Geography’s subject

Conceptualisations of a ‘subject’ or subjectivity form part of a theoretical tradition variously theorising who, what and where the ‘human’ is in geography. I don’t want to poorly approximate excellent intellectual histories of human geography (in particular Kevin Cox’s Making Human Geography and Derek Gregory‘s Geographical Imaginations are worth regularly revisiting) but I think it’s nevertheless probably important to remind ourselves of the kinds of geographical imagination with which we continue to make meaning in geography.

Waymarks in the theoretical landscape of geographical tradition might include theories of action, human agency, identity, reflexivity, structure and sovereignty. The latter two on that list might be the most influential in geographical work that took alternative paths to the ‘quantitative revolution’ of the post-WWII period. Political agency and power, considered from all sorts of angles, whether geopolitical or bodily intimate, have formed a longstanding interest for those considering ‘subjecivity’. To pick two key influences for the kind of (Anglophone and basically British) geography I’ve ‘grown up’ in, we can look at the influence of Marx and then literary theory (maybe as assorted flavours of structuralism, post-structuralism, postmodernism etc).

Geographers influenced by Marxian traditions of thought have been perhaps more concerned with the kinds of people who can act or speak in society–who has power, and how. ‘New’ cultural geographers moved towards acknowledging a greater diversity in identities and an attempt to account for a wider gamut of experiences, extending beyond the perceived limits of the ‘human’. The erstwhile reference: The Dictionary of Human Geography contained ‘human agency’ and ‘sovereignty’ entries from the first edition (1981) while an entry for ‘human subjectivity’ did not arrive until the third (1994).

Conceptualisations of ‘the subject’ and subjectivity can be broadly seen to follow the twists and ‘turns’ in geographical thought (don’t take my word for it, look at the entry in the Dictionary of Human Geography). Whereas the figure of the human ‘subject’ of much of mid-20th century geographies carried implications of universalism (homo economicus, or ‘nodes’ in spatial modeling), several theoretical ‘turns’ turned that figure into a problem to be investigated. Perhaps from humanistic geographies onwards, geographers have attempted to wrangle and tease out the contradictions of an all-too-easy to accept ‘simple being’ (Tuan, Space & Place: p. 203). So, for (what Gregory, in Geographical Imaginations calls) ‘post-Marxist’ geographical research the sole subject-positioning of ‘class’ elides too much, such as varying (more or less political) differences in identities, e.g: gender, race and sexuality. There is, of course, lots of work tracing out nuanced arguments for a differentiated and decentred subject, which I cannot hope to do justice to in a blogpost, but maybe we can tease out some of the significant conceptual points of reference.

An attention to the identities and subject positions of those who are not male, not heterosexual, non-white, non-Western and not of the global North is important to subject and subjectivity theorisations. This sort of work mostly occurs in the kinds of geographies collected under sub-disciplinary categories like cultural, development, feminist, political, social (and a long list of) geographies. Postcolonial accounts of subaltern subject-positionings and subjectivities powerfully evoke the processes of Othering and Orientalism, especially drawing upon literary theory (such as work by Homi Bhabha, Edward Said and Gayatri Spivak). Feminist geographers highlighted the masculinity of that ‘simple’ figure of ‘the subject’ and the importance of attending to gender and sex (in particular we might look to Gillian Rose‘s Feminism and Geography and the Women and Geography Study Group of the IBG’s 1984 Geography and Gender [1]). This attention to the forms of difference that may influence subject formation and subject-positioning, especially race and sexuality, has grown into something like a normative element of ‘critical’ geographical thought. Of course, this is not without controversy and contestation. Look at, for example, the negotiations around what it means to hold an RGS-IBG annual conference themed on decolonisation – check out the virtual issue of Transactions for some excellent interventions. Taking this further, some geographers variously inspired by wider movements in social theory seek to ‘decentre’ the (human) subject in favour of approaches that address the complex variety and ‘excessive’ nature of experiences that are not delimited by the individual human.

I’m inclined to identify two further themes in contemporary theorisations of a ‘subject’ and subjectivities in geography, which are considered more or less ‘cultural’: (1) theorising pre- and trans- subjective relations; and (2) attempts to account for more-than-human subjectivities.

First, theories of affect as ‘different models of causality and determination; different models of social relations and agency; [without] different normative understandings of political power’ (as my colleague Clive Barnett says in ‘Political affects in public space‘) attempt to both decentre but also render ontological a figure of ‘the subject’ (for more critical reflections on this sort of thing I recommend exploring Clive’s work). Non-representational or more-than-representational geographies seek to decentre ‘the subject’ by appealing to pre-subjective experiences, focussing on ‘affects’ (just do a search for ‘affect’ in geographical journals and you can see the influence of this way of thinking). ‘Affects‘ are processes that exceed any individual (they are ‘trans-subjective’) and structure possibilities for individual thought and experience, which constitute subject-formations and positionings (this is sometimes considered ‘ontogenetic’, as my colleague John Wylie has argued).

