Reblog> Humans and machines at work

A warehouse worker and robot

Via Phoebe Moore. Looks good >>

Humans and Machines coverHumans and machines at work: monitoring, surveillance and automation in contemporary capitalism edited by Phoebe V. Moore, Martin Upchurch and Xanthe Whittaker.
This edited collection is now in production/press (Palgrave, Dynamics of Virtual Work series editors Ursula Huws and Rosalind Gill). This is the results of the symposium I organised for last year’s International Labour Process Conference (ILPC). We are so fortunate to have 9 women and 3 men authors from all over the world including Chinese University Hong Kong, Harvard, WA University St Louis, Milan, Sheffield, Lancaster, King’s College, Greenwich, and Middlesex researchers, two trade unionists from UNI Global Union and Institute for Employment Rights, early career and more advanced contributors.

In the era of the so-called Fourth Industrial Revolution, we increasingly work with machines in both cognitive and manual workplaces. This collection provides a series of accounts of workers’ local experiences that reflect the ubiquity of work’s digitalisation. Precarious gig economy workers ride bikes and drive taxis in China and Britain; domestic workers’ timekeeping and movements are documented; call centre workers in India experience invasive tracking but creative forms of worker subversion are evident; warehouse workers discover that hidden data has been used for layoffs; academic researchers see their labour obscured by a ‘data foam’ that does not benefit us; and journalists suffer the algorithmic curse. These cases are couched in historical accounts of identity and selfhood experiments seen in the Hawthorne experiments and the lineage of automation. This collection will appeal to scholars in the sociology of work and digital labour studies and anyone interested in learning about monitoring and surveillance, automation, the gig economy and quantified self in workplaces.

Table of contents:

Chapter 1: Introduction. Phoebe V. Moore, Martin Upchurch, Xanthe Whittaker

Chapter 2: Digitalisation of work and resistance. Phoebe V. Moore, Pav Akhtar, Martin Upchurch

Chapter 3: Deep automation and the world of work. Martin Upchurch, Phoebe V. Moore

Chapter 4: There is only one thing in life worse than being watched, and that is not being watched: Digital data analytics and the reorganisation of newspaper production. Xanthe Whittaker

Chapter 5: The electronic monitoring of care work – the redefinition of paid working time. Sian Moore and L. J. B. Hayes

Chapter 6: Social recruiting: control and surveillance in a digitised job market. Alessandro Gandini and Ivana Pais

Chapter 7: Close watch of a distant manager:  Multisurveillance by transnational clients in Indian call centres. Winifred R. Poster

Chapter 8: Hawthorne’s renewal: Quantified total self. Rebecca Lemov

Chapter 9: ‘Putting it together, that’s what counts’: Data foam, a Snowball and researcher evaluation. Penny C. S. Andrews

Chapter 10: Technologies of control, communication, and calculation: Taxi drivers’ labour in the platform economy. Julie Yujie Chen

Reblog> Martin Dodge and Rob Kitchin, Mapping Cyberspace (free book download)

Via Stuart Elden.

Mapping Cyberspace was a formative introduction to ‘geography’ for me as an undergraduate digital arts student. It certainly influenced my (all-too-naive) BSc dissertation ideas… It’s great this is available, it documents so many things that seemed so vital at the time and that now appear almost like peculiar mirages.

Martin Dodge and Rob Kitchin, Mapping Cyberspace (free book download)

Mapping Cyberspace – Martin Dodge & Rob KitchinMartin Dodge and Rob Kitchin’s 2001 book Mapping Cyberspace is now available as a free download. There is also a website about the book here.

Mapping Cyberspace is a ground-breaking geographic exploration and critical reading of cyberspace, and information and communication technologies. The book:

  • * provides an understanding of what cyberspace looks like and the social interactions that occur there
  • * explores the impacts of cyberspace, and information and communication technologies, on cultural, political and economic relations
  • * charts the spatial forms of virtual spaces
  • * details empirical research and examines a wide variety of maps and spatialisations of cyberspace and the information society

has a related website at

This book will be a valuable addition to the growing body of literature on cyberspace and what it means for the future.

