‘Cybernetics in City Hall’ and the Challenge of Real-Time Urban Management

Periodically I come across an old article that seems very relevant to the present, such as the article about public sector innovation I posted in January.

The ongoing expanded use — and declining cost — of sensors and computing technologies has sparked a renewed interest in using them to solve persistent urban problems. A similar wave of interest occurred during the early history of digital computing. In his influential 1950 book, Norbert Wiener popularized the term “cybernetics” to refer to the emerging science of communication and control of organized systems. If the city is an organized system, then cybernetics in city hall would involve creating information feedback loops to be used by the manager (or “actuator”) to minimize the effects of disturbances and maximize achievement of urban goals. Sound familiar? It should: IBM inked a multimillion dollar deal to open a real-time “public information management center” in Rio de Janeiro (right) as part of their smarter cities initiative, and Wired magazine is keeping up a drumbeat about the power of feedback loops.

In an astute article published in Science in 1970, E.S. Savas considered the challenges this approach might face in the real world of New York City government. I don’t doubt the importance of real-time control for management tasks like transportation system management and emergency response, but the article describes some important challenges such a system would face if applied more broadly. Savas described how the five elements of the cybernetic loop would play out in the city: (1) dynamics of urban government, (2) information system, (3) administration, (4) goal setting, and (5) disturbances.

1. Dynamics of city government: The election cycle faced by big city mayors would limit the range of solutions considered, resulting in smaller goals and visible acts, which “may be more symbolic than effective.” Government itself is very slow-moving and one solution — delegating power — may have unintended consequences.

2. Information system: Arguably today much more information is available than was in 1970 about what’s happening in the city. But another crucial input is as tricky as ever — gauging the will of the people.

3. Administration: Making a decision is one thing, but implementing it requires an administration with appropriate personnel and structure, a well-known weakness of big-city bureaucracies.

4. Structure of government: Not only are city governments organized in anachronistic ways, the article omits another key fact: the fragmentation of powers. In Boston, for example, in addition to municipal fragmentation itself, separate entities manage many utilities, the transit system, parks, etc.

4. Goal setting: Identifying a common set of goals may be impossible. The chief executive can use judgement, but it is for good reason that power is delegated to elaborate systems of commissions, boards, and advisers on many topics.

5. Disturbances: These are unpredictable, often external to the city, and often not visible to the public (who sets the goals) until it is too late to prevent their impact. (e.g., climate change)

There are, in general, two responses to most of these concerns. Savas himself took one approach: give up on city government and advocate for privatization of service delivery. Presumably the cold logic of the profit motive would sweep away administrative, regulatory, and decision-making quirks of city governments. The other approach is to attempt to reform the government. In fact, IBM staff have admitted the “challenges” that will face a contemporary agenda for cybernetics. I think the need for contemporary urban government reorganization and reform is acute in many cities, but interest in it seems limited.

Notably, neither of these approaches truly addresses the challenges posed by the short time-horizon of elected officials, difficulty setting goals or forming consensus, and unpredictable disturbances. These three point to the need for planning to solve urban problems: a multi-stakeholder process involving analysis, deliberation, and solution design that both forges a consensus about the definition of a public problem and crafts a desired solution. It seems to me that in the face of the enormity of the challenges we face we need both smart planning and an efficiency-driven smart cities movement willing to push for reform but respectful of democratic systems.

> E.S. Savas in Science magazine, 1970: “Cybernetics in City Hall“

New Planetizen Post: The Coming Urban Data Revolution

I just posted a new article on the Planetizen blog: “The Coming Urban Data Revolution“:

Historically, data sources for urban planning have remained relatively stable. Planners relied on a collection of well-known government-produced datasets to do their work, including statistics and geographic layers from federal, state and local sources. Produced by regulatory processes or occasional surveys, the strengths and limitations of these sources are well known to planners and many citizens. However all this is beginning to change. Not only has the U.S. Census Bureau’s American Community Survey introduced a bewildering variety of data products, all with margins of error, three interrelated categories of new data are growing rapidly: crowdsourced, private, and “big” data.

Back to the Future for Modeling Urban Systems: Research Mirage or New Frontier?

