Glass in architecture once represented transparency. In today’s hyper-gentrified London, it means the opposite

Walls of glass: the City of London. Image: Getty.

Stand on London Bridge on a sunny day and look east. You’ll see the towers of Canary Wharf glistening in the distance, the Shard looming to your right slicing into the sky, and the bloated curves of the Walkie Talkie shimmering like a newly blown glass vase. 

Walk further west along the South bank, and you’ll come across the ‘South Bank tower cluster’, with its centrepiece One Blackfriars jutting its chest out ostentatiously over the river. Further still, and you’ll reach Nine Elms, the biggest building site in the city. Scores of towers are flashing into the sky and construction has begun on the remarkably opulent ‘sky pool’, a 25m long, glass-bottomed swimming pool that hangs 10 storeys up.

These towers represent the most visible beacons of London’s continued development. They contain the moneymaking corporate machines that swell the city’s coffers but fuel the city’s rampant housing crisis, and the unaffordable luxury flats that are the symptom of the city’s hyper-gentrification.

Yet there is another aspect to their representation that often goes under-recorded in the hyperbole around London’s gentrification problem – namely, their most visible constituent material, glass.

In 1921, Ludwig Mies Van der Rhoe designed the now seminal Friedrichstrasse Skyscraper. While it was never built, it is credited as shattering architectural tradition by envisioning buildings that could support entire glass facades, based on a having a then-revolutionary supporting steel skeleton. Mies’ designs encouraged “fluid space”: the connection of the exterior and interior of buildings, bringing nature and light into the home or office.

By Mies van de Rohe 1921. Image: Wikimedia Commons.

Later, in 1958, the ‘float glass’ production method meant much larger sheets of glass could be produced: that facilitating its shift from a decorative material, to one that was fundamental to a building’s construction.

Since then, glass has become one of the most used materials in building construction. In the UK, over 1m tonnes are used every year, it is 100 per cent recyclable, and it can reduce the carbon emissions of buildings by allowing for more efficient temperature regulation.

Because of its environmentally friendly qualities, many cities’ skylines are filled with acres and acres of glass. But in addition, building upon Mies’ original philosophies, it is a material most often associated with transparency, letting in light and allowing inhabitants to see and interact with the city around them. Glass is now so often the architects’ go-to material for modern, ‘homely’ construction, with its transparency and interactive materiality posited in contrast to the harsh, imposing, opaque and brutal forms of concrete.


Yet today, the glass towers of the City and the new-build luxury skyscrapers of the South Bank – and many more like them – are private citadels of the super-rich, imposing a harsh and brutal reality of evictions, displacements and estate demolition. And the concrete modernist housing blocks that they are replacing are fast becoming kitsch totems of a now-distant social housing dream that offered an ethics of commonality, social life and public space – the very characteristics that glass ‘yuppidromes’ so spectacularly fail to deliver.

The recent development of Elephant Park on the footprint of the Heygate Estate in Elephant & Castle is perhaps the most vivid reminder of this process. In addition, the jewel in the Nine Elms crown is the new US embassy that opened in January this year, supposedly the most secure building in the city. What material have they used to convey such heightened levels of opacity, security and ossifying national borders? Glass.

So while glass-fronted buildings offer glimpses into a private, secure and/or corporate world, these worlds are distant mirages. They are hyperreal.

Take one example: the Shard in London, itself covered in 56,000m2 of glass. It may allow the gawker to see inside and the inhabitant to gaze outside upon London’s skyline – but the glistening façade alludes to far-flung, hyper-mobile, international capitalist relations from Qatar that are opaque, and distance the building from the citizens below struggling to find housing. It’s distance so extreme, that the Qatari owners sought to defenestrate any protests as far from the building as possible.

The gaze from inside the Shard is afforded to those with enough capital and power to be able to inhabit the space permanently, or to visitors who have paid (a not insubstantial) entrance fee to obtain the picture postcard view. In both cases, the inhabitants of the building have had to decouple themselves from public space, to enter the privatised place of financialised urban spectacle.

And so, glass as a building’s surface, far from blurring the public-private spatial divide and (re)democratising urban space actually erects further divisions between the private, commercialised and financialised spaces of the contemporary city, and the public, democratic and contested places of urban citizenry. It offers a window into a private pastiche world that is visible, yet very distant from the public and agonistic commons.

The same accusation could be levelled at City Hall. According to the architects, the ‘glass egg’ “expresses the transparency and accessibility of the democratic process”. However, it is situated on private land, where protest – one of the most critical democratic process there is – is strictly forbidden.

The materials that are used in urban construction are vital in how citizens interact with them. Glass, once a material of fluidity, transparency and openness has come to symbolise the extreme inequality blighting so many of the world’s greatest cities. It was Ruth Glass who coined the term gentrification in 1964: little did she realise how aptronymic her name would be…

Oli Mould is a lecturer in human geography at Royal Holloway. This article first appeared on his blog.

 
 
 
 

Just like teenagers, self-driving cars need practice to really learn to drive

A self-driving car, of unknown level of education. Image: Grendelkhan/Flickr/creative commons.