Our vascilating accounts of the agency of automated things

Rachael in the film Blade Runner

“There’s no hiding behind algorithms anymore. The problems cannot be minimized. The machines have shown they are not up to the task of dealing with rare, breaking news events, and it is unlikely that they will be in the near future. More humans must be added to the decision-making process, and the sooner the better.”

Alexis Madrigal

I wonder whether we have if not an increasing then certainly a more visible problem with addressing the agency of automated processes. In particular automation that functions predominantly through software, i.e. stuff we refer to as ‘algorithms’ and ‘algorithmic’, possibly ‘intelligent’ or ‘smart’ and perhaps even ‘AI’, ‘machine learning’ and so on.  I read three things this morning that seemed to come together to concretise this thought: Alexis Madrigal’s article in The Atlantic – “Google and Facebook have failed us“, James Somers’ article in The Atlantic – “The coming software apocalypse” and LM Sacacas’ blogpost “Machines for the evasion of moral responsibility“.

In Madrigal’s article we can see how the apparent autonomy of the ‘algorithm’ becomes the fulcrum around which machinations around ‘fake news’, in this case regarding the 2nd October 2017 mass shooting in Las Vegas. The apparent incapacity of an automated software system to perform the kinds of reasoning attributable to a ‘human’ editor is diagnosed on the one hand, and on the other the speed at which such breaking news events taking place and the volume of data being processed by ‘the algorithm’ led to Google admitting that their software was “briefly surfacing an inaccurate 4chan website in our Search results for a small number of queries”. Madrigal asserts:

It’s no longer good enough to shrug off (“briefly,” “for a small number of queries”) the problems in the system simply because it has computers in the decision loop.

In Somers’ article we can see how decisions made by programmers writing software that processed call sorting and volume for the emergency services in Washington State led to the 911 phone system being inaccessible to callers for six hours one night in 2014. As Somers describes:

The 911 outage… was traced to software running on a server in Englewood, Colorado. Operated by a systems provider named Intrado, the server kept a running counter of how many calls it had routed to 911 dispatchers around the country. Intrado programmers had set a threshold for how high the counter could go. They picked a number in the millions.

Shortly before midnight on April 10, the counter exceeded that number, resulting in chaos. Because the counter was used to generating a unique identifier for each call, new calls were rejected. And because the programmers hadn’t anticipated the problem, they hadn’t created alarms to call attention to it. Nobody knew what was happening. Dispatch centers in Washington, California, Florida, the Carolinas, and Minnesota, serving 11 million Americans, struggled to make sense of reports that callers were getting busy signals. It took until morning to realize that Intrado’s software in Englewood was responsible, and that the fix was to change a single number.

Quoting an MIT Professor of aeronautics (of course) Nancy Leveson, Somers observes: “The problem,” Leveson wrote in a book, “is that we are attempting to build systems that are beyond our ability to intellectually manage.”

Michael Sacasas in his blogpost refers to Madrigal’s article and draws out arguments that the complex processes of software development, maintenance and the large and complicated organisations such as Facebook are open to those working there to work in a ‘thoughtless’ manner:

“following Arendt’s analysis, we can see more clearly how a certain inability to think (not merely calculate or problem solve) and consequently to assume moral responsibility for one’s actions, takes hold and yields a troubling and pernicious species of ethical and moral failures. …It would seem that whatever else we may say about algorithms as technical entities, they also function as the symbolic base of an ideology that abets thoughtlessness and facilitates the evasion of responsibility.”

The simplest version of what I’m getting at is this: on the one hand we attribute significant agency to automated software processes, this usually involves talking about ‘algorithms’ as quasi- or pretty much autonomous, which tends to infer that whatever it is we’re talking about, e.g. “Facebook’s algorithm”, is ‘other’ to us, ‘other’ to what might conventionally be characterised as ‘human’. On the other hand we talk about how automated processes can encode the assumptions and prejudices of the creators of those techniques and technologies, such as the ‘racist soap dispenser‘.

There’s a few things we can perhaps note about these related but potentially contradictory narratives.