Second, geographers extend analysis to more than ‘human’ experience. Through the infleunce of Science and Technology Studies we have ‘hybrid’ geographies (following Sarah Whatmore) that trouble clear ‘subject’/’object’, and ‘human’/’non-human’, distinctions address distributed forms of agency, such that agency emerges from networks of relations between different ‘actants’, rather than ‘subjects’ (drawing out the influences, and the geographical mash-up, of Actor-Network Theory and sort-of-Deleuzian assemblage theory). A focus on these sorts of more-than-human geographies has for some time been non-human animals as ‘provocateurs’ (See my colleague Henry Buller‘s Progress Reports [1, 2, 3]). The ‘non-human’ is extended beyond the animal to broader forms of life–including plants, bacteria and other non-human living (and dead) matter (for example see the fantastic work of my colleagues in the Exeter Geography Nature Materiality & Biopolitics research group)–and further to the inorganic ‘non-human’ (I guess in terms of the new materialisms currently in fashion, such as Jane Bennett’s Vibrant Matter). Finally, perhaps the most influential trope in contemporary geographical accounts of subjectivity and subject-positions (that I end up reading) renders processes creating a ‘subject’ as, at least in part, coercive and involuntary (more or less following Foucault’s theories of ‘governmentality‘ and ‘subjectification’). This is often elucidated through processes of corporate and state surveillance, many with digital technologies at their heart.

What seems to become clear (to me anyway!) from my ham-fisted listing and attempting to make sense of what on earth geographical understandings of subjectivity might be is the significant turn to ‘ontology’ in a lot of contemporary work. I don’t know whether this is due to styles of research, pressures to write influential (4* etc etc.) journal articles, lack of time for fieldwork and cogitative reflection… but it sort of seems to me that we’re either led by theory, so assuming subjectivity is the right concept and attempting to validate the fairly prescriptive understanding of subjectivity we have in our theory toolkits, or we’re applying a theoretical jelly mold to our data to find ‘affects’, ‘subjectification’ and so on, when maybe, just maybe, there are other things to say about the kinds of experience, the kinds of agency or action, or ways we understand ourselves and one another.

The abstract figure of ‘the subject’ may be the metaphysical, catchall entity attributed with the ability to act, in contradistinction to static ‘objects’. This kind of ‘subject’ is a vessel for the identities, personhood and experiences of different and diverse individuals. It’s funny then to think that one of many concerns expressed about the growth of (big) data-driven ‘personalisation’ and surveillance is it propagates monolithic data-based ‘subjectivities’, we are calculated as our digital shadows and so forth… In this sense, the ‘ontological’ entity of ‘subject’ appears to supplant the multiple, perhaps messy, forms of subjective experience. Then both of these can perhaps displace or elide wider discussions about action or agency (which is an important element of discussions of pragmatism in/and geography).

For clarification purposes, I’ve begun to think about three particular ways of interrogating how geographers approach whatever ‘subjectivity’ is: (1) a conceptual figure: ‘the subject’; (2) particular kinds of role and responsibility as: ‘subject positions’; and (3) kinds of experience as: ‘subjectivities’. Of course, we probably shouldn’t think about these as static categories; in a variety of geographical research they are all considered ongoing processes (as various flavours of geographical theory from Massey to Thrift will attest). So, I suppose we might equally render the above list as what get’s called: (1) ‘subjectification’; (2) ‘subject positioning’; and (3) ‘subjectivities’.

I could witter on, but I’m running out of steam. I want to (albeit clumsily) tie this back to the recent ‘turn’ to (whatever might be meant by) ‘the digital’ though, cos it’s sort of what’s expected of me and cos it may be vaguely interesting. It’s funny to think that the entity (figure, identity, person etc.) these concepts ground is still, inspite of hybrid geographies and STS influences (mostly), ‘human’. Even within science-fiction tales of robots and Artificial Intelligence (AI), as Katherine Hayles highlights, ‘the subject’ is mostly a human figure – the entity that may act to orchestrate the world (there is, of course, lots to unpack concerning what ‘human’ might mean and whether any technology, however autonomous, can be considered properly non-human).

So, all this might boil down to this supposition: within ‘digital geographies’ debates ‘the subject’, especially the data-based ‘subject’, may be usefully thought about as a figure or device of critique rather than an actually existing thing, while ‘subjectivities’, and how we describe their qualities, remain part of a more plural, maybe more intersectional, explanatory vocabulary.

Notes.

1. I can’t find much online about the original, 1984, Gender and Geography book (maybe needs a presence?) but the Gender & Feminist Geography Research Group (what WGSG became) published Gender and Geography Reconsidered, as a CD(!), which is available on the research group’s website.

‘Automated’ sweated labour

Charlie Chaplin in Modern Times

This piece by Sonia Sodha (Worry less about robots and more about sweatshops) in the Grauniad, which accompanies an episode of the Radio 4 programme Analysis (Who Speaks for the Workers?), is well worth checking out. It makes a case that seems to be increasing in consensus – that ‘automation’ in particular parts of industry will not mean ‘robots’ but pushing workers to become more ‘robotic’. This is an interesting foil to the ‘automated luxury communism’ schtick and the wider imaginings of automation. If you stop to think about wider and longer term trends in labour practices, it also feels depressingly possible…

This is the underbelly of our labour market: illegal exploitation, plain and simple. But there are other legal means employers can use to sweat their labour. In a sector such as logistics, smart technology is not being used to replace workers altogether, but to make them increasingly resemble robots. Parcel delivery and warehouse workers find themselves directed along exact routes in the name of efficiency. Wrist-based devices allow bosses to track their every move, right down to how long they take for lavatory breaks and the speed with which they move a particular piece of stock in a warehouse or from the delivery van to someone’s front door.

This hints at a chilling future: not one where robots have replaced us altogether, but where algorithms have completely eroded worker autonomy, undermining the dignity of work and the sense of pride that people can take in a job well done.

