From the Daily Mail, 7th July 1956.


Spatial Machinations
From the Daily Mail, 7th July 1956.

I’m doing some archival digging… I guess we’re all historical geographers at some level đ
For your consideration:


Via Phoebe Moore.
INTERNATIONAL LABOUR PROCESS CONFERENCE
Artifical Intelligence, Technology and Work
ILPC 2019 Special Stream No. 5
Please submit abstracts via the International Labour Process Conference website (ilpc.org.uk) by the deadline of 26 October 2018.
Of all the social changes occurring over the past six or seven decades, perhaps most fascinating is the integration of computers and machines into the fabric of our lives and organizations. Machines are rapidly becoming direct competitors with humans for intelligence and decision-making powers. This is important for research in international labour process because artificial intelligence (AI) brings about challenges and questions for how organizations, globally, are designed and established with respective human resources planning and execution and industrial relations negotiations. We start with John McCarthyâs term, who both invented and defined AI as processes that are âmaking a machine behave in ways that would be called intelligent if humans were so behavingâ in 1955. At the origin of the term, AI aligned humans directly with machines, expecting machines to behave symbolically like humans. Over time, programmers working on neural networks and machine learning have emphasised the cognitive rather than symbolic. Now, AI is seen to have comparable capabilities to humans in both routine and non-routine ways, leading to new possibilities for automation. This draws on huge amounts of data often produced originally by humans. In fact, every time we enter a search term on a computer we add to and train machinic âintelligence.â Every day, billions of actions are captured as part of this process, contributing to the development of AI. In doing so, people provide under-recognised cognitive and immaterial labour.
Therefore, this streams looks at the conditions and circumstances whereby machines begin to have the capacity to influence and become integrated in to humansâ ways of thinking, decision-making, working. It also considers the possibilities of AI in resistance against neoliberal and even authoritarian capitalism in the global north and south. AI is a broad term that identifies the pinnacle of machine capabilities that have recently become possible based on the amount of a) extensive big data that has become available in organisations, b) data analytical tools where programmers can identify what to track based on this data and what algorithms will allow one to gain the insights of interest, c) machine learning, where patterns across data sets can be identified and d) AI, where the final frontier has become the ability of pattern recognition across myriad data sets that have already identified their own patterns. When applied to work and work design, the primary goals are efficiency, market capture, and control over workers.
The rise of autonomous machines leads to philosophical questions that Marx engaged with in theories of objectification and alienation. Later, critical theorists have dealt with these questions in labour process research, where technologies and digitalization have created unprecedented concerns for how workplaces and work design are structured and control and resistance are pursued. In particular, the gig economy has become the frontline of these new changes. Workers here are now facing automation of the management function, supervised and even fired (or âdeactivatedâ) without human intervention nor interaction. This is creating intensified and precarious working conditions, leading to fragmentation over digital platforms and platform management methods (Moore and Joyce 2018), as well as new forms of resistance and solidarities. These are all happening while their own work is under the threat of digitalization, where control and resistance have taken new forms and humans are in danger of becoming resources for tools (see Moore 2018a, 2018b; Woodcock, 2017; Waters and Woodcock, 2017).
Ultimately, across the economy, technology and its integration may be leading to organisations that take on a life of their own. Human resource decisions are increasingly taken by algorithms, where new human resources techniques integrate machine learning to achieve a new technique called âpeople analyticsâ where data patterns are used to make workplace decisions for hiring/firing/talent predictions, creating significant threats to the possibilities of workplace organising and social justice. Sometimes, AI-based decisions lead to automating aspects of the workplace, for example, in the case of wearable devices in factories that allow human resource calculations based on AI and location-management by GPS and RFID systems. In these ways and others, AI processes inform a number of decision-making processes and digitalized management methods that have led to significant changes to workplaces and working conditions. If machines can deal with ethically based questions and begin to mimic the nuances of experiences and human judgement, will they become participants in humansâ already manifest âlearned helplessnessâ? While currently, humans train AI with the use of big data, could machines begin to train humans to be helpless?