First, they perhaps infer that the moment of authoring, creating, making, manufacturing is a one-off event – the things are made, the software is written and it becomes set, a bit like baking a sponge cake – you can’t take the flour, sugar, butter and eggs out again. Or, in a more nuanced version of this point – there is a sense that once set in train these things are really, really hard to change, which may, of course, be true in particular cases but also may not be a general rule. A soap dispenser’s sensor may be ‘hard coded’ to particular tolerances, whereas what gets called ‘Facebook’s algorithm’, while complicated, is probably readily editable (albeit with testing, version control and so on). This kind of narrative freights a form of determinism – there is an implied direction of travel to the technology.

Second, the kinds of automated processes I’m referring to here, ‘algorithms’ and so on, get ‘black boxed’. This is not only on the part of those who create, operate and benefit from those processes—like those frequently referred to Google, Facebook, Amazon and so on—but also in part by those who seek to highlight the black boxing. As Sacasas articulates: “The black box metaphor tries to get at the opacity of algorithmic processes”. He offers a quote from a series of posts by Kevin Hamilton which illustrates something of this:

Let’s imagine a Facebook user who is not yet aware of the algorithm at work in her social media platform. The process by which her content appears in others’ feeds, or by which others’ material appears in her own, is opaque to her. Approaching that process as a black box, might well situate our naive user as akin to the Taylorist laborer of the pre-computer, pre-war era. Prior to awareness, she blindly accepts input and provides output in the manufacture of Facebook’s product. Upon learning of the algorithm, she experiences the platform’s process as newly mediated. Like the post-war user, she now imagines herself outside the system, or strives to be so. She tweaks settings, probes to see what she has missed, alters activity to test effectiveness. She grasps at a newly-found potential to stand outside this system, to command it. We have a tendency to declare this a discovery of agency—a revelation even.

In a similar manner to the imagined participant in Searle’s “Chinese Room” thought experiment, the Facebook user can only guess at the efficacy of their relation to the black boxed process. ‘Tweaking our settings’ and responses might, as Hamilton suggest, “become a new form of labor, one that might then inevitably find description by some as its own black box, and one to escape.” A further step here is that even those of us diagnosing and analysing the ‘black boxes’ are perhaps complicit in keeping them in some way obscure. As Evan Selinger and Woodrow Hartzog argue: things that are obscure can be seen as ‘safe’, which is the principle of cryptography. Obscurity, for Selinger & Hartzog, “is a protective state that can further a number of goals, such as autonomy, self-fulfillment, socialization, and relative freedom from the abuse of power”. Nevertheless, obscurity can also be an excuse – the black box is impenetrable, not open to analysis and so we settle on other analytic strategies or simply focus on other things. A well-worn strategy seems to be to retreat to the ontological, to which I’ll return shortly.

Third, following from above, perhaps the ways in which we identify ‘black boxes‘ or the forms of black boxing we do ourselves over-simplifies or elides complexity. This is a difficult balancing act. A good concept becomes a short-hand that freights meaning in useful ways. However, there is always potential that it can hide as much as it reveals. In the case of the phenomena outlined in the two articles above, we perhaps focus on the ends, what we think ‘the algorithm’ does – the kinds of ‘effects’ we see, such as ‘fake news’ and the breakdown of an emergency telephone system, or even a ‘racist soap dispenser’. It is then very tempting to perform what Sally Wyatt calls a ‘justifactory’ technological determinism – not only is there a ’cause and effect’ but these things were bound to happen because of the kinds of technological processes involved. By fixing ‘algorithms’ as one kind of thing, we perhaps elide the ways in which they can be otherwise and, perhaps more seriously, elide the parts of the process of the development, resources, use and reception of those technologies and their integration into wider sociotechnical systems and society. These things don’t miraculously appear from nowhere – they are the result of lots of actions and decisions, some banal, some ‘strategic’, some with good intentions and some perhaps morally-questionable. By black boxing ‘the algorithm’, attributing ‘it’ with agency and making it ‘other’ to human activities we ignore or obscure the organisational processes that make it possible at all. I argue we cannot see these things as completely one thing or the other: the black boxed entity or the messy sociotechnical system, but rather as both and need to accommodate that sort of duality in our approaches to explanation.