This fits well with complementary arguments about ‘heteromation‘ and other more nuanced understandings of what’s followed or extended what we used to call ‘post-Fordism’…

The dystopian ‘megacity’ future according to US Defence Dept.

dystopian city

Via the Intercept.

Megacities Urban Future, the “Emerging Complexity,” from Philippe Desrosiers on Vimeo.

According to a startling Pentagon video obtained by The Intercept, the future of global cities will be an amalgam of the settings of “Escape from New York“ and “Robocop“ – with dashes of the “Warriors“ and “Divergent“ thrown in. It will be a world of Robert Kaplan-esque urban hellscapes – brutal and anarchic supercities filled with gangs of youth-gone-wild, a restive underclass, criminal syndicates, and bands of malicious hackers.

At least that’s the scenario outlined in “Megacities: Urban Future, the Emerging Complexity,” a five-minute video that has been used at the Pentagon’s Joint Special Operations University. All that stands between the coming chaos and the good people of Lagos and Dhaka (or maybe even New York City) is the U.S. Army, according to the video, which The Intercept obtained via the Freedom of Information Act.

The “Ethics and Governance of Artificial Intelligence Fund” commits $7.6M to research “AI for the public interest”

A press release from the Knight Foundation and another from Omidyar Network highlight their joint effort with several other funders to commit $7.6M to be distributed across several international institutions to research “AI for the public interest”. This seems like an ambitious and interesting research programme, albeit located in the elite institutions one might unfortunately expect to hoover up this sort of funding… Nevertheless, it will be interesting to see what comes of this.

Here’s some snippets (see the full Knight Foundation PR here and the Omidyar PR here).

…a $27 million fund to apply the humanities, the social sciences and other disciplines to the development of AI.

The MIT Media Lab and the Berkman Klein Center for Internet & Society at Harvard University will serve as founding academic institutions for the initiative, which will be named the Ethics and Governance of Artificial Intelligence Fund. The fund will support a cross-section of AI ethics and governance projects and activities, both in the United States and internationally.

…

The fund seeks to advance AI in the public interest by including the broadest set of voices in discussions and projects addressing the human impacts of AI. Among the issues the fund might address:

  • Communicating complexity: How do we best communicate, through words and processes, the nuances of a complex field like AI?
  • Ethical design: How do we build and design technologies that consider ethical frameworks and moral values as central features of technological innovation?
  • Advancing accountable and fair AI: What kinds of controls do we need to minimize AI’s potential harm to society and maximize its benefits?
  • Innovation in the public interest: How do we maintain the ability of engineers and entrepreneurs to innovate, create and profit, while ensuring that society is informed and that the work integrates public interest perspectives?
  • Expanding the table: How do we grow the field to ensure that a range of constituencies are involved with building the tools and analyzing social impact?

…

Supporting a Global Conversation

  • Digital Asia Hub (Hong Kong): Digital Asia Hub will investigate and shape the response to important, emerging questions regarding the safe and ethical use of artificial intelligence to promote social good in Asia and contribute to building the fund’s presence in the region. Efforts will include workshops and case studies that will explore the cultural, economic and political forces uniquely influencing the development of the technology in Asia.
  • ITS Rio (Rio de Janeiro, Brazil): ITS Rio will translate international debates on artificial intelligence and launch a series of projects addressing how artificial intelligence is being developed in Brazil and in Latin America more generally. On behalf of the Global Network of Internet and Society Research Center, ITS Rio and the Berkman Klein Center will also co-host a symposium on artificial intelligence and inclusion in Rio de Janeiro, bringing together almost 80 centers and an international set of participants to address diversity in technologies driven by artificial intelligence, and the opportunities and challenges posed by it around the world.

Tackling Concrete Challenges

  • AI Now (New York): AI Now will undertake interdisciplinary, empirical research examining the integration of artificial intelligence into existing critical infrastructures, looking specifically at bias, data collection, and healthcare.
  • Leverhulme Centre for the Future of Intelligence (Cambridge, United Kingdom): Leverhulme Centre for the Future of Intelligence will be focused on bringing together technical and legal perspectives to address interpretability, a topic made urgent by the European Union’s General Data Protection Regulation coming into force next year.
  • Access Now (Brussels, Belgium): Access Now will contribute to the rollout of the General Data Protection Regulation by working closely with data protection authorities to develop practical guidelines that protect user rights, and educate public and private authorities about rights relating to explainability. The organization will also conduct case studies on data protection issues relating to algorithms and artificial intelligence in France and Hungary.

Bolstering Interdisciplinary Work 

  • FAT ML (Global): FAT ML will host a researcher conference focused on developing concrete, technical approaches to securing values of fairness, accountability, and transparency in machine learning.
  • Data & Society (New York): Data & Society will conduct a series of ethnographically-informed studies of intelligent systems in which human labor plays an integral part, and will explore how and why the constitutive human elements of artificial intelligence are often obscured or rendered invisible. The research will produce empirical work examining these dynamics in order to facilitate the creation of effective regulation and ethical design considerations across domains.