What do self-driving cars and teenage drivers have in common?

Experience. Or, more accurately, a lack of experience.

Teenage drivers – novice drivers of any age, actually – begin with little knowledge of how to actually operate a car’s controls, and how to handle various quirks of the rules of the road. In North America, their first step in learning typically consists of fundamental instruction conveyed by a teacher. With classroom education, novice drivers are, in effect, programmed with knowledge of traffic laws and other basics. They then learn to operate a motor vehicle by applying that programming and progressively encountering a vast range of possibilities on actual roadways. Along the way, feedback they receive – from others in the vehicle as well as the actual experience of driving – helps them determine how best to react and function safely.

The same is true for autonomous vehicles. They are first programmed with basic knowledge. Red means stop; green means go, and so on. Then, through a form of artificial intelligence known as machine learning, self-driving autos draw from both accumulated experiences and continual feedback to detect patterns, adapt to circumstances, make decisions and improve performance.

For both humans and machines, more driving will ideally lead to better driving. And in each case, establishing mastery takes a long time. Especially as each learns to address the unique situations that are hard to anticipate without experience – a falling tree, a flash flood, a ball bouncing into the street, or some other sudden event. Testing, in both controlled and actual environments, is critical to building know-how. The more miles that driverless cars travel, the more quickly their safety improves. And improved safety performance will influence public acceptance of self-driving car deployment – an area in which I specialise.

Starting with basic skills

Experience, of course, must be built upon a foundation of rudimentary abilities – starting with vision. Meeting that essential requirement is straightforward for most humans, even those who may require the aid of glasses or contact lenses. For driverless cars, however, the ability to see is an immensely complex process involving multiple sensors and other technological elements:

  • radar, which uses radio waves to measure distances between the car and obstacles around it;
  • LIDAR, which uses laser sensors to build a 360-degree image of the car’s surroundings;
  • cameras, to detect people, lights, signs and other objects;
  • satellites, to enable GPS, global positioning systems that can pinpoint locations;
  • digital maps, which help to determine and modify routes the car will take;
  • a computer, which processes all the information, recognising objects, analysing the driving situation and determining actions based on what the car sees.

How a driverless car ‘sees’ the road.

All of these elements work together to help the car know where it is at all times, and where everything else is in relation to it. Despite the precision of these systems, however, they’re not perfect. The computer can know which pictures and sensory inputs deserve its attention, and how to correctly respond, but experience only comes from traveling a lot of miles.

The learning that is occurring by autonomous cars currently being tested on public roads feeds back into central systems that make all of a company’s cars better drivers. But even adding up all the on-road miles currently being driven by all autonomous vehicles in the U.S. doesn’t get close to the number of miles driven by humans every single day.

Dangerous after dark

Seeing at night is more challenging than during the daytime – for self-driving cars as well as for human drivers. Contrast is reduced in dark conditions, and objects – whether animate or inanimate – are more difficult to distinguish from their surroundings. In that regard, a human’s eyes and a driverless car’s cameras suffer the same impairment – unlike radar and LIDAR, which don’t need sunlight, streetlights or other lighting.

This was a factor in March in Arizona, when a pedestrian pushing her bicycle across the street at night was struck and killed by a self-driving Uber vehicle. Emergency braking, disabled at the time of the crash, was one issue. The car’s sensors were another issue, having identified the pedestrian as a vehicle first, and then as a bicycle. That’s an important distinction, because a self-driving car’s judgments and actions rely upon accurate identifications. For instance, it would expect another vehicle to move more quickly out of its path than a person walking.


Try and try again

To become better drivers, self-driving cars need not only more and better technological tools, but also something far more fundamental: practice. Just like human drivers, robot drivers won’t get better at dealing with darkness, fog and slippery road conditions without experience.

Testing on controlled roads is a first step to broad deployment of driverless vehicles on public streets. The Texas Automated Vehicle Proving Grounds Partnership, involving the Texas A&M Transportation Institute, University of Texas at Austin, and Southwest Research Institute in San Antonio, Texas, operates a group of closed-course test sites.

Self-driving cars also need to experience real-world conditions, so the Partnership includes seven urban regions in Texas where equipment can be tested on public roads. And, in a separate venture in July, self-driving startup Drive.ai began testing its own vehicles on limited routes in Frisco, north of Dallas.

These testing efforts are essential to ensuring that self-driving technologies are as foolproof as possible before their widespread introduction on public roadways. In other words, the technology needs time to learn. Think of it as driver education for driverless cars.

People learn by doing, and they learn best by doing repeatedly. Whether the pursuit involves a musical instrument, an athletic activity or operating a motor vehicle, individuals build proficiency through practice.

The ConversationSelf-driving cars, as researchers are finding, are no different from teens who need to build up experience before becoming reliably safe drivers. But at least the cars won’t have to learn every single thing for themselves – instead, they’ll talk to each other and share a pool of experience.

Johanna Zmud, Senior Research Scientist, Texas A&M Transportation Institute, Texas A&M University .

This article was originally published on The Conversation. Read the original article.