Curated findings and actionable knowledge at the intersection of technology, innovation, and governance
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Blog entry by Dan Swislow at OpeningParliament: “On December 17, the presidency of the Brazilian Chamber of Deputies passed a resolution that creates a permanent Laboratório Ráquer or “Hacker Lab” inside the Chamber—a global first.
Read the full text of the resolution in Portuguese.
The resolution mandates the creation of a physical space at the Chamber that is “open for access and use by any citizen, especially programmers and software developers, members of parliament and other public workers, where they can utilize public data in a collaborative fashion for actions that enhance citizenship.”
The idea was born out of a week-long, hackathon (or “hacker marathon”) event hosted by the Chamber of Deputies in November, with the goal of using technology to enhance the transparency of legislative work and increase citizen understanding of the legislative process. More than 40 software developers and designers worked to create 22 applications for computers and mobile devices. The applications were voted on and the top three awarded prizes.
The winner was Meu Congress, a website that allows citizens to track the activities of their elected representatives, and monitor their expenses. Runner-ups included Monitora, Brasil!, an Android application that allows users to track proposed bills, attendance and the Twitter feeds of members; and Deliberatório, an online card game that simulates the deliberation of bills in the Chamber of Deputies.
The hackathon engaged the software developers directly with members and staff of the Chamber of Deputies, including the Chamber’s President, Henrique Eduardo Alves. Hackathon organizer Pedro Markun of Transparencia Hacker made a formal proposal to the President of the Chamber for a permanent outpost, where, as Markun said in an email, “we could hack from inside the leviathan’s belly.”
The Chamber’s Director-General has established nine staff positions for the Hacker Lab under the leadership of the Cristiano Ferri Faria, who spoke with me about the new project.
Faria explained that the hackathon event was a watershed moment for many public officials: “For 90-95% of parliamentarians and probably 80% of civil servants, they didn’t know how amazing a simple app, for instance, can make it much easier to analyze speeches.” Faria pointed to one of the hackathon contest entries, Retórica Parlamentar, which provides an interactive visualization of plenary remarks by members of the Chamber. “When members saw that, they got impressed and wondered, ‘There’s something new going on and we need to understand it and support it.’”
Science 2.0: “Open Collaboration, defined in a new paper as “any system of innovation or production that relies on goal-oriented yet loosely coordinated participants who interact to create a product (or service) of economic value, which they make available to contributors and non-contributors alike” brought the world Wikipedia, Bitcoin and, yes, even Science 2.0.
But what does that mean, really? That’s the first problem with vague terms in an open environment. It is anything people want it to be and sometimes what people want it to be is money, but hidden behind a guise of public weal.
TED’s lesser cousin TEDx is a result of open collaboration but there is no doubt it has successfully leveraged the marketing of TED to sell seats in auditoriums, just as it was designed to do. Generally, Open Collaboration now is less like its early days, where a group of like-minded people got together to create an Open Source tool, and more like corporations. Only they avoid the label, they are not quite non-profits and not quite corporations.
And because they are neither they can operate free of the cultural stigma. Despite efforts to claim that Wikipedia is a hotbed of misogyny and blocks out minorities, the online encyclopedia has endured just fine. Their defense is a simple one; they have no idea what gender or race or religion anyone is and anyone can contribute – it is a true open collaboration. Open Collaboration is goal-oriented, they lack the infrastructure to obey demands that they become about social justice, so the environments can be less touchy-feely than corporations and avoid the social authoritarianism of academia.
Many open collaborations perform well even in ‘harsh’ environments, where some minorities are underrepresented and diversity is lacking or when products by different groups rival one another. It’s a real puzzle for sociologists. The authors conclude that open collaboration is likely to expand into new domains, displacing traditional organizations, because it is so mission-oriented. Business executives and civic leaders should take heed – the future could look a lot more like the 1940s.”
See also: Sheen S. Levine, Michael J. Prietula, ‘Open Collaboration for Innovation: Principles and Performance’, Organization Science December 30, 2014 DOI:10.1287/orsc.2013.0872
Please find below the latest installment in The GovLab Index series, inspired by Harper’s Index. “The GovLab Index: Open Data — December 2013” provides an update on our previous Open Data installment, and highlights global trends in Open Data and the release of public sector information. Previous installments include Measuring Impact with Evidence, The Data Universe, Participation and Civic Engagement and Trust in Institutions.