##

About the Ethics and Governance of Artificial Intelligence Fund 

The Ethics and Governance of Artificial Intelligence Fund aims to support work around the world that advances the development of ethical artificial intelligence in the public interest, with an emphasis on applied research and education. The fund was launched in January 2017, with an initial investment of $27 million from the John S. and James L. Knight Foundation, Omidyar Network, LinkedIn founder Reid Hoffman, the Hewlett Foundation, and Jim Pallotta. The activities supported through the fund aim to address the global challenges of artificial intelligence from a multidisciplinary perspective–grounded in data, code, and academic analysis. The fund will advance the public understanding of artificial intelligence and support the creation of networks that span disciplines and topics related to artificial intelligence. The Miami Foundation is serving as fiscal sponsor for the fund.

Via Alexis Madrigral.

Do robots replace (human) jobs? – a further update on imaginings of automation

A warehouse worker and robot

In November I reviewed some literature concerning the narratives of ‘robots’ ‘destroying’ jobs, replacing workers and maybe driving down wages. I showed in that blogpost how different articles contradicted one another about the destruction or creation of jobs/work through automation and argued we probably need to think about this as a discourse, heavy with technological determinisms (following Wyatt) and open to social scientific critique. I went on to look at other stories about automation that emerged in the subsequent five or six months in April and in particular the ways that jobs are becoming ‘unbundled’, the various parts of a job role are being split apart.

In a post earlier today I discussed some of these issues further in relation to the ways these sorts of arguments are storied, and the forms of authority they acquire through the use of statistics. This all goes towards constituting the forms of imagination I discussed in the earlier blogposts – it’s all a part of what I’ve been calling, to make sense of things for myself, a sort of ‘automative imagination’.

I have also today seen an interesting, if lengthy, argument by Mishel and Bivens, of the Economic Policy Institute (considered to be a ‘liberal’ think tank), arguing against some of the recent “robot apocalypse” economic research (in particular showing the widespread misreading of the piece by Acemoglu and Restrepo I highlighted back in April) and the media narratives built around such research:

What is remarkable about this media narrative is that there is a strong desire to believe it despite so little evidence to support these claims. There clearly are serious problems in the labor market that have suppressed job and wage growth for far too long; but these problems have their roots in intentional policy decisions regarding globalization, collective bargaining, labor standards, and unemployment levels, not technology.

This report highlights the paucity of the evidence behind the alleged robot apocalypse, particularly as mischaracterized in the media coverage of the 2017 Acemoglu and Restrepo (A&R) report. Yes, automation has led to job displacements in particular occupations and industries in the past, but there is no basis for claiming that automation has led–or will lead–to increased joblessness, unemployment, or wage stagnation overall. We argue that the current excessive media attention to robots and automation destroying the jobs of the past and leaving us jobless in the future is a distraction from the main issues that need to be addressed: the poor wage growth and inequality caused by policies that have shifted economic power away from low- and moderate-wage workers. It is also the case that, as Atkinson and Wu (2017) argue, our productivity growth is too low, not too high.

[…]

What is remarkable about the automation narrative is that any research on robots or technology feeds it, even if the bottom-line findings of the research do not validate any part of it. The most recent example is the new research by Acemoglu and Restrepo (2017a) on the impact of robots on employment and wages. Here is how The New York Times wrote about this research:

The paper adds to the evidence that automation, more than other factors like trade and offshoring that President Trump campaigned on, has been the bigger long-term threat to blue-collar jobs. The researchers said the findings–”large and robust negative effects of robots on employment and wages”–remained strong even after controlling for imports, offshoring, software that displaces jobs, worker demographics and the type of industry. (Miller 2017)

The EPI article is quite long so I won’t attempt to abridge it here, but the authors do provide some “key findings”, which I do want to reproduce here, see below. I recommend reading the full article though, its an interesting read for anyone who is remotely interested in automation, the nature of work, and the narratives of technology innovation.

Key findings

In this paper we make the following points:

Acemoglu and Restrepo’s new research does not show large and negative effects on overall employment stemming from automation.

  • A&R’s methodology delivers high-quality local estimates of the impact of one sliver of automation (literally looking just at robots). But their translation of these high-quality local estimates (for “commuting zones”) into national effects relies on stylized and largely unrealistic assumptions.
  • Even if one takes the unreliable simulated (not estimated) national effects as given, they are small (40,000 jobs lost each year) relative to any reasonable benchmark. For example, our analysis shows that their estimated job losses from the “China trade shock” are roughly four times as large as their estimated job losses from growing robot adoption in the 2000s.
  • While A&R’s report shows that “robots” are negatively correlated with employment growth across commuting zones, it finds that all other indicators of automation (nonrobot IT investment) are positively correlated or neutral with regard to employment. So even if robots displace some jobs in a given commuting zone, other automation (which presumably dwarfs robot automation in the scale of investment) creates many more jobs. It is curious that coverage of the A&R report ignores this major finding, especially since it essentially repudiates what has been the conventional wisdom for decades–that automation has hurt job growth (at least for less-credentialed Americans).
  • The A&R results do not prove that automation will lead to joblessness in the future or overturn previous evidence that automation writ large has not led to higher aggregate unemployment.

Technological change and automation have not been the main forces driving the wage stagnation and inequality besieging working-class Americans.

