Technology is not neutral, and cities aren’t either: May 20, 2018 Snippets
As always, thanks for reading. Want Snippets delivered to your inbox, a whole day earlier? Subscribe here.
This week’s theme: how transportation technology changed from an equalizing force into a magnifier of inequality. Plus more news on Saildrone’s big ambitions.
Welcome back to our Snippets series on cities, where over the last few weeks we’ve learned about how cities, and particularly their transportation, follow the general rules of networks. Last week, we looked at the impact of technology, and how new tech — in this case, the streetcar systems of 100 years ago, the automobile in the 20th century, and on-demand “mobility as a service” products emerging today — changes the rules by which those networks spread and operate. This week, we’re going to look a little deeper into an uncomfortable truth about transportation networks in cities today, and how many of the progressive transport technologies we celebrate may be exacerbating and reinforcing inequality.
As a general rule, one of the most important (and often overlooked) fundamental properties of any new technology is that it reflects the preferences, norms and worldview of its designers. This is what we mean when we say technology is not neutral. You might look at some new technology and argue, “This technology is equal-opportunity! It’s the same for everyone!” but that’s hardly ever true, except in the narrowest of senses. The design choices and tradeoffs that are made, along with the price and business model structure in question, will be optimized within the worldview of its creators unless deliberately made otherwise. That’s not to say that its designers and builders are bad people! It’s just the way things naturally happen. (Anil Dash has a good post on this phenomenon here.) The neutrality of tech doesn’t exist in a vacuum, either. More often than not, the real drivers tech’s non-neutrality are outside forces, whose consequences and ramifications get magnified by the technology in question. But the technology’s creators do not notice, usually because those outside forces are acting as an unnoticed wind at their back.
Let’s consider this idea through the lens of transportation technology and housing prices in cities over the last century. 100 years ago, when we think about what factors went into working out who lived where, two factors stood out in particular. First, transportation was relatively slow: the dominant mode of transportation was walking, and longer commutes from the home to the workplace were quite costly in terms of time. Second, workplaces were much dirtier, unpleasant environments than they are today: people didn’t want to live near the factory; riverside neighbourhoods were seen as undesirable. As a general rule, city neighbourhoods evolved around this tradeoff: living farther away from dirty industry was a privilege reserved for those who could afford luxury “high-speed” transportation like carriages or very early automobiles. Neighborhood segregation between different communities was very real, but it was largely along explicit racial and class boundaries rather than purely economic ones.
Now consider what happened with the automobile and the rise of personal transportation. The car democratized the ability to commute out of the city and into the suburbs: the cost of commuting became much easier to bear. Personal automobile transportation has many drawbacks, as we now appreciate — they pollute, they contribute to sprawl, they demand space in the form of roads and parking lots that create anti-social areas. But, as a technology for people, cars were a huge and lasting success partially because as far as technologies go, cars are about as neutral as they come. Everyone’s equal on the road: rich people and poor people get stuck in the same traffic together, and face the same tradeoff of commuting time versus city escape together. The spatial relationship between jobs and residential neighbourhoods meant that for most people, cars were an equalizing, rather than polarizing force. Although it came at great cost, it’s not an accident that the rise of the personal automobile corresponded with the growth and prosperity of the American middle class in the mid-20th century.
But in the last few decades, something important has flipped. The nature of work, jobs and city downtowns has changed dramatically: mixed-use communities where work, commercial and residential spaces all co-mingle together have become attractive places to live. What used to be a negative feedback relationship (where the benefits of living far away and the cost of commuting kept one another in check) have given way to a positive feedback relationship: city living has become desirable, and that desire compounds in the form of housing prices. Meanwhile, a new form of urbanism is gaining traction: transit-oriented development. TOD was created and popularized by Peter Calthorpe, through his work in the 1980s through the publication of “The New American Metropolis” in 1993. (Calthorpe is still on the transit-oriented development front lines as the co-founder of UrbanFootprint, which builds urban planning and modelling tools and is part of the Social Capital family.) With TOD, priority public transit corridors are built in tandem with both residential and mixed-use development, creating a set of planning best practices that are now being adopted around the world.
The problem is that the recent shift in cities towards desirable downtown living has turned transportation and commute times into a magnifier of inequality rather than a levelling force. “Commuting inequality” is now a very real and terrible phenomenon in wealthy coastal cities, where middle class and median-wage workers are forced farther and farther out into the exurbs if they want any chance of owning a home — or even, in cases, like the Bay Area — being able to afford any kind of rent at all. Housing costs have become the fulcrum through which transportation technology has transformed from being an equalizer to a magnifier of inequality, and from neutral to non-neutral technology. Transit-oriented development would be a potential solution, but in some cases, laying light rail lines has made the problem worse instead of better: they simply create thin corridors of expensive property values along public transit lines, allowing small numbers of professional workers to leapfrog the line by paying fare tickets priced just out of reach for most. Transit-oriented development is great, if you can afford to live next to transit. City initiatives that fund fancy light rail lines at the expense of their everyday workhorse bus routes don’t alleviate commuting inequality, they magnify it.
