I came across yet another smart city event yesterday with a line-up of speakers that was heavily male-dominated: 38 men and 12 women. I tweeted, “what difference does it make that men outnumber women speakers at a #smartcity event by 2 to 1? Sam Kinsley replied and pointed out, quite rightly, that this wasn’t actually as bad as some other events claiming to interpret the contemporary city (for a really shameful example, see Emily Jackson’s post here about a day conference organised by an ESRC-funded research project without a single female speaker – I can’t help thinking that someone high up in the ESRC should have a quiet word with the organisers).
Nonetheless, it’s not great, and it’s part of what seems to be a widespread marginalisation of women among the voices discussing and defining the ‘smart city’. (Ayona Datta joined in the twitter conversation, suggesting some reasons why it happens. ) One day I will find the time and energy to do a proper analysis of the gender balance in the images attached to the tweets of the main smart city players, for example, as well as a headcount of the speakers at the main smart city beanoes, just to confirm the point. In the meanwhile, after I’d read that event’s line-up of speakers and done just a tiny bit of counting, here a few thoughts.
I’m assuming that the overwhelming dominance of men in the smart sector does have a major impact: on what tech is designed and how, on how potential markets are perceived, on what data is collected and what even counts as data, on how the smart city is imagined and therefore built. (There’s so much relevant literature on how digital tech design reinforces various kinds of social differences that I’m just going to point to a useful website that summarises some of it here.) That impact will be both on what social identities are (often) visualised and assumed (both masculine and feminine) and also on what identies are then enacted as the data or device is used. It would be great though to see some research really work at that question and interrogate my answer (and another ESRC-funded project, led by my colleague Prof Parvati Raghuram, promises to contribute towards that).
But maybe a more interesting question is: how to put women into the smart city? Ok, so that’s already problematic. ‘Women’ are a hugely diverse group of course, who do a gazillion different things.
However, as social scientists, we also know that there are patterns of activity within those gazillions. Women still do more domestic labour than men. Women still do more childcare than men. Women still earn less than men. Women are still objectified as sex objects in demeaning ways. So a smart city for women might, say, be focussed a lot more on transport apps that don’t assume that the traveller is one adult, but might allow options for adult(s)+children+(contents of a shopping trolley). It might entail crowd-sourced mapping that pays as much attention to the various forms of childcare (breakfast clubs, nurseries, kindergartens, childminders, after-school-clubs, youth clubs) as it does to drinking venues (as Sarah Elwood and Agnieszka Leszczynski have argued here). The tech of a smart city would assume and enable a wide and diverse range of social actions by people in all sorts of combinations and conditions.
But of course we also want to challenge those patterns, and many other inequalities too. I’m currently touring a talk about corporate visions of smart cities and I often get asked about “bottom-up, participatory, critical alternatives” (a lot of assumptions going on there that should also be unpacked); the example of lot of questioners come up with are the many apps that allow women to log how safe they feel in particular locations and to send messages for help really easily in an emergency. On the one hand, great. City spaces are certainly not always easy for women to inhabit, and some apps make that even worse (again, Sarah Elwood and Agnieszka Leszczynski discuss this most excellently), so it’s fantastic that there are apps in response to that. On the other hand, there’s something profoundly depressing – and disempowering – when the most frequent way women appear in smart cities is as the victims of violence.
So asking about putting ‘women’ into smart cities is maybe not the right question, or maybe not the only question to ask. Not only does it erase the many differences among women, it also doesn’t always negotiate the line between ‘difference’ and ‘stereotype’ adroitly enough.
So maybe we also need a somewhat different agenda, which is more about moving between and against specific forms of difference via digital data and devices. There are those all-too-familiar issues that ‘women’ face. There are ways in which the design and use of digital devices can intensify those issues. But other digital activity might have quite other effects. In relation to those intensifications, for example, is there also something quite liberating, in some ways at least, to be mediated as a geolocated point in space, rather than as a visualised body encoded through gendered, classed, racialised and other ways of seeing?
Which suggests that, in a smart city, ‘women’ can be both: both embodied and a datapoint. Among other things (a selfie, eg). How then can ‘women’ be imagined, in a smart city?
This suggests that another approach to thinking about ‘women in a smart city’ would be to focus on how different social categories are constituted in the first place, when various things are done in cities with digital technologies. That’s the sort of question asked by lots of sociotechnical scholars, of course. But also by feminist scholars of data visualisations like Catherine D’Ignazio and the digital humanities like Johanna Drucker. Their work focuses much more on the production of data in the first place and its problematic relation to social identities and the practices through which identities are enacted – data’s diversity, provisionality and unreliability, its uncertainty – and it focuses attention in particular on the process of turning data into something – a platform, an app – that enables certain social performances. That is, it would be less focussed on ready-made categories of social difference and more on the processes of making data and making with data.
How would a mobility app or a city dashboard build that kind of data provisionality that into its interface? I have no idea! How would its users react? Ditto! But I would love to talk to interface designers about it.
Particularly because these are of course extremely sketchy and initial thoughts. I hope to elaborate them in future posts on how smart cities are visualised in particular – but it would also be great to hear them raised too in some of those flashy smart city events.
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