  • There is no historical correlation between increases in automation broadly defined and wage stagnation or increasing inequality. Automation–the implementation of new technologies as capital equipment or software replace human labor in the workplace–has been an ongoing feature of our economy for decades. It cannot explain why median wages stagnated in some periods and grew in others, or why wage inequality grew in some periods and shrank in others.
    • Indicators of automation increased rapidly in the late 1990s and the early 2000s, a period that saw the best across-the-board wage growth for American workers in a generation.
    • Indicators of automation fell during two periods of stagnant (or worse) wage growth: from 1973 to 1995 and from 2002 to the present. In these periods, inequality grew as wage growth for the richest Americans far outpaced wage growth of everyone else.
    • During the long period of shared wage growth from the late 1940s to the mid-1970s (shared because all workers’ wages grew at roughly the same pace), indicators of automation also increased rapidly.
  • There is no evidence that automation-driven occupational employment “polarization” has occurred in recent years, and thus no proof it has caused recent wage inequality or wage stagnation.
    • First, numerous studies have documented that there was no occupational employment polarization–in which employment expands in higher-wage and lower-wage occupations while hollowing out in the middle–in the 2000s. Employment has primarily expanded in the lowest-wage occupations. Yet wage inequality between the top and the middle has risen rapidly since 2000.
    • Second, wage inequality overwhelmingly occurs between workers within an occupation, not between workers in different occupations. So even if occupational employment polarization had occurred, it could not explain the growth of wage stagnation or inequality.
  • There is no evidence of an upsurge in automation in the last 10 to 15 years that has affected overall joblessness. The evidence indicates automation has slowed. Trends in productivity, capital investment, information equipment investment, and software investment suggest that automation has decelerated in the last 10 or so years. Also, the rate of shifts in occupational employment patterns has been slower in the 2000s than in any period since 1940. Therefore, there is no empirical support for the prominent notion that automation is currently accelerating exponentially and leading to a robot apocalypse.

The fact that robots have displaced some jobs in particular industries and occupations does not mean that automation has or will lead to increased overall joblessness. 

  • As noted above, data showing a recent deceleration in automation suggest that there is no footprint of an automation surge that can be expected to accelerate in the near future.
  • Technological change and automation absolutely can, and have, displaced particular workers in particular economic sectors. But technology and automation also create dynamics (for example, falling relative prices of goods and services produced with fewer workers) that help create jobs in other sectors. And even when automation’s job-generating and job-displacing forces don’t balance out, government policy can largely ensure that automation does not lead to rising overall unemployment.
    • The narrative that automation creates joblessness is inconsistent with the fact that we had substantial and ongoing automation for many decades but did not have continuously rising unemployment. And the fall in unemployment from 10 percent to below 5 percent since 2010 is inconsistent with the claim that surging automation is generating greater unemployment.
    • As noted above, fluctuations in the pace of technological change have been associated with both good and bad labor market outcomes. So there is no reason to deduce that we should fear robots.

The American labor market has plenty of problems keeping it from working well for most Americans, and these are the problems that should occupy our attention.

  • The problems afflicting American workers include the failure to secure genuine full employment through macroeconomic policy and the intentional policy assault on the bargaining power of low- and middle-wage workers; these are the causes of wage stagnation and rising inequality. Solving these actually existing problems should take precedence over worrying about hypothetical future effects of automation.

See the full article “The zombie robot argument lurches on” on the EPI website.

Past event > Technology’s Limits: Automation, Invention, Labour, and the Exhausted Environment

Glitched image of a mural of Prometheus giving humans' fire in Freiberg

This looks like it was a fascinating event…

Workshop hosted by the Digital Life Research Program 

An abstract artwork of a light background with brown and red rectangles of various sizes.

Artwork by Stephen Scrivener Opens in a new window

Event Details

Date: Friday March 10, 2017
Time: 10am – 4.30pm
Venue: EB.G.21, Parramatta South campus

Among its many political preoccupations, 2016 was marked by an obsessive concern with the new powers of the machine to erase human labour and employment. Science fiction dystopias – among them, the French Trepalium and the Brazilian 3% – saddled older anxieties about a world without work to a more novel recognition of resource depletion and scarcity. Academic publishing houses, conference organisers, funding agencies and the press have responded with a deluge of content covering algorithms, automation and the Anthropocene. Meanwhile, a less conspicuous narrative about the decline of innovation has resurfaced with claims that the rate of fundamental new technology inventions is slowing and jeopardising long term global productivity returns. What happens when technology hits its limits? Velocity and volume excite machinic economies, but do little to confront some of the core problems and challenges facing planetary labour and life today.

This workshop brings together leading Australian scholars of technology and society with contemporary German and French reflections on the prevailing discourses of technology’s limits. Since the 1990s, Bernard Stiegler has been a leading philosopher and critic of technology, and in his recent book Automatic Society he directly tackles problems of automation and algorithms for the distribution of financial and social resources to populations increasingly bereft of economic capital and political agency. Building upon Frankfurt School critical theory and Kittlerian media theory, contemporary German critique intersects with similar questions by combining investigations of epistemology, history and the technical. The Australian take on these European developments is simultaneously appreciative and critical, though often oriented toward more regional conditions that arise in part due to different economic, cultural and political relations with Asia.

The morning session of the workshop will introduce current theoretical European work on technology. Daniel Ross will develop a critical introduction to Bernard Stiegler, whose recent work in Automatic Society and In the Disruption continues to mount a wide-ranging and provocative critique of technology. Armin Beverungen will then offer an overview of his research on algorithmic management and high-frequency trading, with Ned Rossiter introducing logistical media as technologies of automation and labour control. In the afternoon, Gay Hawkins will outline her theoretical interest in nonhuman and technical objects and their irreducible role in making humans and ecologies. A key empirical example will be the history of plastic and the emergence of its technical agency and capacity to reconfigure life. Nicholas Carah will follow with a discussion of his latest work on algorithms, brand management and media engineering. The workshop will close with an audience-driven panel session and discussion. These interventions will be held in conjunction with a close reading of the key texts below.

