In Amsterdam, most rents are capped, revenge evictions illegal and affordable housing quotas are enforced

All this and you get a canal, too. Image: Patrick Clenet/Wikimedia Commons.

Renters in the Netherlands are some of the most protected tenants in the world: most rents are capped, revenge evictions are illegal, affordable housing quotas are enforced. While renters in the UK are filling holes in their ceilings with chewed-up paper, Dutch renters are settling down for a friendly chat with their government supplied housing lawyers. It’s a utopia.

But of course, it isn’t, really. And once I’ve finished spaffing on about all the Dutch laws the UK should adopt, I’ll explain the loophole that is making the whole thing fall apart.

The Netherlands is truly committed to affordable housing

Nearly 50 per cent of the housing in Amsterdam is social rented housing, managed by housing associations and the government. Nearly half.

And it gets better: by 2020, 30 per cent of new builds are going to be social housing. Low income families can live near to the city centre, neighbourhoods retain a diverse mix of people and they’ve neatly sidestepped the ghost towns currently populating France..

Rents are capped on a points system

The Dutch system assigns a certain number of points to each property in the social rented sector, which determines how much rent you have to pay. It’s based on things like number of windows, storage space, and how high up the apartment is.

What this means is that the property's owners can’t make surface changes to an apartment, and then use them to justify hiking the rent. If a tenant moves into an apartment and realises they are paying too much based on the point system, they can also claim the excess rent back.

(Editor's note: It's been brought to our attention that there are properties in the private rental sector which aren't subject to this cap. But a) this liberalisation only applies to the largest and most expensive properties, and b) the social rented sector makes up around three-quarters of all Dutch rental homes, anyway.)

There are no revenge evictions

The only ways a Dutch landlord can evict a tenant is if they have multiple, police registered, noise complaints from the neighbours, or if they are demonstrably damaging the apartment.

The only exceptions are if the landlord suddenly needs to move back into the property (that still needs to go through the courts, and they have to live there for one year after the tenants leave); or if the landlord registered the tenancy as a short term rental before the tenants moved in. A short term rental can only be registered if the landlord is actively trying to sell the property; the tenants must be informed of this before they move in.


There’s free legal support for tenants

Wijksteunpunt Wonen is a government funded organisation that provides free legal advice to tenants. That includes filing charges on their behalf, subsidising any legal fees and negotiating with the landlord.

When it comes to housing, the Dutch have a cheery little saying that

“Expats are the suckers of the world”, so WW is particularly good at helping non-Dutch speakers navigate the intricacy of Dutch law. The current housing slump has seen a lot of landlords attempting to squeeze ever more income out of the one bed apartments they bought in their 20s, only to be told by WW that they have to reimburse the tenants.

Now for the bad news.

Estate agents suck

Estate agents in The Netherlands occupy the same position that they do in the UK. They are the middle men, and landlords are increasingly relying on estate agents to rent their homes in an attempt to simplify the process.

What many landlords don’t realise is that, when they hand over their properties to estate agents, they are basically allowing them to hold tenants hostage. Estate agents will often not disclose to tenants that a property is a short-term let – because they still get their signing fee, even if the tenant ends up taking the landlord to court.

Speaking of signing fees, one of the great things about the Netherlands is that only one party has to pay an estate agents fee; most of the time that’s the landlord. If the tenant finds the property themselves (online, say), then they don’t have to pay as the estate agent hasn’t done anything for them, other than maybe turn up at a building and open a door.

But – there is no law in place to stop estate agents blocking communication between tenants and landlords. And some tell tenants that they have to pay fees that can run into the thousands of euros, if they want the landlords to know they’re interested in renting an apartment.

This effectively prices lower income tenants out of certain neighbourhoods as relatively few people can afford to be blackmailed at €1,000+ a pop.

There are many, many, many good things about Dutch housing law that the UK could learn from, starting with Wijksteunpunt Wonen. But until the Netherlands passes laws to keep estate agents in line, tenants will still be vulnerable to exploitation.

This article was amended on 13 March 2015 to clarify that some private properties are outside the rent capping system.

 
 
 
 

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.