Jathan Sadowski in the Atlantic on “Eleven principles for relating to cities that are automated and smart: Over half of the world’s population lives in urban environments, and that number is rapidly growing according to the World Health Organization. Many of us interact with the physical environments of cities on a daily basis: the arteries that move traffic, the grids that energize our lives, the buildings that prevent and direct actions. For many tech companies, though, much of this urban infrastructure is ripe for a digital injection. Cities have been “dumb” for millennia. It’s about time they get “smart” — or so the story goes….
Before accepting the techno-hype as a fait accompli, we should consider the implications such widespread technological changes might have on society, politics, and life in general. Urban scholar and historian Lewis Mumford warned of “megamachines” where people become mere components — like gears and transistors — in a hierarchical, human machine. The proliferation of smart projects requires an updated way of thinking about their possibilities, complications, and effects.
A new book, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, by Anthony Townsend, a research director at the Institute for the Future, provides some groundwork for understanding how these urban projects are occurring and what guiding principles we might use in directing their development. Townsend sets out to sketch a new understanding of “civics,” one that will account for new technologies.
The foundation for his theory speaks to common, worthwhile concerns: “Until now, smart-city visions have been controlling us. What we need is a new social code to bring meaning and to exert control over the technological code of urban operating systems.” It’s easy to feel like technologies — especially urban ones that are, at once, ubiquitous and often unseen to city-dwellers — have undue influence over our lives. Townsend’s civics, which is based on eleven principles, looks to address, prevent, and reverse that techno-power.”
Cyberpsychology and New Media
A thematic reader, edited by Andrew Power, Grainne Kirwan: “Cyberpsychology is the study of human interactions with the internet, mobile computing and telephony, games consoles, virtual reality, artificial intelligence, and other contemporary electronic technologies. The field has grown substantially over the past few years and this book surveys how researchers are tackling the impact of new technology on human behaviour and how people interact with this technology.
Examining topics as diverse as online dating, social networking, online communications, artificial intelligence, health-information seeking behaviour, education online, online therapies and cybercrime, Cyberpsychology and New Media book provides an in-depth overview of this burgeoning field, and allows those with little previous knowledge to gain an appreciation of the diversity of the research being undertaken in the area.”
(Appropriate) Big Data for Climate Resilience?
Amy Luers at the Stanford Social Innovation Review: “The answer to whether big data can help communities build resilience to climate change is yes—there are huge opportunities, but there are also risks.
Opportunities
- Feedback: Strong negative feedback is core to resilience. A simple example is our body’s response to heat stress—sweating, which is a natural feedback to cool down our body. In social systems, feedbacks are also critical for maintaining functions under stress. For example, communication by affected communities after a hurricane provides feedback for how and where organizations and individuals can provide help. While this kind of feedback used to rely completely on traditional communication channels, now crowdsourcing and data mining projects, such as Ushahidi and Twitter Earthquake detector, enable faster and more-targeted relief.
- Diversity: Big data is enhancing diversity in a number of ways. Consider public health systems. Health officials are increasingly relying on digital detection methods, such as Google Flu Trends or Flu Near You, to augment and diversify traditional disease surveillance.
- Self-Organization: A central characteristic of resilient communities is the ability to self-organize. This characteristic must exist within a community (see the National Research Council Resilience Report), not something you can impose on it. However, social media and related data-mining tools (InfoAmazonia, Healthmap) can enhance situational awareness and facilitate collective action by helping people identify others with common interests, communicate with them, and coordinate efforts.
Risks
- Eroding trust: Trust is well established as a core feature of community resilience. Yet the NSA PRISM escapade made it clear that big data projects are raising privacy concerns and possibly eroding trust. And it is not just an issue in government. For example, Target analyzes shopping patterns and can fairly accurately guess if someone in your family is pregnant (which is awkward if they know your daughter is pregnant before you do). When our trust in government, business, and communities weakens, it can decrease a society’s resilience to climate stress.