Register

Attendance numbers will be limited so please register in advance. No registration fee required.

RSVP by 7 March on Eventbrite Opens in a new window

Speakers

  • Armin Beverungen
    Junior Director at the Digital Cultures Research Lab (DCRL) at Leuphana Universität Lüneburg & Visiting Fellow, Institute for Culture and Society, Western Sydney University
  • Nicholas Carah
    Author of Brand Machines, Sensory Media and Calculative Culture (2016)
  • Gay Hawkins
    Author of Plastic Water: The Social and Material Life of Bottled Water (2015)
  • Liam Magee
    Author of Interwoven Cities (2016)
  • Nicole Pepperell
    Author of Dissembling Capital (forthcoming, 2017)
  • Daniel Ross
    Translator of Bernard Stiegler’s Automatic Society (2016) and numerous other works
  • Ned Rossiter
    Author of Software, Infrastructure, Labor: A Media Theory of Logistical Nightmares (2016).

Co-chairs: Liam Magee and Ned Rossiter, co-convenors of the Institute for Culture and Society’s Digital Life research program.

Recommended Readings

Frank Pasquale (2017), Duped by the Automated Public Sphere Opens in a new window
Lee Rainer and Janna Anderson [Pew Research Center] (2017), Code-Dependent: Pros and Cons of the Algorithm Age Opens in a new window
Bernard Stiegler (2012), Die Aufklärung in the Age of Philosophical Engineering (opens in a new window)
Bernard Stiegler (2015), Escaping the Anthropocene Opens in a new window
Bernard Stiegler (2015), On Automatic Society Opens in a new window
Sonia Sodha [The Guardian] (2017), Is Finland’s basic universal income a solution to automation, fewer jobs and lower wages? Opens in a new window

Related Readings

Bruce Braun (2014), A New Urban Dispositif? Governing Life in an Age of Climate Change Opens in a new window
Nick Dyer-Witheford (2013), Contemporary Schools of Thought and the Problem of Labour Algorithms (opens in a new window)
Victor Galaz (2015), A Manifesto for Algorithms in the Environment Opens in a new window
Victor Galaz et al. (2017), The Biosphere Code Opens in a new window
Orit Halpern (2015), Cloudy Architectures Opens in a new window
Erich Hörl (2014), Prostheses of Desire: On Bernard Stiegler’s New Critique of Projection Opens in a new window
Yuk Hui (2015), Algorithmic Catastrophe: The Revenge of Contingency (opens in a new window)
International Labour Organisation (2016), ASEAN in Transformation Opens in a new window
Lilly Irani (2015), The Cultural Work of Microwork Opens in a new window
MIT Technology Review (2012), The Future of Work Opens in a new window
Cathy O’Neill (2016), How Algorithms Rule Our Working Lives Opens in a new window
Elaine Ou (2017), Working for an Algorithm Might Be an Improvement (opens in a new window)
The Guardian (2016), Robot Factories Could Threaten Jobs of Millions of Garment Workers Opens in a new window
Tommaso Venturini, Pablo Jensen, Bruno Latour (2015), Fill in the Gap. A New Alliance for Social and Natural Sciences Opens in a new window

Agenda

  • 10:00 –10:10: Liam Magee, Ned Rossiter: Welcome and Introduction
  • 10:10–11:10: Daniel Ross
  • 11:10–11:30: Q&A
  • 11:30–11:45: Coffee
  • 11:45–1:00: Armin Beverungen, Ned Rossiter
  • 1:00–2:00: Lunch
  • 2:00–3:15: Gay Hawkins, Nicholas Carah
  • 3:15–4:15: Panel discussion responding to automation: Dan / Gay / Nicholas / Armin / Nicole – Liam & Ned to chair
  • 4:15–4:30: Closing thoughts, future actions

65% of future non-existent jobs (which doesn’t exist) 70% of jobs automated (just not yet)

Twiki the robot from Buck Rogers

The future of work is the work of imagination. We are, repeatedly, and have been for a while, bombarded with (pseudo-)facts about what the future of work will bring. These are, of course, part of well-known, long-standing, narratives about ‘innovation’, ‘growth’, technological advance and, of course, ‘automation’.

Martin shared a good post by , on his site Long View on Education, about some persistent kinds of story around the nature of work our schools are preparing children for, or not. Here’s  an abridged, and selective, version of the story…

“The top 10 in demand jobs in 2010 did not exist in 2004. We are currently preparing students for jobs that don’t exist yet, using technologies that haven’t been invented, in order to solve problems we don’t even know are problems yet.”

Shift Happens videos (2007).

People repeat the claim again and again, but in slightly different forms. Sometimes they remove the dates and change the numbers; 65% is now in fashion. Respected academics who study education, such as Linda Darling-Hammond (1:30), have picked up and continue to repeat a mutated form of the factoid, as has the World Economic Forum and the OECD.

[…]

“By one popular estimate 65% of children entering primary schools  today will ultimately work in new job types and  functions that currently don’t yet exist. Technological  trends such as the Fourth Industrial Revolution will  create many new cross-functional roles for which  employees will need both technical and social and analytical skills. Most existing education systems at all levels provide highly siloed training and continue a  number of 20th century practices that are hindering  progress on today’s talent and labour market issues.  “¦  Businesses should work closely with governments,  education providers and others to imagine what a true 21st century curriculum might look like.”

