discipline’]) has ‘parasitical’ organising principles through which play out the pharmacological tendencies of intelligence-stupidity.
I suspect this would also resonate strongly with Feminist Technology Studies approaches (following Judy Wajcman in particular) to thinking about contemporary technologies. An organological approach situates the knowledges that go towards and result from such an understanding of intelligence-stupidity. Likewise, to resist figuring ‘intelligence’ foremost in terms of the sovereign and universal ‘subject’ also resists the elision of difference. An organological approach as put forward here can (perhaps should[?]) also be intersectional.
That’s as far as I’ve got in my thinking-aloud, I welcome any responses/suggestions and may return to this again.
If you’d like to read more on how this sort of argument might play out in terms of ‘agency’ I blogged a little while ago.
ADD. If this sounds a little like the ‘extended mind‘ (of Clark & Chalmers) or various forms of ‘extended self’ theory then it sort of is. What’s different is the starting assumptions: here, we’re not assuming a given (a priori) ‘mind’ or ‘self’. In Stiegler’s formulation the ‘internal’ isn’t realised til the external is apprehended: mental interior is only recognised as such with the advent of the technical exterior. This is the aporia of origin of ‘the human’ that Stiegler and Derrida diagnose, and that gives rise to the theory of ‘originary technics’. The interior and exterior, and with them the contemporary understanding of the experience of being ‘human’ and what we understand to be technology, are mutually co-constituted – and continue to be so [more here]. I choose to render this in a more-or-less epistemological, rather than ontological manner – I am not so much interested in the categorisation of ‘what there is’, rather in ‘how we know’.
Via Nancy Baym.
All those digits aren’t illegit,
they got it all mapped out for you…
Worth a listen/watch:
A few more bits on how automation gets gendered in particular kinds of contexts and settings. In particular, the identification of ‘home’ or certain sorts of intimacy with certain kinds of domestic or caring work that then gets gendered is something that has been increasingly discussed.
Two PhD researchers I am lucky enough to be working with, Paula Crutchlow (Exeter) and Kate Byron (Bristol), have approached some of these issues from different directions. Paula has had to wrangle with this in a number of ways in relation to the Museum of Contemporary Commodities but it was most visible in the shape of Mikayla, the hacked ‘My Friend Cayla Doll’. Kate is doing some deep dives on the sorts of assumptions that are embedded into the doing of AI/machine learning through the practices of designing, programming and so on. They are not, of course, alone. Excellent work by folks like Kate Crawford, Kate Devlin and Gina Neff (below) inform all of our conversations and work.
Here’s a collection of things that may provoke thought… I welcome any further suggestions or comments 🙂
Alexa is female. Why? As children and adults enthusiastically shout instructions, questions and demands at Alexa, what messages are being reinforced? Professor Neff wonders if this is how we would secretly like to treat women: ‘We are inadvertently reproducing stereotypical behaviour that we wouldn’t want to see,’ she says.Prof Gina Neff in conversation with Ruth Abrahams, OII.
it has been reported that female-sounding assistive chatbots regularly receive sexually charged messages. It was recently cited that five percent of all interactions with Robin Labs, whose bot platform helps commercial drivers with routes and logistics, is sexually explicit. The fact that the earliest female chatbots were designed to respond to these suggestionsVidisha Mishra and Madhulika Srikumar – Predatory Data: Gender Bias in Artificial Intelligence
deferentially or with sass was problematic as it normalised sexual harassment.
“Consistently representing digital assistants as female…hard-codes a connection between a woman’s voice and subservience.”Stop Giving Digital Assistants Female Voices – Jessica Nordell, The New Republic
This video of a panel session at HKW entitled “Speaking to Racial Conditions Today” is well-worth watching.
Follow this link (the video is not available for embedding here).
Inputs, discussions, Mar 15, 2018. With Zimitri Erasmus, Maya Indira Ganesh, Ruth Wilson Gilmore, David Theo Goldberg, Serhat Karakayali, Shahram Khosravi, Françoise Vergès
English original version
All of a sudden the summer is nearly over, apparently, and the annual conference of the Royal Geographical Society with the Institute of British Geographers is fast approaching, this year in Cardiff.
I am convening a double session on the theme of ‘New geographies of automation?’, with two sessions of papers by some fantastic colleagues that promise to be really interesting. I am really pleased to have this opportunity to invite colleagues to collectively bring their work into conversation around a theme that is not only a contemporary topic in academic work but also, significantly, a renewed topic of interest in the wider public.