Value and Impact
Efforts and Involvement
Examining Datasets…
FULL VERSION AT http://thegovlab.org/govlab-index-open-data-updated/
Steven Hodas @ The Lean Startup Conference 2013 –…Steven runs an procurement-innovation program in one of the world’s most notorious bureaucracies: the New York City Department of Education. In a fear-driven atmosphere, with lots of incentive to not be embarrassed, he’ll talk about the challenges he’s faced and progress he’s made testing new ideas.
Brett Scott: “This is an article about Open Source Finance. It’s an idea I first sketched out at a talk I gave at the Open Data Institute in London. By ‘Open Source Finance’, I don’t just mean open source software programmes. Rather, I’m referring to something much deeper and broader. It’s a way of framing an overall change we might want to see in the financial system….
Pillar 2: Widespread distribution
Financial intermediaries like banks and funds serve as powerful gatekeepers to access to financing. To some extent this is a valid role – much like a publisher or music label will attempt to only publish books or music that they believe are high quality enough – but on the other hand, this leads to excessive power vested in the intermediaries, and systematic bias in what gets to survive. When combined with a lack of democratic accountability on the part of the intermediaries, you can have whole societies held hostage to the (arbitrary) whims, prejudices and interests of such intermediaries. Expanding access to financial services is thus a big front in the battle for financial democratisation. In addition to more traditional means to buildingfinancial inclusion – such as credit unions and microfinance – here are two areas to look at:
Pillar 3: The ability to monitor
Do you know where the money in the big banks goes? No, of course not. They don’t publish it, under the guise of commercial secrecy and confidentiality. It’s like they want to have their cake and eat it: “We’ll act as intermediaries on your behalf, but don’t ever ask for any accountability”. And what about the money in your pension fund? Also very little accountability. The intermediary system is incredibly opaque, but attempts to make it more transparent are emerging. Here are some examples:
Pillar 4: An ethos of non-prescriptive DIY collaboration
At the heart of open source movements is a deep DIY ethos. This is in part about the sheer joy of producing things, but also about asserting individual power over institutionalised arrangements and pre-established officialdom. Alongside this, and deeply tied to the DIY ethos, is the search to remove individual alienation: You are not a cog in a wheel, producing stuff you don’t have a stake in, in order to consume stuff that you don’t know the origins of. Unalienated labour includes the right to produce where you feel most capable or excited.
This ethos of individual responsibility and creativity stands in contrast to the traditional passive frame of finance that is frequently found on both the Right and Left of the political spectrum. Indeed, the debates around ‘socially useful finance’ are seldom about reducing the alienation of people from their financial lives. They’re mostly about turning the existing financial sector into a slightly more benign dictatorship. The essence of DIY though, is to band together, not via the enforced hierarchy of the corporation or bureaucracy, but as part of a likeminded community of individuals creatively offering services to each other. So let’s take a look at a few examples of this
Pillar 5: The right to fork
The right to dissent is a crucial component of a democratic society. But for dissent to be effective, it has to be informed and constructive, rather than reactive and regressive. There is much dissent towards the current financial system, but while people are free to voice their displeasure, they find it very difficult to actually act on their displeasure. We may loathe the smug banking oligopoly, but we’re frequently compelled to use them.
Furthermore, much dissent doesn’t have a clear vision of what alternative is sought. This is partially due to the fact that access to financial ‘source code’ is so limited. It’s hard to articulate ideas about what’s wrong when one cannot articulate how the current system operates. Most financial knowledge is held in proprietary formulations and obscure jargon-laden language within the financial sector, and this needs to change. It’s for this reason that I’m building the London School of Financial Activism, so ordinary people can explore the layers of financial code, from the deepest layer – the money itself – and then on to the institutions, instruments and networks that move it around….”
Michael Simmons at Forbes: “There is a debate happening between software developers and scientists: How large can and should our networks be in this evolving world of social media? The answer to this question has dramatic implications for how we look at our own relationship building…
To better understand our limits, I connected with the famous British anthropologist and evolutionary psychologist, Robin Dunbar, creator of his namesake; Dunbar’s number.
Dunbar’s number, 150, is the suggested cognitive limit to the number of relationships we can maintain where both parties are willing to do favors for each other.
Dunbar’s discovery was in finding a very high correlation between the size of a species’ neocortex and the average social group size (see chart to right). The theory predicted 150 for humans, and this number is found throughout human communities over time….
Does Dunbar’s Number Still Apply In Today’s Connected World?