In June I took the general exams for my PhD program, which involved a one-week written and oral test on topics related to my chosen fields — urban information systems and democratic land use planning. This means over the past year I’ve plowed through much of the literature on urban modeling from the 1950s to the present day. As a result, I’ve been feeling acute déjà vu reading about the latest efforts by IBM and others to model “smart” cities, presented as a new frontier for cities devoid of any previous research.

For example, here is a description of an IBM project announced this week:

This problem–if you can’t measure it, you can’t manage it–combined with the impulse to improve cities by models, is driving both IBM’s “smarter city” strategy and the nascent “urban systems” movement, which seek to apply complexity science to cities. IBM … today announced the latest plank in its smarter city platform: an “app” containing 3,000 equations which collectively seek to model cities’ emergent behavior. IBM also revealed its first customer, the City of Portland, Oregon. Systems Dynamics for Smarter Cities, as the app is called, tries to quantify the cause-and-effect relationships between seemingly uncorrelated urban phenomena. What’s the connection, for example, between public transit fares and high school graduation rates? Or obesity rates and carbon emissions? To find out, simply round up experts to hash out the linkages, translate them into algorithms, and upload enough historical data to populate the model.

Here is a description of Jay Forrester’s 1969 book Urban Dynamics. (A MIT professor emeritus, Forrester is known as the founder of System Dynamics.)

In this controversial book, Jay Forrester presents a computer model describing the major internal forces controlling the balance of population, housing, and industry within an urban area. He then simulates the life cycle of a city and predicts the impact of proposed remedies on the system. Startling in its conclusions, this book became the basis of a major research effort that has influenced many government urban-policy decisions.

The contemporary smarter cities discourse seemed to start as merely a marketing ploy, but recently its proponents have sought a more substantial foundation. Although maybe there is more under the surface, so far all I have seen is warmed-over systems modeling or system optimization of the type invented in the 1950s and 1960s. If the promoters of these methods hope for contemporary relevance they must explain why — and how — the severe challenges these approaches face in a democratic society can be overcome.

Perhaps the most well-known article in this field is Douglass Lee’s 1973 article “Requiem for Large-scale Models” (PDF) where Lee, then a freshly minted Berkeley PhD, laid out the “seven sins” of the early generation of large-scale models (which included Forresters’ urban dynamics model): hypercomprehensiveness, grossness, hungriness, wrongheadedness, complicatedness, mechanicalness, and expensiveness. Importantly, he described desirable characteristics for city models:

• Transparency (“‘Black-box’ models will never have an impact on policy other than possibly through mystique, and this will be short lived and self-defeating.”)
• Balance between theory, objectivity, and intuition (“large-scale modeling has been significantly lacking in theory”)
• Start with a particular policy problem that needs solving, not a methodology that needs applying
• Build only very simple models

These recommendations reflect two fundamental differences between cities and other complex systems: randomness and democracy. These underlying theoretical challenges face any would-be urban modeler, from hacktivist to corporate consultant, engaged in the “battle for control of smart cities,” described by Anthony Townsend in a 2010 report and in his forthcoming book.

Urban systems aren’t just complex systems, they’re highly random ones subject to internal and exogenous shocks almost impossible to model, let alone predict. (e.g., gas prices, hurricanes, Justin Bieber concerts, etc) Most concerning, contradictory theories describe these models’ most most important variable, human behavior. These theories all have limited explanatory power but some validity, e.g., economics’ utility maximization and sociology’s social norms.

Secondly, the promise of urban optimization must be reconciled with democratic government. IBM has been running ads where the their employees boast of all the good things they are doing — tracking food for safety or reducing crime. Every time I see them, I think about priorities and trade-offs. Who decided these were the right priorities for resources? Individually they are achieving laudable goals, but they can only be judged in context. Only a democratically legitimate government can determine whether money is well spent on a food or crime tracking systems, versus other pressing concerns like education, health care, and infrastructure.

This post is not a critique of using data and analytical methods for urban policy. To the contrary, I think they’re as needed as ever and have been working with MAPC on a scenario modeling platform. There very well may be analytical innovations, like cellular automata, genetic algorithms, or complexity theories, which could be applied to create useful urban models. However new technology and new buzzwords does not eliminate the long-running theoretical and practical challenges of using models to improve urban life, or the importance of learning from history.