- Mistaking correlation for causation: Data mining seeks meaning in patterns that are completely independent of theory (suggesting to some that theory is dead). This approach can lead to erroneous conclusions when correlation is mistakenly taken for causation. For example, one study demonstrated that data mining techniques could show a strong (however spurious) correlation between the changes in the S&P 500 stock index and butter production in Bangladesh. While interesting, a decision support system based on this correlation would likely prove misleading.
- Failing to see the big picture: One of the biggest challenges with big data mining for building climate resilience is its overemphasis on the hyper-local and hyper-now. While this hyper-local, hyper-now information may be critical for business decisions, without a broader understanding of the longer-term and more-systemic dynamism of social and biophysical systems, big data provides no ability to understand future trends or anticipate vulnerabilities. We must not let our obsession with the here and now divert us from slower-changing variables such as declining groundwater, loss of biodiversity, and melting ice caps—all of which may silently define our future. A related challenge is the fact that big data mining tends to overlook the most vulnerable populations. We must not let the lure of the big data microscope on the “well-to-do” populations of the world make us blind to the less well of populations within cities and communities that have more limited access to smart phones and the Internet.”
San Francisco To Test Online Participatory Budgeting
Crunch.gov: “Taxpayers are sometimes the best people to decide how their money gets spent — sounds obvious, but usually we don’t have a direct say beyond who we elect. That’s changing for San Francisco residents.
It intends to be the first major US city to allow citizens to directly vote on portions of budget via the web. While details are still coming together, its plan is for each city district to vote on $100,000 in expenditures. Citizens will get to choose how the money is spent from a list of options, similar to the way they already vote from a list of ballot propositions. Topical experts will help San Francisco residents deliberate online.
So-called “participatory budgeting” first began in the festival city of Porto Alegre, Brazil, in 1989, and has slowly been expanding throughout the world. While major cities, such as Chicago and New York, have piloted participatory budgeting, they have not incorporated the modern features of digital voting and deliberation that are currently utilized in Brazil.
According to participatory budgeting expert and former White House technology fellow, Hollie Russon Gilman, San Francisco’s experiment will mark a “frontier” in American direct democracy.
This is significant because the Internet engenders a different type of democracy: not one of mere expression, but one of ideas. The net is good at surfacing the best ideas hidden within the wisdom of the crowds. Modern political scientists refer to this as “Epistemic Democracy,” derived from the Greek word for knowledge, epistēmē. Epistemic Democracy values citizens most for their expertise and builds tools to make policy making more informed.
For example, participatory budgeting has been found to reduce infant mortality rates in Brazil. It turns out that the mothers in Brazil had a better knowledge of why children were dying than health experts. Through participatory budgeting, they “channeled a larger fraction of their total budget to key investments in sanitation and health services,” writes Sonia Goncalves of King’s College London. “I also found that this change in the composition of municipal expenditures is associated with a pronounced reduction in the infant mortality rates for municipalities which adopted participatory budgeting.” [PDF]”
Three ways to think of the future…
Geoff Mulgan’s blog: “Here I suggest three complementary ways of thinking about the future which provide partial protection against the pitfalls.
The shape of the future
First, create your own composite future by engaging with the trends. There are many methods available for mapping the future – from Foresight to scenarios to the Delphi method.
Behind all are implicit views about the shapes of change. Indeed any quantitative exploration of the future uses a common language of patterns (shown in this table above) which summarises the fact that some things will go up, some go down, some change suddenly and some not at all.
All of us have implicit or explicit assumptions about these. But it’s rare to interrogate them systematically and test whether our assumptions about what fits in which category are right.
Let’s start with the J shaped curves. Many of the long-term trends around physical phenomena look J-curved: rising carbon emissions, water useage and energy consumption have been exponential in shape over the centuries. As we know, physical constraints mean that these simply can’t go on – the J curves have to become S shaped sooner or later, or else crash. That is the ecological challenge of the 21st century.
New revolutions
But there are other J curves, particularly the ones associated with digital technology. Moore’s Law and Metcalfe’s Law describe the dramatically expanding processing power of chips, and the growing connectedness of the world. Some hope that the sheer pace of technological progress will somehow solve the ecological challenges. That hope has more to do with culture than evidence. But these J curves are much faster than the physical ones – any factor that doubles every 18 months achieves stupendous rates of change over decades.