There are two camps when it comes to Dunbar’s number. The first camp is embodied by David Morin, the founder of Path, who built a whole social network predicated on the idea that you cannot have more than 150 friends. Robin Dunbar falls into this camp and even did an academic study on social media’s impact on Dunbar’s number. When I asked for his opinion, he replied:
The 150 limit applies to internet social networking sites just as it does in face-to-face life. Facebook’s own data shows that the average number of friends is 150-250 (within the range of variation in the face-to-face world). Remember that the 150 figure is just the average for the population as a whole. However, those who have more seem to have weaker friendships, suggesting that the amount of social capital is fixed and you can choose to spread it thickly or thinly.
Zvi Band, the founder of Contactually, a rapidly growing, venture-backed, relationship management tool, disagrees with both Morin and Dunbar, “We have the ability as a society to bust through Dunbar’s number. Current software can extend Dunbar’s number by at least 2-3 times.” To understand the power of Contactually and tools like it, we must understand the two paradigms people currently use when keeping in touch: broadcast & one-on-one.
While broadcast email makes it extremely easy to reach lots of people who want to hear from us, it is missing personalization. Personalization is what transforms information diffusion into personal relationship building. To make matters worse, email broadcast open rates have halved in size over the last decade.
On the other end of the spectrum is one-on-one outreach. Research performed by Facebook data scientists shows that one-on-one outreach is extremely effective and explains why:
Both the offering and the receiving of the intimate information increases relationship strength. Providing a partner with personal information expresses trust, encourages reciprocal self-disclosure, and engages the partner in at least some of the details of one’s daily life. Directed communication evokes norms of reciprocity, so may obligate partner to reply. The mere presence of the communication, which is relatively effortful compared to broadcast messages, also signals the importance of the relationship….”
John Tolva: “…We can build upon the success of the work being done at the intersection of technology and urban design, right now.
For one, the whole realm of social enterprise — for-profit startups that seek to solve real social problems — has a huge overlap with urban issues. Impact Engine in Chicago, for instance, is an accelerator squarely focused on meaningful change and profitable businesses. One of their companies, Civic Artworks, has set as its goal rebalancing the community planning process.
The Code for America Accelerator and Tumml, both located in San Francisco, morph the concept of social innovation into civic/urban innovation. The companies nurtured by CfA and Tumml are filled with technologists and urbanists working together to create profitable businesses. Like WorkHands, a kind of LinkedIn for blue collar trades. Would something like this work outside a city? Maybe. Are its effects outsized and scale-ready in a city? Absolutely. That’s the opportunity in urban innovation.
Scale is what powers the sharing economy and it thrives because of the density and proximity of cities. In fact, shared resources at critical density is one of the only good definitions for what a city is. It’s natural that entrepreneurs have overlaid technology on this basic fact of urban life to amplify its effects. Would TaskRabbit, Hailo or LiquidSpace exist in suburbia? Probably, but their effects would be minuscule and investors would get restless. The city in this regard is the platform upon which sharing economy companies prosper. More importantly, companies like this change the way the city is used. It’s not urban planning, but it is urban (re)design and it makes a difference.
A twist that many in the tech sector who complain about cities often miss is that change in a city is not the same thing as change in city government. Obviously they are deeply intertwined; change is mighty hard when it is done at cross-purposes with government leadership. But it happens all the time. Non-government actors — foundations, non-profits, architecture and urban planning firms, real estate developers, construction companies — contribute massively to the shape and health of our cities.
Often this contribution is powered through policies of open data publication by municipal governments. Open data is the raw material of a city, the vital signs of what has happened there, what is happening right now, and the deep pool of patterns for what might happen next.
Tech entrepreneurs would do well to look at the organizations and companies capitalizing on this data as the real change agents, not government itself. Even the data in many cases is generated outside government. Citizens often do the most interesting data-gathering, with tools like LocalData. The most exciting thing happening at the intersection of technology and cities today — what really makes them “smart” — is what is happening at the periphery of city government. It’s easy to belly-ache about government and certainly there are administrations that to do not make data public (or shut it down), but tech companies who are truly interested in city change should know that there are plenty of examples of how to start up and do it.