This call builds upon the âArtificial Intelligence. A service revolution?â stream that featured at the 36th ILPC conference in Buenos Aires. This yearâs stream is intended as a forum to bring together researchers engaged with the topics of labour process, political economy, technology, and AI to discuss this topic. We invite submissions on the following topics (not limited to, but also considering the need not to overlap with other streams):
-The effect of AI on the labour process where control and resistance rub against debates about exploitation Vs empowerment
-The implication of algorithmic management and control on the labour process, work replacement, and/or intensification from the factory to the office
-The âblack boxâ of AI and related practices, algorithmic decision support, people analytics, performance management
-The impact of AI on the Global South: geographies and variegation of AI implementation, direct and indirect impact on jobs and differential effects of diverse socio-political setups
-Resistance and organising against/with AI and social media
Special Issue: We are also considering a submission for a journal special issue (though contributions may be requested before the conference). Please email Phoebe Moore pm358@leicester.ac.uk immediately if this is of interest.
Stream Organisers:
Please feel free to contact the stream organisers with any informal inquiries.
For information on the ILPC 2019 and the Calls for Papers for the General Conference and the other Special Streams please go to https://www.ilpc.org.uk/
References
Moore, P. (2018a): The Quantified Self in Precarity: Work, Technology and What Counts, Advances in Sociology series (Abingdon, Oxon: Routledge).
Moore, P. (2018b): âThe Threat of Physical and Psychosocial Violence and Harassment in Digitalized Workâ International Labour Organization, ACTRAV, Geneva: Switzerland.
Woodcock, J. (2017): Working the Phones: Control and Resistance in Call Centres, London: Pluto.
Waters, F. and Woodcock, J. (2017): âFar From Seamless: a Workersâ Inquiry at Deliverooâ, Viewpoint Magazine.
I was sitting in my office, which I actually really like (for reasons which may be explained in a bit), when I began writing this post â thinking about the tendency at present for sitting alone in an office to be the sort of ‘everyday’ norm. I suspect this is a common experience for many academics. I also recognise that it is actually a privilege to have my own office, something I really do value, but that’s not the focus of this post. I am also near certain that others have written much the same thing before in different guises. What I want to do is argue for the keeping or reinstating of ‘common rooms’, not for nostalgic reasons but for pragmatic ones.
Summer working in a building that is mostly empty, and so sitting alone quite a bit of the time, makes me think about the nature of my job at present. It also prompts me to remember what it was like five years ago when I started the job I currently have. It makes me think of the stripping away of things that some might think of as quaint, old fashioned, out-of-date and superfluous but I tend to think might actually be really important to the efficient functioning of academic institutions.
We used to have a “Senior Common Room” at the end of my corridor. It was just the one, shared, PGR/staff ‘common room’ for a very large building (the Amory building, in Exeter, is a warren and is home to about seven departments) but it had a little cafĂ©, the people that worked there were nice – you knew them by name, and it meant that colleagues would gravitate there.
This was a space colleagues would choose to go to. Where possible, patterns I had become used to in other institutions were sort of observed â people would go for coffee around 10:45, some still do, and often arrange to be there for lunch too. This was a room in which you would feel comfortable to take a visiting academic, you may well bump into colleagues. You could learn what others are working on, maybe share tips about mundane teaching issues (the speakers in that seminar room still don’t work etc). Some years ago I doorstepped a colleague at a London university whilst killing time in advance of an event and was taken to a nice, if well-worn, common room and we bumped into colleagues and I learned things I do not think I otherwise would have.
Now, this post is not merely the yearnings of a privileged white male academic pining for a time that only really existed, and was sent up, in campus novels by Bradbury and Lodge. Neither do I want to rehearse that peculiar line about how academic life is special and different. I think many of the issues here are relatable to other kinds of work. Nevertheless, I do think that the kinds of work we do are made better, work better, if we are able to talk and share ideas in ways that are conducive to that communcation taking place. While I think they help – I do not think that a social media channel or email list is sufficient. I guess, this post is also prompted by an anecdote that I’d like to relate, something I observed a while ago but that has stayed with me.