That’s why we can be pretty confident that digital technologies will continue to throw up new revolutions – whether around the Internet of Things, the quantified self, machine learning, robots, mass surveillance or new kinds of social movement. But what form these will take is much harder to predict, and most digital prediction has been unreliable – we have Youtube but not the Interactive TV many predicted (when did you last vote on how a drama should end?); relatively simple SMS and twitter spread much more than ISDN or fibre to the home. And plausible ideas like the long tail theory turned out to be largely wrong.
If the J curves are dramatic but unusual, much more of the world is shaped by straight line trends – like ageing or the rising price of disease that some predict will take costs of healthcare up towards 40 or 50% of GDP by late in the century, or incremental advances in fuel efficiency, or the likely relative growth of the Chinese economy.
Also important are the flat straight lines – the things that probably won’t change in the next decade or two: the continued existence of nation states not unlike those of the 19th century? Air travel making use of fifty year old technologies?
Great imponderables
If the Js are the most challenging trends, the most interesting ones are the ‘U’s’- the examples of trends bending: like crime which went up for a century and then started going down, or world population that has been going up but could start going down in the later part of this century, or divorce rates which seem to have plateaued, or Chinese labour supply which is forecast to turn down in the 2020s.
No one knows if the apparently remorseless upward trends of obesity and depression will turn downwards. No one knows if the next generation in the West will be poorer than their parents. And no one knows if democratic politics will reinvent itself and restore trust. In every case, much depends on what we do. None of these trends is a fact of nature or an act of God.
That’s one reason why it’s good to immerse yourself in these trends and interrogate what shape they really are. Out of that interrogation we can build a rough mental model and generate our own hypotheses – ones not based on the latest fashion or bestseller but hopefully on a sense of what the data shows and in particular what’s happening to the deltas – the current rates of change of different phenomena.”
Patients Take Control of Their Health Care Online
MIT Technology Review: “Patients are collaborating for better health — and, just maybe, radically reduced health-care costs….Not long ago, Sean Ahrens managed flare-ups of his Crohn’s disease—abdominal pain, vomiting, diarrhea—by calling his doctor and waiting a month for an appointment, only to face an inconclusive array of possible prescriptions. Today, he can call on 4,210 fellow patients in 66 countries who collaborate online to learn which treatments—drugs, diets, acupuncture, meditation, even do-it-yourself infusions of intestinal parasites —bring the most relief.
The online community Ahrens created and launched two years ago, Crohnology.com, is one of the most closely watched experiments in digital health. It lets patients with Crohn’s, colitis, and other inflammatory bowel conditions track symptoms, trade information on different diets and remedies, and generally care for themselves.
The site is at the vanguard of the growing “e-patient” movement that is letting patients take control over their health decisions—and behavior—in ways that could fundamentally change the economics of health care. Investors are particularly interested in the role “peer-to-peer” social networks could play in the $3 trillion U.S. health-care market.
“Patients sharing data about how they feel, the type of treatments they’re using, and how well they’re working is a new behavior,” says Malay Gandhi, chief strategy officer of Rock Health, a San Francisco incubator for health-care startups that invested in Crohnology.com. “If you can get consumers to engage in their health for 15 to 30 minutes a day, there’s the largest opportunity in digital health care.”
Experts say when patients learn from each other, they tend to get fewer tests, make fewer doctors’ visits, and also demand better treatment. “It can lead to better quality, which in many cases will be way more affordable,” says Bob Kocher, an oncologist and former adviser to the Obama administration on health policy.”
Open data for accountable governance: Is data literacy the key to citizen engagement?
Camilla Monckton at UNDP’s Voices of Eurasia blog: “How can technology connect citizens with governments, and how can we foster, harness, and sustain the citizen engagement that is so essential to anti-corruption efforts?
UNDP has worked on a number of projects that use technology to make it easier for citizens to report corruption to authorities:
- Serbia’s SMS corruption reporting in the health sector
- Montenegro’s ‘be responsible app’
- Kosovo’s online corruption reporting site kallxo.com
These projects are showing some promising results, and provide insights into how a more participatory, interactive government could develop.