And yet, the somewhat staid world of architecture and urban-scale design presents the most opportunity to a tech community interested in real urban change. While technology obviously plays a role in urban planning — 3D visual design tools like Revit and mapping services like ArcGIS are foundational for all modern firms — data analytics as a serious input to design matters has only been used in specialized (mostly energy efficiency) scenarios. Where are the predictive analytics, the holistic models, the software-as-a-service providers for the brave new world of urban informatics and The Internet of Things? Technologists, it’s our move.
Something’s amiss when some city governments — rarely the vanguard in technological innovation — have more sophisticated tools for data-driven decision-making than the private sector firms who design the city. But some understand the opportunity. Vannevar Technology is working on it, as is Synthicity. There’s plenty of room for the most positive aspects of tech culture to remake the profession of urban planning itself. (Look to NYU’s Center for Urban Science and Progress and the University of Chicago’s Urban Center for Computation and Data for leadership in this space.)…”
The New York Times: “Computers have entered the age when they are able to learn from their own mistakes, a development that is about to turn the digital world on its head.
The first commercial version of the new kind of computer chip is scheduled to be released in 2014. Not only can it automate tasks that now require painstaking programming — for example, moving a robot’s arm smoothly and efficiently — but it can also sidestep and even tolerate errors, potentially making the term “computer crash” obsolete.
The new computing approach, already in use by some large technology companies, is based on the biological nervous system, specifically on how neurons react to stimuli and connect with other neurons to interpret information. It allows computers to absorb new information while carrying out a task, and adjust what they do based on the changing signals.
In coming years, the approach will make possible a new generation of artificial intelligence systems that will perform some functions that humans do with ease: see, speak, listen, navigate, manipulate and control. That can hold enormous consequences for tasks like facial and speech recognition, navigation and planning, which are still in elementary stages and rely heavily on human programming.
Designers say the computing style can clear the way for robots that can safely walk and drive in the physical world, though a thinking or conscious computer, a staple of science fiction, is still far off on the digital horizon.
“We’re moving from engineering computing systems to something that has many of the characteristics of biological computing,” said Larry Smarr, an astrophysicist who directs the California Institute for Telecommunications and Information Technology, one of many research centers devoted to developing these new kinds of computer circuits.
Conventional computers are limited by what they have been programmed to do. Computer vision systems, for example, only “recognize” objects that can be identified by the statistics-oriented algorithms programmed into them. An algorithm is like a recipe, a set of step-by-step instructions to perform a calculation.
But last year, Google researchers were able to get a machine-learning algorithm, known as a neural network, to perform an identification task without supervision. The network scanned a database of 10 million images, and in doing so trained itself to recognize cats.
In June, the company said it had used those neural network techniques to develop a new search service to help customers find specific photos more accurately.
The new approach, used in both hardware and software, is being driven by the explosion of scientific knowledge about the brain. Kwabena Boahen, a computer scientist who leads Stanford’s Brains in Silicon research program, said that is also its limitation, as scientists are far from fully understanding how brains function.”
Tiago Peixoto: “Having a refined understanding of what leads people to participate is one of the main concerns of those working with citizen engagement. But particularly when it comes to participatory democracy, that understanding is only partial and, most often, the cliché “more research is needed” is definitely applicable. This is so for a number of reasons, four of which are worth noting here.
Precisely for the opposite reasons, our knowledge of electoral participation is in better shape. First, despite the differences between elections, comparative work is relatively easy, which is attested by the high number of cross-country studies in the field. Second, the fact that elections (for the most part) are repeated regularly and following a similar design enables the refinement of hypotheses and research questions over time, and specific time-related analysis (see an example here [PDF]). Third, when compared to the funds allocated to research in participatory initiatives, the relative amount of resources channeled into electoral studies and voting behavior is significantly higher. Here I am not referring to academic work only but also to the substantial resources invested by the private sector and parties towards a better understanding of elections and voting behavior. This includes a growing body of knowledge generated by get-out-the-vote (GOTV) research, with fascinating experimental evidence from interventions that seek to increase participation in elections (e.g. door-to-door campaigns, telemarketing, e-mail). Add to that the wealth of electoral data that is available worldwide (in machine-readable formats) and you have some pretty good knowledge to tap into. Finally, both conceptually and terminologically, the field of electoral studies is much more consistent than the field of citizen engagement which, in the long run, tends to drastically impact how knowledge of a subject evolves.
These reasons should be sufficient to capture the interest of those who work with citizen engagement. While the extent to which the knowledge from the field of electoral participation can be transferred to non-electoral participation remains an open question, it should at least provide citizen engagement researchers with cues and insights that are very much worth considering…”