Living in the World of Both/And

Curated on Posted on by Stefaan Verhulst

Essay by Adene Sacks & Heather McLeod Grant  in SSIR: “In 2011, New York Times data scientist Jake Porway wrote a blog post lamenting the fact that most data scientists spend their days creating apps to help users find restaurants, TV shows, or parking spots, rather than addressing complicated social issues like helping identify which teens are at risk of suicide or creating a poverty index of Africa using satellite data.

That post hit a nerve. Data scientists around the world began clamoring for opportunities to “do good with data.” Porway—at the center of this storm—began to convene these scientists and connect them to nonprofits via hackathon-style events called DataDives, designed to solve big social and environmental problems. There was so much interest, he eventually quit his day job at the Times and created the organization DataKind to steward this growing global network of data science do-gooders.

At the same time, in the same city, another movement was taking shape—#GivingTuesday, an annual global giving event fueled by social media. In just five years, #GivingTuesday has reshaped how nonprofits think about fundraising and how donors give. And yet, many don’t know that 92nd Street Y (92Y)—a 140-year-old Jewish community and cultural center in Manhattan, better known for its star-studded speaker series, summer camps, and water aerobics classes—launched it.

What do these two examples have in common? One started as a loose global network that engaged data scientists in solving problems, and then became an organization to help support the larger movement. The other started with a legacy organization, based at a single site, and catalyzed a global movement that has reshaped how we think about philanthropy. In both cases, the founding groups have incorporated the best of both organizations and networks.

Much has been written about the virtues of thinking and acting collectively to solve seemingly intractable challenges. Nonprofit leaders are being implored to put mission above brand, build networks not just programs, and prioritize collaboration over individual interests. And yet, these strategies are often in direct contradiction to the conventional wisdom of organization-building: differentiating your brand, developing unique expertise, and growing a loyal donor base.

A similar tension is emerging among network and movement leaders. These leaders spend their days steering the messy process required to connect, align, and channel the collective efforts of diverse stakeholders. It’s not always easy: Those searching to sustain movements often cite the lost momentum of the Occupy movement as a cautionary note. Increasingly, network leaders are looking at how to adapt the process, structure, and operational expertise more traditionally associated with organizations to their needs—but without co-opting or diminishing the energy and momentum of their self-organizing networks…

Welcome to the World of “Both/And”

Today’s social change leaders—be they from business, government, or nonprofits—must learn to straddle the leadership mindsets and practices of both networks and organizations, and know when to use which approach. Leaders like Porway, and Henry Timms and Asha Curran of 92Y can help show us the way.

How do these leaders work with the “both/and” mindset?

First, they understand and leverage the strengths of both organizations and networks—and anticipate their limitations. As Timms describes it, leaders need to be “bilingual” and embrace what he has called “new power.” Networks can be powerful generators of new talent or innovation around complex multi-sector challenges. It’s useful to take a network approach when innovating new ideas, mobilizing and engaging others in the work, or wanting to expand reach and scale quickly. However, networks can dissipate easily without specific “handrails,” or some structure to guide and support their work. This is where they need some help from the organizational mindset and approach.

On the flip side, organizations are good at creating centralized structures to deliver products or services, manage risk, oversee quality control, and coordinate concrete functions like communications or fundraising. However, often that efficiency and effectiveness can calcify over time, becoming a barrier to new ideas and growth opportunities. When organizational boundaries are too rigid, it is difficult to engage the outside world in ideating or mobilizing on an issue. This is when organizations need an infusion of the “network mindset.”