There are two halves of the session, broadly themed around ‘autonomy’ and ‘spacings’. Please find below the abstracts for the session.
Details: Sessions 92 & 123 (in slots 3 & 4 – 14:40-16:20 & 16:50-18:30) | Bates Building, Lecture Theatre 1.4
New Geographies of Automation? (1): Autonomy
1.1 An Automative Imagination
Samuel Kinsley, University of Exeter
This paper sets out to review some of the key ways in which automation gets imagined – the sorts of cultural, economic and social forms of imagination that are drawn upon and generated when discussing how automation works and the kinds of future that may come as a result. The aim here is not to validate/invalidate particular narratives of automation – but instead to think about how they are produced and what they tell us about how we tell stories about what it means to be ‘human’, who/what has agency and what this may mean for how we think politically and spatially. To do this the concept of an ‘automative imagination’ is proposed as a means of articulating these different, sometimes competing – sometimes complementary, orientations towards automation.
1.2 The Future of Work: Feminist Geographical Engagements
Julie MacLeavy (Geographical Sciences, University of Bristol)
This paper considers the particular pertinence of feminist geographical scholarship to debates on the ‘future of work’. Drawing inspiration from Linda McDowell’s arguments that economic theories of epochal change rest on the problematic premise that economic and labour market changes are gender-neutral, it highlights the questions that are emerging from feminist economic geography research and commentary on the reorganisation of work, workers’ lives and labour markets. From this, the paper explores how feminist and anti-racist politics connect with the imagination of a ‘post-work’ world in which technological advancement is used to enable more equitable ways of practice (rather than more negative effects such as the intensification of work lifestyles). Political responses to the critical challenges that confront workers in the present moment of transformation are then examined, including calls for Universal Basic Income, which has the potential to reshape the landscape of labour-capital relations.
1.3 Narrating the relationship between automation and the changing geography of digital work
Daniel Cockayne, Geography and Environmental Management, University of Waterloo
Popular narratives about the relationship between automation and work often make a straightforward causal link between technological change and deskilling, job loss, or increased demand for jobs. Technological change – today, most commonly, automation and AI – is often scripted as threatening the integrity of labor, unionization, and traditional working practices or as creating more demand for jobs, in which the assumption is the more jobs the better. These narratives elide a close examination of the politics of work that include considerations of domestic and international racialized and gendered divisions of labor. Whether positive or negative, the supposed inevitability of technological transition positions labor as a passive victim of these changes, while diverting attention away from the workings of international financialized capital. Yet when juxtaposed against empirical data, straightforward cause and effect narratives become more complex. The unemployment rate in North America has been the lowest in 40 years (4.1% in the USA and 5.7% in Canada), which troubles the relationship between automation and job loss. Yet, though often touted by publications like The Economist as a marker of national economic well-being, unemployment rates ignore the kinds of work people are doing, effacing the qualitative changes in work practices over time. I examine these tropes and their relationship to qualitative changes in work practices, to argue that the link between technological change and the increasing precaratization of work is more primary than the diversionary relationship between technological change and job loss and gain or deskilling.
1.4 Sensing automation
David Bissell, University of Melbourne
Processes of industrial automation are intensifying in many sectors of the economy through the development of AI and robotics. Conventional accounts of industrial automation stress the economic imperatives to increase economic profitability and safety. Yet such coherent snapped-to-grid understandings risk short-circuiting the complexity and richness of the very processes and events that compose automation. This paper draws from and reflects through a series of encounters with workers engaged in the increasingly automated mining sector in Australia. Rather than thinking these encounters solely through their representational dimensions with an aim to building a coherent image of what automation is, this paper is an attempt at writing how automation becomes differently disclosed through the aesthetic dimensions of encounters. It acknowledges how automation is always caught up in multiple affective and symbolic ecologies which create new depths of association. Developing post-phenomenological thought in cultural geography, this paper articulates some of the political and ethical stakes for admitting ambiguity, incoherence and confusion as qualities of our relations with technological change.