Fourth, normative judgements are attached to the apparent agency of an automated system when it is perceived as core to the purpose of the business. Just like any other complicated organisation whose business becomes seen as a ‘public good’ (energy companies might be another example), competing, perhaps contradictory, narratives take hold. The purpose of the business may be to make money–in the case of Google and Facebook this is of course primarily through advertising, requiring attractive content to which to attach adverts–but the users perhaps consider their experience, which is ‘free’, more important. It seems to have become received wisdom that the very activities that drive the profits of the company, by boosting content that drives traffic and therefore serves more advertising and I assume therefore resulting in more revenue, run counter to accepted social and moral norms. This exemplifies the competing understandings of what companies like Google and Facebook do – in other words, what their ‘algorithms’ are for. This has a bearing on the kinds of stories we then tell about the perceived, or experienced, agency of the automated system.

Finally (for now), there is a tendency for academic social scientific studies of automated software systems to resort to ontological registers of analysis. There may be all sorts of reasons used as justification for this, such as specific detail of a given system is not accessible, or (quite often) only accessible through journalists, or the funding isn’t available to do the research. However, it also pays dividends to do ‘hard’ theory. In the part of academia I knock about in, geography-land and it’s neighbours, technology has been packaged up into the ‘non-human’ whereby the implication is that particular kinds of technology are entirely separate from us, humans, and can be seen to have ‘effects’ upon us and our societies. This is trendy cos one can draw upon philosophy that has long words and hard ideas in it, in particular: ‘object oriented ontology‘ (to a much lesser extent the ‘bromethean‘ accellerationists). The generalisable nature of ‘big’ theory is beguiling, it seems to permit us to make general, perhaps global, claims and often results in a healthy return in the academic currency of citations. Now, I too am guilty of resorting to theory, which is more or less abstract, through the work of Bernard Stiegler in particular, but I’d like to think I haven’t disappeared down the almost theological rabbit hole of trying to think objects in themselves through abstract language such as ‘units‘ or ‘allopoetic objects‘ and ‘perturbations’ of non-human ‘atmospheres’.

It seems to me that while geographers and others have been rightly critical of simplistic binaries of human/technical, there remains a common habit of referring to a technical system that has been written by and is maintained by ‘humans’ as other to whatever that ‘human’ apparently is, and to refer to technologically mediated activities as somehow extra-spatial, as virtual, in contra-distinction to a ‘real’. This is plainly a contradiction. On the one hand this positions the technology in question (‘algorithms’ and so on) as totally distinct from us, imbued with an ability to act without us and so potentially powerful. On the other hand if that technology is ‘virtual’ and not ‘real’ it implies it doesn’t count in some way. While in the late 90s and early 00s the ‘virtual’ technologies we discussed were often seen as somewhat inconsequential, the more contemporary concerns about ‘fake news’, malware and encoded prejudices (such as racism) have made automated software systems part of the news cycle. I don’t think it is a coincidence that we’ve moved from metaphors of liberty and community online to metaphors of ‘killer robots’, like the Terminator (of course there is a real prospect of autonomous weapons systems, as discussed elsewhere).

In the theoretical zeal of ‘decentering the human subject’ and focusing on the apparent alterity of technology, as abstract ‘objects’, we are at risk of failing to address the very concerns which are expressed in the articles by Madrigal and Somers. In a post entitled ‘Resisting the habits of the algorithmic mind‘, Sacasas suggests that automated software systems (‘algorithms’) are something like an outsourcing of problems solving ‘that ordinarily require cognitive labor–thought, decision making, judgement. It is these very activities–thinking, willing, and judging–that structure Arendt’s work in The Life of the Mind.’ The prosthetic capacity of technologies like software to in some way automate some of these processes might be liberating but they are also, as Sacasas suggests, morally and politically consequential. To ‘outsource the life of the mind’ for Sacasas means to risk being ‘habituated into conceiving of the life of the mind on the model of the problem-solving algorithm’. A corollary to this supposition I would argue is that there is a risk in the very diagnosis of this problem that we habituate ourselves to a determinism as well. As argued in the third point, above, we risk obscuring the organisational processes that make such sociotechnical systems possible at all. In the repetition of arguments that autonomous, ‘non-human’, ‘algorithms’ are already apparently doing all of these problematic things we will these circumstances upon ourselves. There is, therefore, an ethics to thinking about and analysing automation too.