At the heart of the projects is the ability to use citizen generated data to identify and report problems for governments to address….
Wanted: Citizen experts
As Kenneth Cukier, The Economist’s Data Editor, has discussed, data literacy will become the new computer literacy. Big data is still nascent and it is impossible to predict exactly how it will affect society as a whole. What we do know is that it is here to stay and data literacy will be integral to our lives.
It is essential that we understand how to interact with big data and the possibilities it holds.
Data literacy needs to be integrated into the education system. Educating non-experts to analyze data is critical to enabling broad participation in this new data age.
As technology advances, key government functions become automated, and government data sharing increases, newer ways for citizens to engage will multiply.
Technology changes rapidly, but the human mind and societal habits cannot. After years of closed government and bureaucratic inefficiency, adaptation of a new approach to governance will take time and education.
We need to bring up a generation that sees being involved in government decisions as normal, and that views participatory government as a right, not an ‘innovative’ service extended by governments.
What now?
In the meantime, while data literacy lies in the hands of a few, we must continue to connect those who have the technological skills with citizen experts seeking to change their communities for the better – as has been done in many a Social Innovation Camps recently (in Montenegro, Ukraine and Armenia at Mardamej and Mardamej Relaoded and across the region at Hurilab).
The social innovation camp and hackathon models are an increasingly debated topic (covered by Susannah Vila, David Eaves, Alex Howard and Clay Johnson).
On the whole, evaluations are leading to newer models that focus on greater integration of mentorship to increase sustainability – which I readily support. However, I do have one comment:
Social innovation camps are often criticized for a lack of sustainability – a claim based on the limited number of apps that go beyond the prototype phase. I find a certain sense of irony in this, for isn’t this what innovation is about: Opening oneself up to the risk of failure in the hope of striking something great?
In the words of Vinod Khosla:
“No failure means no risk, which means nothing new.”
As more data is released, the opportunity for new apps and new ways for citizen interaction will multiply and, who knows, someone might come along and transform government just as TripAdvisor transformed the travel industry.”
Coase’s theories predicted Internet’s impact on how business is done
Don Tapscott in The Globe and Mail: “Renowned economist Ronald Coase died last week at the age of 102. Among his many achievements, Mr. Coase was awarded the 1991 Nobel Prize in Economics, largely for his inspiring 1937 paper The Nature of the Firm. The Nobel committee applauded the academic for his “discovery and clarification of the significance of transaction costs … for the institutional structure and functioning of the economy.”
Mr. Coase’s enduring legacy may well be that 60 years later, his paper and theories help us understand the Internet’s impact on business, the economy and all our institutions… Mr. Coase wondered why there was no market within the firm. Why is it unprofitable to have each worker, each step in the production process, become an independent buyer and seller? Why doesn’t the draftsperson auction their services to the engineer? Why is it that the engineer does not sell designs to the highest bidder? Mr. Coase argued that preventing this from happening created marketplace friction.
Mr. Coase argued that this friction gave rise to transaction costs – or to put it more broadly, collaboration or relationship costs. There are three types of these relationship costs. First are search costs, such as the hunt for appropriate suppliers. Second are contractual costs, including price and contract negotiations. Third are the co-ordination costs of meshing the different products and processes.
The upshot is that most vertically integrated corporations found it cheaper and simpler to perform most functions in-house, rather than incurring the cost, hassle and risk of constant transactions with outside partners….This is no longer the case. Many behemoths have lost market share to more supple competitors. Digital technologies slash transaction and collaboration costs. Smart companies are making their boundaries porous, using the Internet to harness knowledge, resources and capabilities outside the company. Everywhere,leading firms set a context for innovation and then invite their customers, partners and other third parties to co-create their products and services.
Today’s economic engines are Internet-based clusters of businesses. While each company retains its identity, companies function together, creating more wealth than they could ever hope to create individually. Where corporations were once gigantic, new business ecosystems tend toward the amorphous.
Procter & Gamble now gets 60 per cent of its innovation from outside corporate walls. Boeing has built a massive ecosystem to design and manufacture jumbo jets. China’s motorcycle industry, which consists of dozens of companies collaborating with no single company pulling the strings, now comprises 40 per cent of global motorcycle production.