Bike Sharing Coming to Boston: What Infrastructure Is Needed?

Boston has been slow to join the urban bicycling renaissance. In this very strong-mayor city, Mayor Menino had a public about-face in 2007. After long neglecting bicyclists in the city, he hired a “bike czar” and the city began implementing bike racks and lanes. The mayor himself even bought a bike for neighborhood rides.

With the introduction of a new bike sharing system (called Hubway) at a noon press conference next week at city hall on Tuesday, July 26th, Boston joins other innovative U.S. cities like Minneapolis and Washington, D.C. which have followed the lead of Paris and Montréal in rolling out large-scale lending systems.

However, the cantankerous response in the local press illustrates the forces resisting progressive transportation planning here. Instead of encouraging bikes, one columnist writes, the city should ban them, focusing on the roads that were “built for cars.” An equally exaggerated rejoinder suggested banning cars instead. An article in this week’s paper contains critiques of the initial station locations, as well as the patient explanations that the company has had more success with a measured roll-out of a dense network centered on active downtown neighborhoods.

Ironically, surrounding cities like Cambridge may very well be better biking cities, with flatter terrain and more extensive bike lane networks. Since the system was procured through a regional planning agency (note: where I have worked and still consult for), adding new institutions or cities will be seamless process, theoretically expanding to any of the 101 cities and towns surrounding Boston where sharing might make sense.

However what’s missing is a broader discussion about what a 21st century bike infrastructure the city — and region — could use. These changes include some of the policy issues and off-road trails discussed by the 2007 MAPC Regional Bicycle Plan, but others will include detailed changes to our streets. Ironically these could include both more and less lines and signals on the streets. It’s a well-known finding that some streets that seem dangerous are not, so long as certain conditions are met. In other cases, separated infrastructure is safer, or required to encourage cycling. However these changes cost money, and an even scarcer commodity on many city streets. The city’s bike director Freedman explained the dilemma in the Globe:

“Every study and survey of cyclists points to the fact that the only way you are going to have women, children, and seniors cycling in any mass numbers is by providing cycle facilities completely segregated from traffic, with timed lights at intersections that let riders cross without being worried by being hit,’’ Pucher said in a telephone interview.

Freedman, a former Olympic cyclist, said establishing truly protected lanes is not a matter of technology. “It is a question of space. The real issue is a public process of communities deciding what we want. Do we keep the priority for cars or do we start making compromises that integrate bikes? We’ve made tremendous strides, but there is a price and the price is space.’’

I’m not a cycling specialist, so I will leave it to others to discuss what exact changes are needed in Boston. During a trip to the Netherlands last year, like many American visitors I was amazed by the highly developed cycling infrastructure. It led to me ask, if we follow some of the steps taken there, what changes are possible? These photos were taken in The Hague, Delft, and Rotterdam in July 2010.

1. Bike Parking

The most basic amenity is a place to park your bike when in the office or running errands. Bicycle racks are expanding in Boston, but this also involves well-designed, convenient storage spaces inside buildings and at transit hubs.

2. Cycle Tracks

In many European cities, busy streets have separated bicycle and walking areas, both separated from the vehicle lanes. In the case above, special accommodation is made for the bus stop. MIT has installed a cycle track on Vassar Street.

3. Bike Signals

Where a crossing is inevitable, a signaled intersection may be needed. If you look closely above, you can see the red light is in the shape of a bike.

4. Smart Intersections

Good intersections have carefully thought out interactions which balance demands between modes, take into account desire lines, and provide subtle guides to encourage safety and efficiency. This corner gracefully accommodates left turning bicycles onto the street cycle track. The best example of this in the Boston area is a special bike crosswalk at Harvard, allow cyclists to safely cross a busy street.

5. Multimodal Connections

The pyramid structure is above the entrance to a train station. In the foreground, a bicycle track linked to the broader neighborhood system. The Southwest Corridor Park is a start in this area in Boston.

6. Bike Freeways

To the right is the entrance ramp to a limit-access freeway. To the left is the accompanying bicycle freeway.