What happens with driverless cars? If we’re not careful, driverless cars and mobility-as-a-service networks based on single occupancy vehicles could multiply this problem to a nightmarish degree. It’s not hard to imagine a future that could evolve quite organically in which not only are “Gold Track” priority traffic lanes the norm for rich people willing to pay more to get around traffic jams (if you want a preview of what this looks like in practice, just look at what happens when passengers board an airplane), but where the price of transportation and the price of housing become fully intertwined and even possibly bundled together. This is highly non-neutral technology, backed into the city’s social and economic fabric, in way that should worry us: it makes our cities, our neighbourhoods and our social structures more divided, more fragile, and less resilient. So what can be done? Is there any good news? We’ll look at why it’s not all bad, and why there may be real reasons to celebrate and be optimistic, next week.
Past societies:
An ice core reveals the economic health of the Roman Empire | Nicholas Wade, NYT
The decline of Snapchat and the secret joy of Internet ghost towns | Helena Fitzgerald, The Verge
How the music industry messed up legal streaming the first time around | Ernie Smith, Motherboard
Bugs, deliberate and accidental:
Stuxnet: the most sophisticated piece of software ever written | John Byrd, Quora
On the social and economic ladder:
Tom Wolfe, sage of status anxiety | Louis Menard, The New Yorker
The 9.9% is the new American Aristocracy | Matthew Stewart, The Atlantic
Take a second look:
Is your job Lynchian, or is it more Kafkaesque? | Rachel Paige King
Symmetry and identity | Kenneth Shinozuka, Ribbonfarm
When humans meet machines: intuition, expertise and learning | Erik Brynjolfsson & Daniel Kahneman
Automotive concerns:
Waymo filings give new details on its driverless taxis | Mark Harris, IEEE Spectrum
Other reading from around the Internet:
The state of cryptocurrency mining | David Vorick
GPDR will pop the adtech bubble | Doc Searls
I know everyone told you to send your fundraising decks as a link; don’t | Mark Suster
Making maps on a micrometer scale | B.J. Linzmeier et al., Earth & Space Science News
Europe’s open-access drive escalates as university stand-offs spread | Holly Else, Nature
In last week’s Snippets, we saw a sneak preview of Saildrone’s voyage to the White Shark Cafe, giving us a hint of one kind of mission the autonomous boats have been tasked with carrying out. This week, Ashlee Vance at Bloomberg Businessweek pulled back the curtain on what’s at stake, and why Richard, Sebastien, and the team at Saildrone are building their company:
This armada of Saildrones could conquer the ocean | Ashlee Vance, Bloomberg Businessweek
Our planet is covered in ocean yet we barely understand it, even today at a time when we can scarcely afford to take any of our planetary resources for granted. It’s simply been a matter of cost: to truly understand something so vast required funding and human resources at a level of intensity that would be unaffordable to any group, public or private. True progress can’t come from policy or funding alone; it needs a true technological breakthrough -and Saildrone’s autonomous boats could well be the answer. As Vance writes:
Despite the ocean’s size and value, resources to study it are scant. The US National Oceanic and Atmospheric Administration, or NOAA, is among the field’s best-funded research organizations and has all of 16 science ships, complemented by another 16 from university fleets. Australia has only one serious research vessel. Much of the data about global seas come from satellite readings and a smattering of sensor-equipped buoys. …
The NOAA ships and their like can cost $80 million to $150 million to build. It’s another $50,000 to $100,000 a day to run them, and the longer the mission, the pricier logistics get. “It’s fuel, consumables, and I don’t want to tell you what our satellite bill is for data,” says Andreas Marouchos, a research group leader with the Commonwealth Scientific and Industrial Research Organization (CSIRO), Australia’s science agency. …
Saildrone says its craft are meant to work in tandem with human researchers to ease these burdens. Scientists and businesses can rent one for $2,500 a day. The drone heads to its selected destination and gathers data, which Saildrone helps process and analyze. The company has built around three dozen drones so far and says it plans to complete 200 by the end of the year. Building 1000, the number Jenkins figures would be enough for round-the-clock assessments of the oceans, could cost upwards of $100 million, although that’s still cheaper than a single NOAA research ship.
The 1000 Saildrone number is an ambitious goal, and Jenkins and his team are fearlessly going for it. This past week, they announced a new $60 million Series B round of funding, led by Horizons Ventures, to carry out their plan:
A step towards a quantified planet | Saildrone
“Our bet is that we can collect in-situ data about the state of our planet by deploying a large number of autonomous ocean-going drones, achieving a feat that was previously economically infeasible with traditional ship-based infrastructure. We are quite far down that path — in fact, our initial global fleet of Saildrones has already traveled over 250,000 nautical miles on the world oceans, collecting data which has been scientifically evaluated to be of climate-quality level by multiple peer-reviewed publications.
Our next step is clear: we are scaling the manufacturing of our drones so that we can cover the entire planet with a target resolution of 6 by 6 degrees, which is equivalent to 1000 vehicles. In doing so, we continue to partner with leading scientific institutions around the world to help guide the scientific application of this emerging infrastructure, collecting terabytes of data along the way.”
As momentum and urgency behind them grows, Saildrone’s mission rings increasingly true: to create the highest resolution ocean data set in the world and use it to make global processes such as weather forecasting, carbon cycling, global fishing and and climate change more predictable, visible and actionable. If this mission speaks to you, reach out. Saildrone wants to hear from you. They’re currently hiring for software engineering, hardware engineering, people operations, and marketing roles in Alamedia. Their next hire could be you.
Have a great week,
Alex & the team from Social Capital