I was looking for our relocated administrators, now no longer ‘geography’ but paired back and blitzed together into a ‘hub’ for the whole building (yes, all seven departments). I was dithering along an unfamiliar corridor on another floor of my building, following room numbers, when I happened across a group of academics talking. Mugs in hand they were stood speaking in semi-hushed tones, somewhat conspiratorially. As I came closer and overheard their conversation it was the usual sort of mix of teaching and research chat. I passed on, in search of the elusive administrators. Having completed my task and returned down the corridor I again passed the group of colleagues stood in the same place talking. Around 15 minutes later I needed to return to the admin office and so strode more confidently back down the same corridor to find the group of colleagues had been augmented by a couple and an impromptu, semi-casual, research meeting was taking place.
I suppose the reason this brief, fairly unremarkable, episode has stuck with me is that this is the reality of working in my building. You talk in corridors, there is nowhere else to go. The ‘common room’ is still sort of there. It has shrunk to accommodate further offices and has been redecorated in the soulless corporate style you will recognise if you work in a university. There are no facilities – so you need to find one of the small kitchens to make your own tea or coffee in advance. We can book seminar rooms for meetings, but that requires notice and you’re told off if you are caught taking in your coffee. Of course teaching rooms are not necessarily conducive to certain kinds of discussion either, with rows of tables and so on.
In the meantime, the building is subject to wall-shaking redevelopment to accommodate the new student ‘hub’, taking the place of our departmental offices. There will be a cafĂ© and social space for the students. So, many of us drink coffee and eat lunch at our desks and will continue to do so. Some go to the cafĂ©s on campus, but I find them rather expensive and it wastes a lot of time with crossing campus and queuing. It is also tacitly clear that these facilities are not intended for staff, they are really for students.
Quite a lot of colleagues work from home when they do not ‘have to’ be on campus. This is difficult for me. We no longer have a ‘spare’ room and so I sit at a desk in the corner of the kitchen. I have no space to store work-related things and so when working from home I have to remember to bring books etc. back and forth in my bag. It is by no means terrible but I find it hard to work from home. I like having an office â all of the things it enables. I would like to bump into colleagues more too. Sitting alone in an office is helpful for concentration and ‘getting things done’ but it is not helpful if it’s the only thing you do. It can be isolating. I value those times when colleagues take the initiative and knock on the door to chat but it can also be an inconvenient moment, with a crying student etc.
Space to meet is, I think, important for a happy and effective working environment in a university department. It also requires a commitment from us, the ‘workers’ to perform the function of commonality â we need to make the time. A common refrain is that there is no time, and I suspect that really is true for many, but even if it’s just once a week, or every so often, I’d like to think that taking the time to be with colleagues and to learn about what they’re doing is an uncontroversially positive thing to do. If we also argue for a little more time to enable this, then all sorts of positive research collaborations, teaching innovations and so on might actually arise â not because of top-down pressure from a person with “chancellor” in their job title but because we actually like to do our jobs.
I am not arguing for the reinstatement of some sort of peculiar system in which a particular class of academic staff can remain aloof in their “Senior Common Room”. I am arguing that, given the kinds of work we do, providing a space to talk, to connect â actually makes us more healthy and more productive. I would also argue that, as lovely as they can be, sometimes you just need to do this away from the students.
For all we might (perhaps rightly) castigate and deride companies like Google, they do understand and take seriously that people work better when there are common spaces and facilities to support less-formal ways of being together. It leads to more productive workers, I am confident that they wouldn’t be doing it otherwise – however ‘cool’ it might look.
So, a modest plea â fight for your common room and use it. I don’t think I’ve taken that seriously enough, so I’ll try too. We don’t know what we’ve got til it’s gone.
I’ve just done a rough edit of some snippets from BBC programmes that I think shows an interesting pattern to the ways that automation has been discussed by the UK national broadcaster over the last 40 years. In each case, automation is a significant issue – it needs to be urgently addressed, but that hasn’t yet happened.
Out of the three programmes, the first two are fairly significant in their onward influence.
The first, the 1978 “Now the Chips Are Down” Horizon episode was reportedly a significant influence for the BBC’s own Computer Literacy Project, which spawned the BBC Micro Computer.
The second, the 1980 (middle of three) episode(s) of “The Silicon Factor” was a part of the Computer Literacy Project. Alongside the three-part series, the producers created a report (for the BBC Continuing Education Department): “Microelectronics“, which was commissioned by the outgoing late-1970s Labour government’s Department for Education and the Manpower Services Commission. I thoroughly recommend watching the programmes and looking at the report if you’re interested in the histories of computing and automation in the UK.