As the number of cyclists continues to expand in Boston and other U.S. cities, more and more of these European-style interventions may be needed to ensure safety and promote the expansion of the ultimate green transportation mode.

References:
> Hubway
> Boston Bikes
> MAPC Bicycling Projects

How Should Detroit Plan for the Future?

The Detroit News published an op-ed I wrote about lessons learned about urban renewal from my undergraduate thesis.

Detroit is facing big problems: declining population, budget deficits and a stagnant economy.

Discussions about fixing the city has generated dramatic ideas, including the Detroit Works Project — Mayor Bing’s roadmap for the city’s future. The plan calls for closing neighborhoods, cutting services and cultivating new industries. But even with the best of intentions, if city leaders don’t learn from the city’s urban renewal mistakes of the past, Detroit will be doomed to repeat them.

Although Detroit’s population has declined by more than 1.3 million since 1950, the problems of how to make tough decisions remain unchanged.

The Detroit News: “Citizens Need Voice in Renewal“Detroit_News_RGoodspeed

New ‘Planning and Technology Today’ Out for APA Conference

The Spring issue of the newsletter of the the Technology Division of the American Planning Association, which I edit, was just published. The issue was timed to coincide with the American Planning Association conference here in Boston next week. The issue includes articles on the following topics:

• Technology-related sessions at the APA conference
• Social media and local food systems
• A new measure of housing affordability by Chicago’s Center for Neighborhood Technology
• Urban planners and open data

Or, read the entire issue in PDF format.

The Problems With ‘Platforms’

It seems that every day the word ‘platform’ becomes more ingrained in the way we think about online tools to do good and address public problems. The ubiquity of the term may be due to its fundamental ambiguity, which it shares with other terms like ‘sustainability’ and ‘participation.’

In an incisive article on the subject last year, Tarleton Gillespie analyzed how the word “platform” was used by major players like Flickr, YouTube, and Google. (I mentioned his article previously but will summarize the thesis here.) In the article, he points out the contradictory ways the companies use the term as part of a rhetorical strategy to serve their interests. On the one hand, as platforms they argue for limits to legal liabilities for actions of their users. On the other, as a platform of opportunity for advertisers, they define and enforce restrictions on users’ speech and activities. He concludes “the discourse of the ‘platform’ works against us developing such precision, offering as it does a comforting sense of technical neutrality and progressive openness.”

However, as we consider how to apply innovating online technologies for community engagement or governance activities, talk of ‘platforms’ can be troubling from another point of view as well.

Discussions of sociotechnical systems argue humans are just as important as the technical artifacts. An extensive literature on usability and systems development has developed a nuanced understanding of any system as a composite of technical and social components. As a simple example, what an expert user can do with a laptop is much different than what a grandparent can do upon first receiving one. In a larger case one theorist argues “the remarkably low accident rates in commercial air transport, for example, reflect the success of vigilant organizations, legal apparatus, and social learning about accidents as much as the demonstrate the quality of aircraft design and maintenance.” Malcolm Gladwell’s fascinating discussion of air safety in Outliers describes how improving air safety often entails new social rules, such as banning idle chatter in the cockpit during key times, not simply technical ones.

Just as it obscures the internal tensions between different interests, the term “platform” alienates us from this more contextual view of technology. We often jump to the position that solving the problem entails designing the platform, implying it is a neutral system equally usable by any visitor. In reality, according the theory proposed here, solving any problem involves modifying or creating both social and technical components. We are dimly aware of a first-mover advantage in a “space,” but much less aware of the process of creating a useful system. In fact, social construction theory argues technologies are mutually constructed between system designers and engineers and users. Internet “platforms” such as Facebook and Twitter are both powerful independent companies, and in a subtle dialog with their users about how their systems should evolve. The simplest examples are how Twitter has incorporated hashtags and @ tweets into their technical architecture, and Facebook has gone through a well-publicized dance about how to manage the news feed, privacy settings, and even whether you can delete your account.

Of course, this links directly to broader debates about the merits (and measurement) of investments in physical versus social infrastructures. Although it can never be fully resolved, the purpose of the post is to temper technical enthusiasm with a more nuanced view of the origin and evolution of a new category of sociotechnical systems: online platforms.