Where does this leave us? I think it leaves us with some critical tools and tasks. We perhaps need not to shy away from the complexity of the systems we discuss – the ideas and words we use can do work for us, ‘algorithm’ for example freights some meaning, but we perhaps need to be careful we don’t obscure as much as we reveal. We perhaps need to use more, not fewer, metaphors. We definitely need more studies that get at the specificity of particular forms, processes and work of automation/automated systems. All of us, journalists and academics alike, need to perhaps use our words more carefully, or use more words to get at the issues.

Simply hailing the ‘rise of the robots’ is not enough. I think this reproduces an imagination of automation that is troubling and ought to be questioned (what I’ve called an ‘automative imaginary’ elsewhere, but maybe that’s too prosaic). For people like me in geography-land to retreat into ‘high’ theory and to only discuss abstract ontological/ metaphysical attributes of technology seems to me to be problematic and is a retreat from that part of the ‘life of the mind’ we claim to advance. I’m not arguing we need not retreat from theory we simply need to find a balance. A crucial issue for social science researchers of ‘algorithms’ and so on is that this sort of work is probably not the work of a lone wolf scholar, I increasingly suspect that it needs multi-disciplinary teams. It also needs to, at least in part, produce publicly accessible work (in all senses of ‘accessible’). In this sense work like the report on ‘Media manipulation and disinformation online‘ by Data & Society seems like necessary (but by no means the only) sorts of contribution. Prefixing your discipline with ‘digital’ and reproducing the same old theory but applied to ‘digital’ things won’t, I think, cut it.

“I’m so excited to join a botnet”

Glitched image of a sous-vide machine

From NY magazine:

I didn’t just buy a sous-vide circulator, I also bought what could very likely turn into a new zombie member of a botnet nobody knows about yet. (A botnet, to refresh your memory, is a group of many disparate internet-enabled computers whose security has been remotely compromised, enabling hackers to network them together and use their combined power for nefarious purposes.)

I do not actually know that my sous-vide circulator will be hacked remotely in order to power a Low Orbit Ion Cannon (popular software for launching a distributed denial-of-service attack used to take websites off the internet temporarily), but if it did happen, I would not be surprised. Oftentimes, the computers — usually very primitive computers of the kind found in security cameras, smart-home light bulbs, and cooking appliances — function normally while these processes run in the background. Perhaps my precision cooker will be attacking a major DNS server while I poach a perfect egg. Or maybe it will help take down a dissident forum as I prepare a cut of steak for the grill. The possibilities are endless.

Another new book from Bernard Stiegler – Neganthropocene

Bernard Stiegler being interviewed

Open Humanities has a(nother!) new book from Bernard Stiegler, blurb pasted below. This is an edited version of Stiegler’s public lectures in various places over the last three or so years, hence Dan Ross’ byline. Dan has done some fantastic work of corralling the fast-moving blizzard of Stiegler’s concepts and sometimes flitting engagements with a wide range of other thinkers and I am sure that this book surfaces this work.

It would be interesting to see some critical engagement with this, it seems that Stiegler simply isn’t as trendy as Latour and Sloterdijk or the ‘bromethean‘ object-oriented chaps for those ‘doing’ the ‘anthropocene’ for some reason. I’m not advocating his position especially, I have various misgivings if I’m honest (and maybe one day I’ll write them down) but it is funny that there’s a sort of anglophone intellectually snobbery about some people’s work…


by Bernard Stiegler
Edited and translated by Daniel Ross


As we drift past tipping points that put future biota at risk, while a post-truth regime institutes the denial of ‘climate change’ (as fake news), and as Silicon Valley assistants snatch decision and memory, and as gene-editing and a financially-engineered bifurcation advances over the rising hum of extinction events and the innumerable toxins and conceptual opiates that Anthropocene Talk fascinated itself with–in short, as ‘the Anthropocene’ discloses itself as a dead-end trap–Bernard Stiegler here produces the first counter-strike and moves beyond the entropic vortex and the mnemonically stripped Last Man socius feeding the vortex.