 

…(More)

Participatory Budgeting and Transparency in Municipal Finances

Curated on Posted on by Stefaan Verhulst

Paper by Anthony Crossman and Dov Fischer: “In the recessionary years following the 2008 financial crisis, prominent voices predicted an imminent crisis in state and municipal finances. The voices – including Bill Gates, Josh Ruah, Meredith Whitney, Paul Volcker, and Richard Ravitch – declared or implied that the road to fiscal responsibility lies in reining in the pensions and benefits of public servants. We argue that painting public employees as villains introduces divisiveness in what should be a universal goal of sound public finances. We suggest that the road to fiscal responsibility lies with budgetary transparency and widespread public knowledge of state and municipal finances. A potential key to achieving these objectives is participatory budgeting. We motivate a research question on the local government level: Does participatory budgeting increase transparency? Although it is too early to test this question on the local level, we use country-level data from the International Budgetary Partnership to explore ways to operationalize budgetary transparency in order to measure the association between participatory budgeting and budgetary transparency….(More)”

Beware of the gaps in Big Data

Curated on Posted on by Stefaan Verhulst

Edd Gent at E&T: “When the municipal authority in charge of Boston, Massachusetts, was looking for a smarter way to find which roads it needed to repair, it hit on the idea of crowdsourcing the data. The authority released a mobile app called Street Bump in 2011 that employed an elegantly simple idea: use a smartphone’s accelerometer to detect jolts as cars go over potholes and look up the location using the Global Positioning System. But the approach ran into a pothole of its own.The system reported a disproportionate number of potholes in wealthier neighbourhoods. It turned out it was oversampling the younger, more affluent citizens who were digitally clued up enough to download and use the app in the first place. The city reacted quickly, but the incident shows how easy it is to develop a system that can handle large quantities of data but which, through its own design, is still unlikely to have enough data to work as planned.

As we entrust more of our lives to big data analytics, automation problems like this could become increasingly common, with their errors difficult to spot after the fact. Systems that ‘feel like they work’ are where the trouble starts.

Harvard University professor Gary King, who is also founder of social media analytics company Crimson Hexagon, recalls a project that used social media to predict unemployment. The model was built by correlating US unemployment figures with the frequency that people used words like ‘jobs’, ‘unemployment’ and ‘classifieds’. A sudden spike convinced researchers they had predicted a big rise in joblessness, but it turned out Steve Jobs had died and their model was simply picking up posts with his name. “This was an example of really bad analytics and it’s even worse because it’s the kind of thing that feels like it should work and does work a little bit,” says King.

Big data can shed light on areas with historic information deficits, and systems that seem to automatically highlight the best course of action can be seductive for executives and officials. “In the vacuum of no decision any decision is attractive,” says Jim Adler, head of data at Toyota Research Institute in Palo Alto. “Policymakers will say, ‘there’s a decision here let’s take it’, without really looking at what led to it. Was the data trustworthy, clean?”…(More)”

Open Government Implementation Model

Curated on Posted on by Stefaan Verhulst

Open Government Implementation ModelKDZ: “The City of Vienna was the first public agency in a German speaking country to develop an Open Government Initative and to commit itself to the concept of Open Data – an open and transparent system that makes city data available to citizens for their further use. Vienna’s first Open Data catalogue has been presented to the public.

The KDZ – Centre for Public Administration Research was contracted by the Chief Executive Office of Vienna to contribute to the Open Government strategy of the City of Vienna. In order to bring the insights and propositions gained to the attention of a wider public, the Open Government Implementation Model  has been translated into English.

The KDZ Implementation Model is based on and significantly elaborates the “Open Government Implementation Model” by Lee/Kwak (2011). …(More)

See also:

How Citizen Attachment to Neighborhoods Helps to Improve Municipal Services and Public Spaces

Curated on Posted on by Stefaan Verhulst

Paper by Daniel O’Brien, Dietmar Offenhuber, Jessica Baldwin-Philippi, Melissa Sands, and Eric Gordon: “What motivates people to contact their local governments with reports about street light outages, potholes, graffiti, and other deteriorations in public spaces? Current efforts to improve government interactions with constituents operate on the premise that citizens who make such reports are motivated by broad civic values. In contrast, our recent research demonstrates that such citizens are primarily motivated by territoriality – that is, attachments to the spaces where they live. Our research focuses on Boston’s “311 system,” which provides telephone hotlines and web channels through which constituents can request non-emergency government services.

Although our study focuses on 311 users in Boston, it holds broader implications for more than 400 U.S. municipalities that administer similar systems. And our results encourage a closer look at the drivers of citizen participation in many “coproduction programs” – programs that involve people in the design and implementation of government services. Currently, 311 is just one example of government efforts to use technology to involve constituents in joint efforts.

