“Technology is the answer, but what was the question?” On art, smart cities and bringing people together

Voiceover in action in East Durham. Image: Richard Kenworthy.

As our world becomes increasingly influenced by data and networked technologies; as real time sensors stream from buildings, streets and mobile devices, informing us about what’s happening right now; and as our micro-decisions interact more and more with the micro-decisions of others, being meaningfully and consciously engaged with each other and the world around us might seem increasingly elusive.

The volume of data, and the variety of decisions that need to be made, can seem almost overwhelming. And so, introducing technological systems seems like an obvious answer.

Technologies like smart thermostats are supposed to help our homes decide, on our behalf, the right moment to switch on the heating. Automation systems driving our cars, or executing trades on the stockmarket, or managing our city infrastructures, or distinguishing criminals in crowds, or guiding our economies... All of these deal with masses of data, and complex interactions between all sorts of phenomena, much more quickly and, in a sense, more accurately than humans can.

But each of these technologies was designed. That means that somebody somewhere, some group of people, with their own perspectives and worldviews, made the most important decision of all – they decided, defined and designed the goals each of these systems should strive for.

The plan for VoiceOver. Image: Richard Kenworthy. 

Somebody somewhere decided on a definition for optimisation, or a definition of efficiency, or a definition of safety, of risk, of certainty. They decided how to evaluate progress towards a goal. They also decided precisely how goals would get encoded into algorithms – the set of rules used to derive solutions, or make decisions.

But goals are designed – they’re crafted, if you will – and crafting means that they reflect something about their designer, and the designer’s own worldview.

All too often the design of such technologies is done behind closed doors. Whether it’s driverless cars, or smart homes in smart cities, or curated news items in social media – other people, in companies driven by their own commercial requirements or organisations with their own unspoken objectives are making countless non-consensual decisions on our behalf.

The case for togetherness

We, the citizens, need to be involved collectively in helping shape the technologies that govern our lives. They are going to affect how and where we live, and what we do from minute to minute and so we all need to be part of the conversation. There is no single definition of “efficiency”, or “optimisation”, or “convenience”, or “comfort”. Or “terrorist” for that matter.

Technology is equally an outcome of, and a defining factor in the development of our social structures: it both affects and is affected by the societies we live in and the ones we want to create. The kinds of technology we hear about today are often good for doing things quickly, for controlling things or responding to large volumes of data. That means they are good if you have a clear definition of efficiency, and if you have decided that efficiency is what you’re after. In many cases that makes them good, unintentionally or not, for surveillance.

But the other thing that they are good at is bridging distance: connecting people and places and things and experiences and environments and neighbourhoods to each other in real-time. They’re good at shrinking the scale of the planet and making us more aware of how what we do relates to others, both human and non-human. They’re good at linking things that are far apart, or connecting people that don’t know each other. They’re good at helping us discover new perspectives.

So the goal, in my work, is to use networked technologies, not to make things more efficient or to optimise, but to see things differently so that we can make decisions together. Not to make decisions better (whatever that means) but to make them collectively; not to remove inefficiency and complexity, or iron out wrinkles and seams, but to embrace that complexity and build value from the unpredictability, serendipity and creativity that you find in messy situations. I look for ways to deploy infrastructure that gets taken over and repurposed by other people, so they develop a shared sense of technological enfranchisement and ownership in civic outcomes.

Take our project VoiceOver, sited in East Durham in the north of England. We’re deploying a chain of interactive light and sound that weaves its way round local streets of Horden to connect residents, in ways that we hope they’ve never been connected before.

It’s a communication infrastructure, designed and deployed in collaboration with local residents and organisations, that everyone can listen in on, and whose spectacular luminescent path explicitly depends on which residents have elected to host a node of the mesh network. As sound passes up and down the streets, each fragment lights up in response to the different voices and sounds passing through it, making explicit the lines of communication.

VoiceOver in action in East Durham. Image: Richard Kenworthy.

It’s not an “efficient” communication tool: a phone would have been better for one-on-one conversations, and Telegram more private. But the aim was to get as many people as possible together at the same time, communicating with others they might not even know, and meaningfully involved in creating, installing, supporting and bringing to life a cultural infrastructure – one that actively encourages performance, sharing and storytelling. The project has already uncovered the fact that three cousins, who've never all met, have been living near to each other all along.

It’s not that “together” is better than “efficient”. But it certainly has different outcomes. When people work together, my experience is that they have a greater sense of agency and accomplishment, as well as more responsibility and ownership in outcomes.

As we plan for technological interventions in our cities, installing networked technologies and infrastructures for managing the complexities of our lives, let’s evaluate these systems on more than just how efficient they are. Let’s evaluate them on how much they connect us together in new ways, and engage us in meaningful decision making.


The architect Cedric Price once said, “Technology is the answer, but what was the question?” Well, the question has got to be about more than just how to be efficient.

Usman Haque designs interactive architecture systems and researches how people relate to each other and their spaces.

VoiceOver is a new public art commission produced by Forma Arts and created by Umbrellium for East Durham Creates.

 
 
 
 

Local child poverty estimates are difficult – but essential to exposing the stark realities of geographic inequality

A map showing incidence of child poverty in northern England and Wales. Image: End Child Poverty.

Which of the following statements tells you more?