1.5 Technological Sovereignty, Post-Human Subjectivity, and the Production of the Digital-Urban Commons
Casey Lynch (School of Geography and Development, University of Arizona)
As cities become increasingly monitored, planned, and controlled by the proliferation of digital technologies, urban geographers have sought to understand the role of software, big data, and connected infrastructures in producing urban space (French and Thrift 2002; Dodge, Kitchin, and Zook, 2009). Reflections on the “automatic production of space” have raised questions about the role and limitations of “human” agency in urban space (Rose 2017) and the possibilities for urban democracy. Yet, this literature largely considers the proliferation of digital infrastructures within the dominant capitalist, smart-city model, with few discussions of the possibilities for more radically democratic techno-urban projects. Engaging these debates, this paper considers alternative models of the techno-social production of urban space based around the collective production and management of a common digital-urban infrastructure. The paper reflects on the notion of “technological sovereignty” and the case of Guifinet, the world’s largest “community wireless network” covering much of Catalonia. The paper highlights the way its decentralized, DIY mode of producing and maintaining digital urban infrastructure points to the possibilities for more radically democratic models of co-production in which urban space, technological infrastructures, and subjectivities are continually reshaped in relation. Through this, the paper seeks to contribute to broader discussions about the digitalization of urban space and the possibilities for a radical techno-politics.
New Geographies of Automation? (2): Spacings
2.1 The urbanisation of robotics and automated systems – a research agenda
Andy Lockhart* (email@example.com), Aidan While* (firstname.lastname@example.org), Simon Marvin (email@example.com), Mateja Kovacic (firstname.lastname@example.org), Desiree Fields (email@example.com) and Rachel Macrorie (firstname.lastname@example.org) (Urban Institute, University of Sheffield)
Pronouncements of a ‘fourth industrial revolution’ or ‘second machine age’ have stimulated significant public and academic interest in the implications of accelerating automation. The potential consequences for work and employment have dominated many debates, yet advances in robotics and automated systems (RAS) will have profound and geographically uneven ramifications far beyond the realm of labour. We argue that the urban is already being configured as a key site of application and experimentation with RAS technologies. This is unfolding across a range of domains, from the development of autonomous vehicles and robotic delivery systems, to the growing use of drone surveillance and predictive policing, to the rollout of novel assistive healthcare technologies and infrastructures. These processes and the logics underpinning them will significantly shape urban restructuring and new geographies of automation in the coming years. However, while there is growing research interest in particular domains, there remains little work to date which takes a more systemic view. In this paper we do three things, which look to address this gap and constitute the contours of a new urban research agenda. First, we sketch a synoptic view of the urbanisation of RAS, identifying what is new, what is being enabled as a result and what should concern critical scholars, policymakers and the wider public in debates about automation. Second, we map out the multiple and sometimes conflicting rationalities at play in the urbanisation of RAS, which have the potential to generate radically different urban futures, and may address or exacerbate existing socio-spatial inequalities and injustices. Third, and relatedly, we pose a series of questions for urban scholars and geographers, which constitute the basis for an urgent new programme of research and intervention.
2.2 Translating the signals: Utopia as a method for interrogating developments in autonomous mobility
Thomas Klinger1, 2
1. Institute of Human Geography, Goethe-University Frankfurt am Main
2. School of Geography and the Environment, University of Oxford
Connected and autonomous vehicles (CAVs) are often presented as technological ‘solutions’ to problems of road safety, congestion, fuel economy and the cost of transporting people, goods and services. In these dominant techno-economic narratives ‘non-technical’ factors such as public acceptance, legal and regulatory frameworks, cost and investment in testing, research and supporting infrastructure are the main ‘barriers’ to the otherwise steady roll-out of CAVs. Drawing on an empirical case study of traffic signalling, we trace the implications that advances in vehicle autonomy may have for such mundane and taken-for-granted infrastructure. We employ the three modes of analysis associated with Levitas’ (2013) ‘utopia as a method’. Starting with the architectural mode we identify the components, actors and visions underpinning ‘autonomobility’. The archaeological mode is then used to unpack the assumptions, contradictions and possible unintended effects that CAVs may have for societies. In the ontological mode we speculate upon the types of human and non-human subjectivities and agencies implied by alleged futures of autonomous mobility. Through this process we demonstrate that techno-economic accounts overemphasise the likely scale, benefits and impacts these advances may have for societies. In particular, they overlook how existing automobile-dependent mobility systems are the outcome of complex assemblages of social and technical elements (e.g., cars, car-drivers, roads, petroleum supplies, novel technologies and symbolic meanings) which have become interlinked in systemic and path-dependent ways over time. We conclude that utopia as method may provide one approach by which geographers can interrogate and opening up alarmist/boosterish visions of autonomobility and automation.