Territorial Ties and Civic Engagement

The concept of territoriality originated in studies of animal behavior – such as bears marking trees in the forest or lions and hyenas fighting over a kill. Human beings also need to manage the ownership of objects and spaces, but social psychologists have demonstrated that human territoriality, whether at home, the workplace, or a neighborhood, entails more than the defense of objects or spaces against others. It includes maintenance and caretaking, and even extends to items shared with others….(More)”

What is being done with open government data?

Curated on Posted on by Stefaan Verhulst

An exploratory analysis of public uses of New York City open data by Karen Okamoto in Webology: “In 2012, New York City Council passed legislation to make government data open and freely available to the public. By approving this legislation, City Council was attempting to make local government more transparent, accountable, and streamlined in its operations. It was also attempting to create economic opportunities and to encourage the public to identify ways in which to improve government and local communities. The purpose of this study is to explore public uses of New York City open data. Currently, more than 1300 datasets covering broad areas such as health, education, transportation, public safety, housing and business are available on the City’s Open Data Portal. This study found a plethora of maps, visualizations, tools, apps and analyses made by the public using New York City open data. Indeed, open data is inspiring a productive range of creative reuses yet questions remain concerning how useable the data is for users without technical skills and resources….(More)”

Discrimination by Design

Curated on Posted on by Stefaan Verhulst

Lena Groeger at ProPublica: “A few weeks ago, Snapchat released a new photo filter. It appeared alongside many of the other such face-altering filters that have become a signature of the service. But instead of surrounding your face with flower petals or giving you the nose and ears of a Dalmatian, the filter added slanted eyes, puffed cheeks and large front teeth. A number of Snapchat users decried the filter as racist, saying it mimicked a “yellowface” caricature of Asians. The company countered that they meant to represent anime characters and deleted the filter within a few hours.

“Snapchat is the prime example of what happens when you don’t have enough people of color building a product,” wrote Bay Area software engineer Katie Zhu in an essay she wrote about deleting the app and leaving the service. In a tech world that hires mostly white men, the absence of diverse voices means that companies can be blind to design decisions that are hurtful to their customers or discriminatory.A Snapchat spokesperson told ProPublica that the company has recently hired someone to lead their diversity recruiting efforts.

A Snapchat spokesperson told ProPublica that the company has recently hired someone to lead their diversity recruiting efforts.

But this isn’t just Snapchat’s problem. Discriminatory design and decision-making affects all aspects of our lives: from the quality of our health care and education to where we live to what scientific questions we choose to ask. It would be impossible to cover them all, so we’ll focus on the more tangible and visual design that humans interact with every day.

You can’t talk about discriminatory design without mentioning city planner Robert Moses, whose public works projects shaped huge swaths of New York City from the 1930s through the 1960s. The physical design of the environment is a powerful tool when it’s used to exclude and isolate specific groups of people. And Moses’ design choices have had lasting discriminatory effects that are still felt in modern New York.

A notorious example: Moses designed a number of Long Island Parkway overpasses to be so low that buses could not drive under them. This effectively blocked Long Island from the poor and people of color who tend to rely more heavily on public transportation. And the low bridges continue to wreak havoc in other ways: 64 collisions were recorded in 2014 alone (here’s a bad one).

The design of bus systems, railways, and other forms of public transportation has a history riddled with racial tensions and prejudiced policies. In the 1990s the Los Angeles’ Bus Riders Union went to court over the racial inequity they saw in the city’s public transportation system. The Union alleged that L.A.’s Metropolitan Transportation Authority spent “a disproportionately high share of its resources on commuter rail services, whose primary users were wealthy non-minorities, and a disproportionately low share on bus services, whose main patrons were low income and minority residents.” The landmark case was settled through a court-ordered consent decree that placed strict limits on transit funding and forced the MTA to invest over $2 billion in the bus system.