The WeF Future of Jobs report

[…]

Cathy Davidson (May 2017) explains up how she came to the factoid:

“I first read this figure in futurist Jim Carroll’s book, Ready, Set, Done (2007). I tracked his citation down to an Australian website where the “65%” figure was quoted with some visuals and categories of new jobs that hadn’t existed before. “Genetic counseling” was the one I cited in the book.

After Now You See It appeared, that 65% figure kept being quoted so I attempted to contact the authors of the study to be able to learn more about their findings but with no luck.  By then, the site was down and even the Innovation Council of Australia had been closed by a new government.”

The BBC radio programme More or Less picks up the story from here, demonstrating how it most likely has no factual basis derived from any identifiable source (there never was an Innovation Council of Australia, for example).

Davidson sort of defends this through dissimulation, in an interview for More or Less, by saying she believes that 100% of jobs have been affected by ‘the digital era we now live in’.

As Audrey Watters has highlighted, statistics like this and the appeal for a ‘disruption’ of education by the tech sector to teach ‘the skills of the future’ etc. can be reasonably interpreted as a marketing smoke screen – ‘the best way to predict the future is to issue a press release’.

An allied claim, that fall within the same oeuvre as the “65%” of not-existing jobs (or should that be non-existent?), is the various statistics for the automation of job roles, with varying timescales. A canonical example, from another “thought leader” (excuse me while I just puke in this bin), is from WIRED maven Kevin Kelly:

There are an awful lot of variations on this theme, focusing on particular countries, especially the USA, or particular sectors, or calculating likelihoods for particular kinds of jobs and so on and so on. This is, of course, big business in and of itself – firms like Deloitte, McKinsey and others sell this bullshit to anyone willing to pay.

What should we make of all this..?

There are a few interpretations we can make of this genre of ‘foresight’. Alongside several other academics I have written about particular ways of communicating possible futures, making them malleable-yet-certain in some way, as a ‘politics of anticipation‘. This politics has various implications, some banal some perhaps more troubling.

First, you might say it’s a perfectly understandable tendency, of pretty much all of us, to try and lend some certainty to the future. So, in our adolescent know-it-all way, we are all wont to lend our speculations some authority, and statistics, however spurious, is a key tool for such a task.

Second, and perhaps allied to the first, is the sense in which methods for speculation become formalised and normative – they’re integrated into various parts of institutional life. So, it becomes normal to talk about speculative (spurious?!) statistics about a future of work, education etc. in the same tone, with the same seriousness, and the same confidence as statistics about a firm’s current inventory, or last year’s GDP trends. Of course, all statistics, all facts, have conditions and degrees of error and so if the calculation of trends for past events is open to change, the rationale might be, perhaps future trends are just as reliable (there’s all sorts of critique available here but I’m not going to delve into that). In this way, consultancies can package up ‘foresight’ as a product/service that can be sold to others. “Futures” are, of course, readily commodified.

Third, an ideological critique might be that it is precisely these forms of storytelling about the redundancy or insufficiency of the labour force that allows those with the large concentrations of capital to accrue more by demeaning the nature of work itself and privatising profits upwards. If we are repeatedly told that the work that generates the good and services that move through our economy is worth less – because it can be automated, because it is ‘out-dated’, because there are other kinds of superior ‘skilled’ work – then it perhaps becomes easier to suppress wage growth, to chip away at labour rights and render work more precarious. Gloomy I know. However, some data (oh no! statistics!) Doxtdator has in his blogpost (and the kinds of data David Harvey uses in his books, such as The Engima of Captial) could be seen as backing up such arguments. For example (source):


These sorts of graphs, tell a different story about yesterday’s future – which didn’t lead to families reaping the rewards of automation and increased productivity by profiting from a share in increased leisure time (following JM Keynes), but rather delivered the profits of these trends to the “1%” (or even the “0.1%”) by massively increasing top executive salaries while keeping wider wage growth comparatively low, if not stagnant. I’m not an economist, so I don’t want to push my luck arguing this point but there are folk out there who argue such points pretty convincingly, such as David Harvey (though see also economic critiques of the ‘zombie’ automation type of argument).

Ultimately, I am, personally, less interested in the numbers themselves – who knows if 65% of today’s school children will be doing new jobs that represent only 70% of the total work we currently undertake?!  I’m more interested in the kinds of (speculative) truth-making or arguing practices they illustrate. The forms of speculative discourse/practice/norms about technology and work we’re all involved in reproducing. It seems to me that if we can’t fathom those things, we’re less able to care for those of us materially affected by what such speculation does, because, of course, sometimes speculation is self-fulfilling.

To try to advance some discussions about the kinds of technological and economic future that get proposed, gain momentum and become something like “truths”, I’ve been puzzling over the various ways we might see the creation of these economic statistics, the narrating of technological ‘innovation’ in particular ways, and the kinds of stories ‘critical’ academics then tell in analysing these things as making up collectively some form of collective imagination. I started out with ‘algorithms’ but I think that’s merely one aspect of a wider set of discourses about automation that I increasingly feel need to be addressed. My placeholder term for the moment is an “automative imaginary” ~ a collective set of discourses and practices by which particular versions of automation, in the present and the future, are brought into being.