Looked at one way, Amazon.com is a website with many employees that ships books. Looked at another way, however, Amazon is a vast ecosystem that includes authors, publishers, customers who write reviews for the site, delivery companies like UPS, and tens of thousands of affiliates that market products and arrange fulfilment through the Amazon network. Hundreds of thousands of people are involved in Amazon’s viral marketing network.
This is leading to the biggest change to the corporation in a century and altering how we orchestrate capability to innovate, create goods and services and engage with the world. From now on, the ecosystem itself, not the corporation per se, should serve as the point of departure for every business strategist seeking to understand the new economy – and for every manager, entrepreneur and investor seeking to prosper in it.
Nor does the Internet tonic apply only to corporations. The Web is dropping transaction costs everywhere – enabling networked approaches to almost every institution in society, from government, media, science and health care to our energy grid, transportation systems and institutions for global problem solving.
Governments can change from being vertically integrated, industrial-age bureaucracies to become networks. By releasing their treasures of raw data, governments can now become platforms upon which companies, NGOs, academics, foundations, individuals and other government agencies can collaborate to create public value…”
Public Open Data: The Good, the Bad, the Future
Camille Crittenden at IDEALAB: “Some of the most powerful tools combine official public data with social media or other citizen input, such as the recent partnership between Yelp and the public health departments in New York and San Francisco for restaurant hygiene inspection ratings. In other contexts, such tools can help uncover and ultimately reduce corruption by making it easier to “follow the money.”
Despite the opportunities offered by “free data,” this trend also raises new challenges and concerns, among them, personal privacy and security. While attention has been devoted to the unsettling power of big data analysis and “predictive analytics” for corporate marketing, similar questions could be asked about the value of public data. Does it contribute to community cohesion that I can find out with a single query how much my neighbors paid for their house or (if employed by public agencies) their salaries? Indeed, some studies suggest that greater transparency leads not to greater trust in government but to resignation and apathy.
Exposing certain law enforcement data also increases the possibility of vigilantism. California law requires the registration and publication of the home addresses of known sex offenders, for instance. Or consider the controversy and online threats that erupted when, shortly after the Newtown tragedy, a newspaper in New York posted an interactive map of gun permit owners in nearby counties.
…Policymakers and officials must still mind the “big data gap.”So what does the future hold for open data? Publishing data is only one part of the information ecosystem. To be useful, tools must be developed for cleaning, sorting, analyzing and visualizing it as well. …
For-profit companies and non-profit watchdog organizations will continue to emerge and expand, building on the foundation of this data flood. Public-private partnerships such as those between San Francisco and Appallicious or Granicus, startups created by Code for America’s Incubator, and non-partisan organizations like the Sunlight Foundation and MapLight rely on public data repositories for their innovative applications and analysis.
Making public data more accessible is an important goal and offers enormous potential to increase civic engagement. To make the most effective and equitable use of this resource for the public good, cities and other government entities should invest in the personnel and equipment — hardware and software — to make it universally accessible. At the same time, Chief Data Officers (or equivalent roles) should also be alert to the often hidden challenges of equity, inclusion, privacy, and security.”
Nonsectarian Welfare Statements
New Paper by Cass Sunstein: “How can we measure whether national institutions in general, and regulatory institutions in particular, are dysfunctional? A central question is whether they are helping a nation’s citizens to live good lives. A full answer to that question would require a great deal of philosophical work, but it should be possible to achieve an incompletely theorized agreement on a kind of nonsectarian welfarism, emphasizing the importance of five variables: subjective well-being, longevity, health, educational attainment, and per capita income. In principle, it would be valuable to identify the effects of new initiatives (including regulations) on all of these variables. In practice, it is not feasible to do so; assessments of subjective well-being present particular challenges. In their ideal form, Regulatory Impact Statements should be seen as Nonsectarian Welfare Statements, seeking to identify the consequences of regulatory initiatives for various components of welfare. So understood, they provide reasonable measures of regulatory success or failure, and hence a plausible test of dysfunction. There is a pressing need for improved evaluations, including both randomized controlled trials and ex post assessments.”