In the essays and lectures here titled Neganthropocene, Stiegler opens an entirely new front moving beyond the dead-end “banality” of the Anthropocene. Stiegler stakes out a battleplan to proceed beyond, indeed shrugging off, the fulfillment of nihilism that the era of climate chaos ushers in. Understood as the reinscription of philosophical, economic, anthropological and political concepts within a renewed thought of entropy and negentropy, Stiegler’s ‘Neganthropocene’ pursues encounters with Alfred North Whitehead, Jacques Derrida, Gilbert Simondon, Peter Sloterdijk, Karl Marx, Benjamin Bratton, and others in its address of a wide array of contemporary technics: cinema, automation, neurotechnology, platform capitalism, digital governance and terrorism. This is a work that will need be digested by all critical laborers who have invoked the Anthropocene in bemused, snarky, or pedagogic terms, only to find themselves having gone for the click-bait of the term itself–since even those who do not risk definition in and by the greater entropy.

Author Bio

Bernard Stiegler is a French philosopher who is director of the Institut de recherche et d’innovation, and a doctor of the Ecole des Hautes Etudes en Sciences Sociales. He has been a program director at the Collège international de philosophie, senior lecturer at Université de Compiègne, deputy director general of the Institut National de l’Audiovisuel, director of IRCAM, and director of the Cultural Development Department at the Centre Pompidou. He is also president of Ars Industrialis, an association he founded in 2006, as well as a distinguished professor of the Advanced Studies Institute of Nanjing, and visiting professor of the Academy of the Arts of Hangzhou, as well as a member of the French government’s Conseil national du numérique. Stiegler has published more than thirty books, all of which situate the question of technology as the repressed centre of philosophy, and in particular insofar as it constitutes an artificial, exteriorised memory that undergoes numerous transformations in the course of human existence.

Daniel Ross has translated eight books by Bernard Stiegler, including the forthcoming In the Disruption: How Not to Go Mad?(Polity Press). With David Barison, he is the co-director of the award-winning documentary about Martin Heidegger, The Ister, which premiered at the Rotterdam Film Festival and was the recipient of the Prix du Groupement National des Cinémas de Recherche (GNCR) and the Prix de l’AQCC at the Festival du Nouveau Cinéma, Montreal (2004). He is the author of Violent Democracy (Cambridge University Press, 2004) and numerous articles and chapters on the work of Bernard Stiegler.

CFP: Workshop on Trustworthy Algorithmic Decision-Making

Not sure where I found this, but it may be of interest…

Workshop on Trustworthy Algorithmic Decision-Making
Call for Whitepapers

We seek participants for a National Science Foundation sponsored workshop on December 4-5, 2017 to work together to better understand algorithms that are currently being used to make decisions for and about people, and how those algorithms and decisions can be made more trustworthy. We invite interested scholars to submit whitepapers of no more than 2 pages (excluding references); attendees will be invited based on whitepaper submissions. Meals and travel expenses will be provided.

Online algorithms, often based on data-driven machine-learning approaches, are increasingly being used to make decisions for and about people in society. One very prominent example is the Facebook News Feed algorithm that ranks posts and stories for each person, and effectively prioritizes what news and information that person sees. Police are using “predictive policing” algorithms to choose where to patrol, and courts are using algorithms that predict the likelihood of repeat offending in sentencing. Face recognition algorithms are being implemented in airports in lieu of ID checks. Both Uber and Amazon use algorithms to set and adjust prices. Waymo/Google’s self-driving cars are using Google maps not just as a suggestion, but to actually make route choices.