The third, as far as I know â less significant in it’s onward influence, is a 2015 episode of Panorama: “Could a Robot Do My Job?” Interesting here because the rhetoric is nearly identical to that of “The Silicon Factor” â we need to take advantage of the revolution.
I’ve got more to say about this and I need to do a bit more thinking but wanted to share, because I think it’s interesting! This video (or a revised version) will form a part of my paper for a double session on ‘New Geographies of Automation(?)‘ at the RGS-IBG conference in August 2018 concerning the ways that we imagine automation.
From KPMG’s Strategic Visions on the Sourcing Market 2016, p. 32. Via Jamie Peck’s excellent Offshore.
How will you manage fallout from displaced labor?
The automation of human jobs may cause some unrest, so prepare to have honest, open discussions with your organization. Resistance may come not only from the workers in automatable roles but also from directors who may fear erosion in their span of control, as they potentially go from managing employees to managing bots.

Saw this via Twitter. Looks good.
How are bodies produced under capitalism?
How, in turn, does capitalism make bodies productive?
How is the body (and knowledge of the body) shaped by demands of production, consumption and exchange, and how can these logics be resisted, challenged and overcome?
These are the questions at the heart of François GuĂ©ry and Didier Deleuleâs Productive Body. First published in French in 1972, The Productive Body asks how the human body and its labour have been expropriated and re-engineered through successive stages of capitalism. The Productive Body challenges us to rethink the relationships between the biological and the social; the body and the mind; power and knowledge; discipline and control. Finally, it invites us to think about the body as a site of resistance and revolutionary potential.

At this one-day, interdisciplinary conference, we invite scholars and activists to assess the contribution of The Productive Body, and to address its relevance as a theoretical tool for understanding and challenging contemporary ideologies of bodily health, efficiency and productivity.
We invite submissions from scholars, activists and artists for 20-minute papers, or 10-minute provocations on the relationships â past and present â between capitalism, work and the body. Collaborative papers are welcome, and proposals for longer workshops and panel discussions will also be considered. Please contact the organisers if you are unsure. Proposals that explore or are inspired by any of the following areas are welcome:
Please send abstracts of no more than 300 words to thebodyproductive@gmail.com by 24th August 2018. Submissions are especially encouraged from graduate students, early-career researchers, and groups typically underrepresented in the academy.
This post contains some tabs I have had open in my browser for a while that I’m pasting here both to save them in a place I may remember to look and to share them with others that might find them of interest. I’m afraid I don’t have time, at present, to offer any cogent commentary or analysis – just simply to share…
Untold A.I. â “What stories are we not telling ourselves about A.I?”, Christopher Noessel: An interesting attempt to look at popular, sci-fi stories of A.I. and compare them to contemporary A.I. research manifestos and look at where we might not be telling ourselves stories about the things people are actually trying to do.
The ethics of crashes with self?driving cars: A roadmap â Sven Nyholm: A two-part series of papers [one and two ($$) / one and two (open)] published in Philosophy Compass concerning how to think through the ethical issues associated with self-driving cars. Nyholm recently talked about this with John Danaher on his podcast.
WEF on the Toronto Declaration and the “cognitive bias codex”: A post on the World Economic Forum’s website about “The Toronto Declaration on Machine Learning” on guiding principles for protecting human rights in relation to automated systems. As part of the post they link to a nice diagram about cognitive bias – the ‘cognitive bias codex‘.
RSA report on public engagement with AI: “Our new report, launched today, argues that the public needs to be engaged early and more deeply in the use of AI if it is to be ethical. One reason why is because there is a real risk that if people feel like decisions about how technology is used are increasingly beyond their control, they may resist innovation, even if this means they could lose out on benefits.”
Artificial Unintelligence, Meredith Broussard: “In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitallyâhiring, driving, paying bills, even choosing romantic partnersâthat we have stopped demanding that our technology actually work.”