Of course, the design of a neighborhood is more than just infrastructure. Zoning laws and regulations that determine how land is used or what schools children go to have long been used as a tool to segregate communities. All too often, the end result of zoning is that low-income, often predominantly black and Latino communities are isolated from most of the resources and advantages of wealthy white communities….(More)”

Crowdsourced map of safe drinking water

Curated on Posted on by Stefaan Verhulst

Springwise: “Just over two years ago, in April 2014, city officials in Flint, Michigan decided to save costs by switching the city’s water supply from Lake Huron to the Flint River. Because of the switch, residents of the town and their children were exposed to dangerous levels of lead. Much of the population suffered from the side effects of lead poisoning, including skin lesions, hair loss, depression and anxiety and in severe cases, permanent brain damage. Media attention, although focussed at first, inevitably died down. To avoid future similar disasters, Sean Montgomery, a neuroscientist and the CEO of technology company, Connected Future Labs, set up CitizenSpring.

CitizenSpring is an app which enables individuals to test their water supply using readily available water testing kits. Users hold a test strip underneath running water, hold the strip to a smartphone camera and press the button. The app then reveals the results of the test, also cataloguing the test results and storing them in the cloud in the form of a digital map. Using what Montgomery describes as “computer vision,” the app is able to detect lead levels in a given water source and confirm whether they exceed the Environmental Protection Agency’s “safe” threshold. The idea is that communities can inform themselves about their own and nearby water supplies in order that they can act as guardians of their own health. “It’s an impoverished data problem,” says Montgomery. “We don’t have enough data. By sharing the results of test[s], people can, say, find out if they’re testing a faucet that hasn’t been tested before.”

CitizenSpring narrowly missed its funding target on Kickstarter. However, collective monitoring can work. We have already seen the power of communities harnessed to crowdsource pollution data in the EU and map conflict zones through user-submitted camera footage….(More)”

For Quick Housing Data, Hit Craigslist

Curated on Posted on by Stefaan Verhulst

Tanvi Misra at CityLab: “…housing researchers can use the Internet bulletin board for a more worthy purpose: as a source of fairly accurate, real-time data on the U.S. rental housing market.

A new paper in the Journal of Planning Education and Research analyzed 11 million Craigslist rental listings posted between May and July 2014 across the U.S. and found a treasure trove of information on regional and local housing trends. “Being able to track rental listings data from Craigslist is really useful for urban planners to take the pulse of [changing neighborhoods] much more quickly,” says Geoff Boeing, a researcher at University of California at Berkeley’s Urban Analytics Lab, who co-authored the paper with Paul Waddell, a Berkeley professor of planning and design.

Here are a couple of big takeaways from their deep dive down the CL rabbit hole:

Overall, Craigslist listings track with HUD data (except when they don’t)

The researchers compared median rents in different Craigslist domains (metropolitan areas, essentially) to the corresponding Housing and Urban Development median rents. In New Orleans and Oklahoma City, the posted and the official rents were very similar. But in other metros, they diverged significantly. In Las Vegas, for example, the Craigslist median rent was lower than the HUD median rent, but in New York, it was much, much higher.

“That’s important for local planners to be careful with because there are totally different cultures and ways that Craigslist is used in different cities,” Boeing explains. “The economies of the cities could very much affect how rentals are being posted. If they’re posting it higher [on Craigslist], they may negotiate down eventually. Or, if they’re posting it low, they could be expecting a bidding war with a bunch of tenants coming in.” …(More)”

‘Homo sapiens is an obsolete algorithm’

Curated on Posted on by Stefaan Verhulst

Extract from Homo Deus: A Brief History of Tomorrow by Yuval Noah Harari: “There’s an emerging market called Dataism, which venerates neither gods nor man – it worships data. From a Dataist perspective, we may interpret the entire human species as a single data-processing system, with individual humans serving as its chips. If so, we can also understand the whole of history as a process of improving the efficiency of this system, through four basic methods:

1. Increasing the number of processors. A city of 100,000 people has more computing power than a village of 1,000 people.

2. Increasing the variety of processors. Different processors may use diverse ways to calculate and analyse data. Using several kinds of processors in a single system may therefore increase its dynamism and creativity. A conversation between a peasant, a priest and a physician may produce novel ideas that would never emerge from a conversation between three hunter-gatherers.