As these algorithms become more integrated into people’s lives, they have the potential to have increasingly large impacts. However, if these algorithms cannot be trusted to perform fairly and without undue influences, then there may be some very bad unintentional effects. For example, some computer vision algorithms have mis-labeled African Americans as “gorillas”, and some likelihood of repeat offending algorithms have been shown to be racially biased. Many organizations employ “search engine optimization” techniques to alter the outcomes of search algorithms, and “social media optimization” to improve the ranking of their content on social media.

Researching and improving the trustworthiness of algorithmic decision-making will require a diverse set of skills and approaches. We look to involve participants from multiple sectors (academia, industry, government, popular scholarship) and from multiple intellectual and methodological approaches (computational, quantitative, qualitative, legal, social, critical, ethical, humanistic).


To help get the conversation started and to get new ideas into the workshop, we solicit whitepapers of no more than two pages in length that describe an important aspect of trustworthy algorithmic decision-making. These whitepapers can motivate specific questions that need more research; they can describe an approach to part of the problem that is particularly interesting or likely to help make progress; or they can describe a case study of a specific instance in the world of algorithmic decision-making and the issues or challenges that case brings up.

Some questions that these whitepapers can address include (but are not limited to):

  • What does it mean for an algorithm to be trustworthy?
  • What outcomes, goals, or metrics should be applied to algorithms and algorithm-made decisions (beyond classic machine-learning accuracy metrics)?
  • What does it mean for an algorithm to be fair? Are there multiple perspectives on this?
  • What threat models are appropriate for studying algorithms? For algorithm-made decisions?
  • What are ways we can study data-driven algorithms when researchers don’t always have access to the algorithms or to the data, and when the data is constantly changing?
  • Should algorithms that make recommendations be held to different standards than algorithms that make decisions? Should filtering algorithms have different standards than ranking or prioritization algorithms?
  • When systems use algorithms to make decisions, are there ways to institute checks and balances on those decisions? Should we automate those?
  • Does transparency really achieve trustworthiness? What are alternative approaches to trusting algorithms and algorithm-made decisions?

Please submit white papers along with a CV or current webpage by October 9, 2017 via email to We plan to post whitepapers publicly on the workshop website (with authors’ permission) to facilitate conversation ahead of, at, and after the workshop. More information about the workshop can be found at

We have limited funding for PhD students interested in these topics to attend the workshop. Interested students should also submit a whitepaper with a brief description of their research interests and thoughts on these topics, and indicate in their email that they are PhD students.

Talking with Mikayla

Talking with Mikayla, the Museum of Contemporary Commodities GuideImage credit: Mike Duggan.

At the RGS-IBG Annual International Conference 2017, co-originator of the Museum of Contemporary Commodities (MoCC) Paula Crutchlow and I staged a conversation with Mikayla the MoCC guide, a hacked ‘My Cayla Doll’. This was part of two sessions that capped off the presence of MoCC at the RGS-IBG and was performed alongside a range of other provocations on the theme(s) of ‘data-place-trade-value’. The doll was only mildly disobedient and it was fun to be able to show the subversion of an object of commercial surveillance in a playful way. Below is the visuals that displayed during the conversation, with additional sound…

For more, please do go and read Paula’s excellent blogpost about Mikayla on the MoCC website.


glitches image of a 1990s NASA VR experience

A bit of nostalgia… ‘practising tomorrows‘ and all that.

Lots of things to crit with the benefit of hindsight, which I’m sure some folks did – I mean, the peculiar sort of aesthetic policing implied is funny and the fact that none of the folk used as talking heads can imagine a collaborative form of authorship is quite interesting. This programme came out in 1990, around the same time Berners Lee is pioneering the web – a rather different, perhaps more “interactive” vision of ‘multimedia’ – insofar as with the web we can all contribute to the creation as well as consumption of media [he writes in the dialog box of the “Add New Post” page of the WordPress interface]…

A slightly geeky thing I appreciate though is the very clear visual reference to the 1987 Apple Computer ‘video prototype’ called ‘Knowledge Navigator‘ (<–follow the link, third video down, see also), which I’m certain is deliberate.

‘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’…