The ambiguity of sharing images

Two tweets, about 12 hours apart. It seems to me, in an entirely unsystematic, morning coffee kind of analysis, that the two posts demonstrate something of the ambiguity of image sharing practices and circulation of images (on Twitter)… at least in my experience of one platform, Twitter.

The “Grease” tweet, through humour, attempts to comment on contemporary geopolitics. The veracity (or not) of the image possibly doesn’t matter.

The ‘fact check’ nature of the later tweet directly addresses the (lack of) authenticity of the image itself. Showing the ‘original’.

So there’s something about ‘fakeness’ of media, the politics of circulation, something about simulacrum and the convening of publics and maybe something about the ambivalence of image making and sharing practices that falls within the “meme” discourse.

In discussing her work as part of the RGS-IBG ‘digital geographies’ working group symposium about 10 days ago, Gillian Rose discussed the ways in which we may or may not malign the ‘everydayness’ of photographic or image practices and why it remains necessary to study and engage with the everyday practices of meaning-making (there’s a course for this, co-convened by Gillian).

This perhaps prompts some questions about the above tweets. For example, what is it we can or might want to say about the images themselves, their circulation and how they fit into wider, everyday, meaning-making practices? The doctored image fits into a particular aesthetic of ‘memes’ and is contextualised in text in the post, which also goes for the ‘fact check’ tweet too, in a way. How do we interpret the (likely) different intentions behind the thousands of retweets of the above? How might we capture the ‘polymedia’ (following Miller et al.) lives of such images? (Is that even possible?) How might we interrogate what I’m suggesting is the ambivalence of ‘sharing’? I suggest this cannot be served by the mass analysis of image corpora (following Manovich), nor is it really reducible to the ‘attention economy’ – it’s not only about the labour of sharing or the advertising it enables. Instead, I guess what I’m fumbling towards is asking for the analysis of the circulation practices for (copies of) a single image within a network (which may or may not span different platforms).

The danger, I increasingly feel, is that we all-too-quickly resort to super-imposing onto these case studies our ontotheological or ideological meta-narratives – so, it may ‘really’ be about affect, neoliberalism and so on… except of course, it isn’t only about those things, and while they may be important analytical frames they may not address the questions we’re interested in, or should be, posing. I’m not saying such framings are wrong, I’m saying they’re not the only frames of analysis.

All of this leads me to confess that I am beginning to wonder if our ‘digital methods‘ (following Rogers and others) are really up to this sort of task… As yet I’ve not read anything to convince me otherwise, which actually sort of surprises me. The closest I’ve got is the media ethnography work of the outstanding Why We Post project – but, of course, that isn’t particularly a “digital” method, which maybe says something (maybe about my own bias). I’d be interested to know if anyone has any thoughts.

A further thing I wonder is whether or not these sorts of practices will remain stable enough for long enough to warrant the ‘slower’, considered, kinds of research that might enable us to begin to get at answers to my all-too-general, or misplaced, questions above. I remain haunted by undergraduate and masters research into now-defunct platforms and styles of media use… friendster and myspace anyone?

Some relevant links:

Revisiting a 90s future: AHRC/EPSRC Next Generation of Immersive Experiences

glitches image of a 1990s NASA VR experience

Emails have been circulating this week about this so it may already be familiar, but ‘digital’ academics may be interested in this… The below is more or less the text of the emails I’ve seen.

Sources: Teeside / AHRC

The Arts and Humanities Research Council (AHRC) and the Engineering and Physical Sciences Research Council (EPSRC) offer support to interdisciplinary research partnerships with the potential to create new knowledge and address major challenges for the development of the next generation of immersive experiences.Proposals are invited from interdisciplinary research partnerships in the areas of:

– Memory – how can new immersive experiences extend the access, interpretation and reach of memory-based institutions such as museum, galleries, archives and collections?
– Place – what new experiences can be created by the combination of immersive technology and place based services?
– Performance – what new creative practices are enabled by immersive technology, what new experiences can be offered to audiences and how can this transform or extend models of performance?

One of the primary aims of this call is to build interdisciplinary capabilities, collaborations, and partnership which will be well placed to take advantage of future opportunities for research and innovation (both from UKRI and beyond). As such AHRC expect partnerships funded through this call to have a life beyond the end of the funding period.

It is expected that the outputs from the funded projects and the wider cohort will include:

  • Interdisciplinary partnerships including academic researchers and creative economy partners;
  • The potential research questions within this space to have been further developed and refined;
  • Sufficient proof of concept(s) / prototypes / visualisations to have been developed by researchers;
  • Tangible advances in creativity, insights, knowledge and understanding in the area of immersive experiences across one or more of the themes;
  • Working with AHRC, EPSRC, IUK and other funders to understand the complexities of funding research in the immersive experience space and potential barriers to exploitation and scaling up of research outputs.

All outcomes should ensure that the UK creative economy can be a world leader in the conceptualisation, design, production and distribution of commercial and cultural immersive experiences in the future.

This call represents an initial stage of investment in the next generation of immersive experiences. AHRC are currently scoping what form further stages of investment might be, and the outcomes of this call will help to inform these further stages.

The maximum value of applications at 100% FEC is £75,000; the deadline for submissions is 5 October 2017. For further details, see the AHRC website.

The Call Document (PDF, 239KB) provides further information on the context and aims for, and the scope of, the call as well as information on how to submit applications.

The AHRC are running a series of engagement events in early July 2017 to cover this call. Details of these events can be found here