1) Around 4m of Britain’s 14m children live in households classified as in poverty because they have below 60 per cent of median income after housing costs.

2) Among the 2,200 children who live in the Notting Barns area of Kensington, site of Grenfell Tower, nearly a thousand are in families with very low incomes. Just over half a mile away, among the 2,200 children living in three wards around Kensington High Street and Cromwell Road, only 150 are in this situation.

In fact, each statement is useful: the first shows the overall extent of child poverty and the second what it looks like on the ground.

For the past 15 years, I have helped produce maps estimating where child poverty is most concentrated in the UK. These local child poverty figures are not just designed to shock, although they regularly do. They also show local authorities and others in which locations children face the double disadvantage of family poverty and area poverty. These children live in places where a lack of material resources and opportunities can worsen the effects of growing up in a socially and economically disadvantaged household.

Incidence of child poverty in southern England and Wales. Image: End Child Poverty.

The value of these figures is clear: they could help ensure services are targeted where they’re most needed, for example. However, capturing the extent of income poverty in local areas is a highly imperfect process.

To produce our local figures, we use two different data sets in combination to get the best local estimates. In response to our most recent figures, which reflected the clear evidence that child poverty is getting worse, the government has produced figures claiming to show that in fact child poverty is falling. But it has done so using raw data from a single source which is highly unsuitable for tracking changes in child poverty rates over time.      


There are several reasons why local statistics are difficult to produce. National surveys asking people in detail about their incomes are based on samples that are far too small to be able to say anything about incomes at a local level. The best indicators we have of local child poverty come from data held by public authorities on the number of people claiming out-of-work benefits, and the number who claim working tax credits whose reported family income falls below the poverty line.

This so-called “administrative data”, reported regularly by HMRC, certainly gives you a good idea about where the worst-off wards and constituencies are, and some measure of the concentration of low income in these places. However, particularly when tracked over time, they need to be used carefully, in conjunction with other evidence.

One difficulty is that HMRC data assumes that everyone who is out of work is in poverty. In reality, the relationship between being out of work and being in poverty changes over time. The child of a non-working lone parent had around 85 per cent chance of being in poverty 20 years ago, a risk that fell to 58 per cent by 2013, but then rose sharply to 68 per cent by 2015.

Another problem is that HMRC is quite good at assessing family income for tax credit purposes, but not so good at identifying who is in a low-income household (which takes account of a wider range of income than tax credit assessments, including income generated by household members not in the child’s nuclear family). HMRC’s local child poverty statistics only manage to count a third as many people on low working incomes as the full income surveys. This matters a lot – because working poverty has been rising, and out-of-work poverty falling. Two in three children in poverty now have at least one working parent.

An indicator that overcounts out-of-work poverty and undercounts in-work poverty is bound to show current trends – when the latter is falling and the former rising – In a favourable light. This is especially true in London, where in-work poverty, measured after deducting housing costs, is particularly high because of high rents.

And governments, even those like the present one that has underplayed the importance of income poverty, cannot resist highlighting such rose-tinted statistics.

This explains why, after the publication of our latest child poverty map, junior DWP minister and former London deputy mayor Kit Malthouse felt the need to parade data in the House of Commons that seemed to show child poverty in London falling rapidly, and to argue that our data showing the opposite must be mistaken.

But the data he was using, the raw figures produced by HMRC, is flawed in multiple ways. In addition to the limitations I have already pointed to, it has some pretty bizarre aspects – pointed out by HMRC itself in its latest commentary.

One is that the measure of median income to which poverty is being compared by HMRC is actually going down, whereas all the DWP’s income distribution analysis shows median income rising. “Falling” median income creates a falling poverty line, and hence a lower child poverty count. Another feature is that HMRC doesn’t at the moment count out-of-work families on Universal Credit as being in poverty, even though it did so when similar families were on tax credits. This directly brings the child poverty count down.

The local data that we produce corrects for these quirks in the HMRC data by calibrating the results with the Households Below Average Income (HBAI) survey results. It uses the national differences between the HBAI and HMRC results, for in-work and out-of-work poverty respectively, as the basis for an adjustment to each of the local results. While this can only be seen as an estimate of what the correct figures actually are at the local level, it is a far more meaningful estimate than using the flawed HMRC figures without adjustment.

The two graphs below show why. In recent years, HMRC figures on their own have shown steady falls in poverty rates, particularly in London – which are not borne out by the HBAI data that measures income more accurately. Our data  produces results much more in line with the HBAI data, which show that child poverty is now increasing (except in London before housing costs, where the rate is steady).

Percentage point change in UK child poverty rate using different indicators:  Her Majesty’s Revenue and Customs (HMRC); Households Below Average Income measure, Before Housing Costs/After Housing Costs (HBAI BHC/AHC); End Child Poverty (ECP).

Percentage point change in London child poverty rate using different indicators (three-year averages; labels show the middle year).

The Institute for Fiscal Studies forecasts that child poverty will continue to rise at an alarming rate, more than wiping out the considerable falls that took place in the 2000s. This will have very real impacts at the local level, which we will continue to estimate.

A government that simultaneously publishes these figures but boasts about its progress on another measure purporting to show the opposite has its head stuck very firmly in the sand.

Donald Hirsch is director of the Centre for Research in Social Policy at Loughborough University.