3. Increasing the number of connections between processors. There is little point in increasing the mere number and variety of processors if they are poorly connected. A trade network linking ten cities is likely to result in many more economic, technological and social innovations than ten isolated cities.

4. Increasing the freedom of movement along existing connections. Connecting processors is hardly useful if data cannot flow freely. Just building roads between ten cities won’t be very useful if they are plagued by robbers, or if some autocratic despot doesn’t allow merchants and travellers to move as they wish.
These four methods often contradict one another. The greater the number and variety of processors, the harder it is to freely connect them. The construction of the sapiens data-processing system accordingly passed through four main stages, each of which was characterised by an emphasis on different methods.

The first stage began with the cognitive revolution, which made it possible to connect unlimited sapiens into a single data-processing network. This gave sapiens an advantage over all other human and animal species. Although there is a limit to the number of Neanderthals, chimpanzees or elephants you can connect to the same net, there is no limit to the number of sapiens.

Sapiens used their advantage in data processing to overrun the entire world. However, as they spread into different lands and climates they lost touch with one another, and underwent diverse cultural transformations. The result was an immense variety of human cultures, each with its own lifestyle, behaviour patterns and world view. Hence the first phase of history involved an increase in the number and variety of human processors, at the expense of connectivity: 20,000 years ago there were many more sapiens than 70,000 years ago, and sapiens in Europe processed information differently from sapiens in China. However, there were no connections between people in Europe and China, and it would have seemed utterly impossible that all sapiens may one day be part of a single data-processing web.
The second stage began with agriculture and continued until the invention of writing and money. Agriculture accelerated demographic growth, so the number of human processors rose sharply, while simultaneously enabling many more people to live together in the same place, thereby generating dense local networks that contained an unprecedented number of processors. In addition, agriculture created new incentives and opportunities for different networks to trade and communicate.

Nevertheless, during the second phase, centrifugal forces remained predominant. In the absence of writing and money, humans could not establish cities, kingdoms or empires. Humankind was still divided into innumerable little tribes, each with its own lifestyle and world view. Uniting the whole of humankind was not even a fantasy.
The third stage kicked off with the appearance of writing and money about 5,000 years ago, and lasted until the beginning of the scientific revolution. Thanks to writing and money, the gravitational field of human co-operation finally overpowered the centrifugal forces. Human groups bonded and merged to form cities and kingdoms. Political and commercial links between different cities and kingdoms also tightened. At least since the first millennium BC – when coinage, empires, and universal religions appeared – humans began to consciously dream about forging a single network that would encompass the entire globe.

This dream became a reality during the fourth and last stage of history, which began around 1492. Early modern explorers, conquerors and traders wove the first thin threads that encompassed the whole world. In the late modern period, these threads were made stronger and denser, so that the spider’s web of Columbus’s days became the steel and asphalt grid of the 21st century. Even more importantly, information was allowed to flow increasingly freely along this global grid. When Columbus first hooked up the Eurasian net to the American net, only a few bits of data could cross the ocean each year, running the gauntlet of cultural prejudices, strict censorship and political repression.

But as the years went by, the free market, the scientific community, the rule of law and the spread of democracy all helped to lift the barriers. We often imagine that democracy and the free market won because they were “good”. In truth, they won because they improved the global data-processing system.

So over the last 70,000 years humankind first spread out, then separated into distinct groups and finally merged again. Yet the process of unification did not take us back to the beginning. When the different human groups fused into the global village of today, each brought along its unique legacy of thoughts, tools and behaviours, which it collected and developed along the way. Our modern larders are now stuffed with Middle Eastern wheat, Andean potatoes, New Guinean sugar and Ethiopian coffee. Similarly, our language, religion, music and politics are replete with heirlooms from across the planet.
If humankind is indeed a single data-processing system, what is its output? Dataists would say that its output will be the creation of a new and even more efficient data-processing system, called the Internet-of-All-Things. Once this mission is accomplished, Homo sapiens will vanish….(More)“