Data-driven discrimination: a new challenge for civil society: A blogpost on the LSE ‘Impact of Soc. Sci.’ blog: “Having recently published a report on automated discrimination in data-driven systems, J?drzej Niklas and Seeta Peña Gangadharan explain how algorithms discriminate, why this raises concerns for civil society organisations across Europe, and what resources and support are needed by digital rights advocates and anti-discrimination groups in order to combat this problem.”
‘AI and the future of work’ – talk by Phoebe Moore: Interesting talk transcript with links to videos. Snippet: “Human resource and management practices involving AI have introduced the use of big data to make judgements to eliminate the supposed âpeople problemâ. However, the ethical and moral questions this raises must be addressed, where the possibilities for discrimination and labour market exclusion are real. Peopleâs autonomy must not be forgotten.”
Government responds to report by Lords Select Committee on Artificial Intelligence: “The Select Committee on Artificial Intelligence receives the Government response to the report: AI in the UK: Ready, willing and able?, published on 16 April 2018.”
How a Pioneer of Machine Learning Became One of Its Sharpest Critics, Kevin Hartnett – The Atlantic: “Judea Pearl helped artificial intelligence gain a strong grasp on probability, but laments that it still can’t compute cause and effect.”
Saw this via Twitter somehow…
Employment generation is crucial to spreading the benefits of economic growth broadly and to reducing global poverty. And yet, emerging economies face a contemporary challenge to traditional pathways to employment generation: automation, digitalization, and labor-saving technologies. 1.8 billion jobsâor two-thirds of the current labor force of developing countriesâare estimated to be susceptible to automation from todayâs technological standpoint. Cumulative advances in industrial automation and labor-saving technologies could further exacerbate this trend. Or will they? In this paper we: (i) discuss the literature on automation; and in doing so (ii) discuss definitions and determinants of automation in the context of theories of economic development; (iii) assess the empirical estimates of employment-related impacts of automation; (iv) characterize the potential public policy responses to automation; and (v) highlight areas for further exploration in terms of employment and economic development strategies in developing countries. In an adaption of the Lewis model of economic development, the paper uses a simple framework in which the potential for automation creates âunlimited supplies of artificial laborâ particularly in the agricultural and industrial sectors due to technological feasibility. This is likely to create a push force for labor to move into the service sector, leading to a bloating of service-sector employment and wage stagnation but not to mass unemployment, at least in the short-to-medium term.
This event looks really interesting!
Via Pip Thornton.
How might we draw on feminist critical thought to reimagine data practices and data work? Join us for a public talk with Lauren Klein (Assistant Professor, Georgia Tech) to discuss her recent work on data feminism. Hosted by Jonathan Gray at the Department for Digital Humanities at King’s College London.
With their ability to depict hundreds, thousands, and sometimes even millions of relationships at a single glance, visualizations of data can dazzle, inform, and persuade. It is precisely this power that makes it worth asking: “Visualization by whom? For whom? In whose interest? Informed by whose values?” These are some of the questions that emerge from what we call data feminism, a way of thinking about data and its visualization that is informed by the past several decades of feminist critical thought. Data feminism prompts questions about how, for instance, challenges to the male/female binary can also help challenge other binary and hierarchical classification systems. It encourages us to ask how the concept of invisible labor can help to expose the invisible forms of labor associated with data work. And it points to how an understanding of affective and embodied knowledge can help to expand the notion of what constitutes data and what does not. Using visualization as a starting point, this talk works backwards through the data-processing pipeline in order to show how a feminist approach to thinking about data not only exposes how power and privilege presently operate in visualization work, but also suggests how different design principles can help to mitigate inequality and work towards justice.
Lauren Klein is an assistant professor in the School of Literature, Media, and Communication at Georgia Tech, where she also directs the Digital Humanities Lab. With Matthew Gold, she editsDebates in the Digital Humanities (University of Minnesota Press), a hybrid print/digital publication stream that explores debates in the field as they emerge. Her literary monograph,Matters of Taste: Eating, Aesthetics, and the Early American Archive, is forthcoming from Minnesota in Spring 2019. She is also at work on two new projects: Data Feminism, co-authored with Catherine DâIgnazio, and under contract with MIT Press, which distills key lessons from feminist theory into a set of principles for the design and interpretation of data visualizations, and Data by Design, which provides an interactive history of data visualization from the eighteenth century to the present.