2.3 Automating the laboratory? Folding securities of malware
Andrew Dwyer, University of Oxford
Folding, weaving, and stitching is crucial to contemporary analyses of malicious software; generated and maintained through the spaces of the malware analysis laboratory. Technologies entangle (past) human analysis, action, and decision into ‘static’ and ‘contextual’ detections that we depend on today. A large growth in suspect software to draw decisions on maliciousness have driven a movement into (seemingly omnipresent) machine learning. Yet this is not the first intermingling of human and technology in malware analysis. It draws on a history of automation, enabling interactions to ‘read’ code in stasis; build knowledges in more-than-human collectives; allow ‘play’ through a monitoring of behaviours in ‘sandboxed’ environments; and draw on big data to develop senses of heuristic reputation scoring.
Though we can draw on past automation to explore how security is folded, made known, rendered as something knowable: contemporary machine learning performs something different. Drawing on Louise Amoore’s recent work on the ethics of the algorithm, this paper queries how points of decision are now more-than-human. Automation has always extended the human, led to loops, and driven alternative ways of living. Yet the contours, the multiple dimensions of the neural net, produce the malware ‘unknown’ that have become the narrative of the endpoint industry. This paper offers a history of the automation of malware analysis from static and contextual detection, to ask how automation is changing how cyberspace becomes secured and made governable; and how automation is not something to be feared, but tempered with the opportunities and challenges of our current epoch.
2.4 Robots and resistance: more-than-human geographies of automation on UK dairy farms
Chris Bear (Cardiff University; email@example.com)
Lewis Holloway (University of Hull; firstname.lastname@example.org)
This paper examines the automation of milking on UK dairy farms to explore how resistance develops in emerging human-animal-technology relations. Agricultural mechanisation has long been celebrated for its potential to increase the efficiency of production. Automation is often characterised as continuing this trajectory; proponents point to the potential for greater accuracy, the removal of less appealing work, the reduction of risks posed by unreliable labour, and the removal of labour costs. However, agricultural mechanisation has never been received wholly uncritically; studies refer to practices of resistance that have developed due to fears around (for instance) impacts on rural employment, landscapes, ecologies and traditional knowledge practices. Drawing on interviews with farmers, observational work on farms and analysis of promotional material, this paper examines resistant relations that emerge around the introduction of Automated Milking Systems (AMS) on UK dairy farms. While much previous work on resistance to agricultural technologies has pitted humans against machines, we follow Foucault in arguing that resistance can be heterogeneous and directionally ambiguous, emerging through ‘the capillary processes of counter-conduct’ (Holloway and Morris 2012). These capillary processes can have complex geographies and emerge through more-than-human relations. Where similar conceptualisations have been developed previously, technologies continue to appear rather inert – they are often the tools by which humans attempt to exert influence, rather than things which can themselves ‘object’ (Latour 2000), or which are co-produced by other nonhumans rather than simply imposed or applied by humans. We begin, therefore, to develop a more holistic approach to the geographies of more-than-human resistance in the context of automation.
2.5 Fly-by-Wire: The Ironies of Automation and the Space-Times of Decision-Making
Sam Hind (University of Siegen; email@example.com)
This paper presents a ‘prehistory’ (Hu 2015) of automobile automation, by focusing on ‘fly-by-wire’ control systems in aircraft. Fly-by-wire systems, commonly referred to as ‘autopilots’ work by translating human control gestures into component movements, via digital soft/hardware. These differ historically from mechanical systems in which pilots have direct steering control through a ‘yoke’ to the physical components of an aircraft (ailerons etc.), via metal rods or wires. Since the launch of the first commercial aircraft with fly-by-wire in 1988, questions regarding the ‘ironies’ or ‘paradoxes’ of automation (Bainbridge 1983) have continued to be posed. I look at the occurrence of ‘mode confusion’ in cockpits to tease out one of these paradoxes; using automation in the aviation industry as a heuristic lens to analyze automation of the automobile. I then proceed by detailing a scoping study undertaken at the Geneva Motor Show in March this year, in which Nissan showcased an autonomous vehicle system. Unlike other manufacturers, Nissan is pitching the need for remote human support when vehicles encounter unexpected situations; further complicating and re-distributing navigational labour in, and throughout, the driving-machine. I will argue that whilst such developments plan to radically alter the ‘space-times of decision-making’ (McCormack and Schwanen 2011) in the future autonomous vehicle, they also exhibit clear ironies or paradoxes found similarly, and still fiercely discussed, in the aviation industry and with regards to fly-by-wire systems. It is wise, therefore, to consider how these debates have played out – and with what consequences.