Vinton G. Cerf in the Communications of the ACM: “The last several weeks (as of this writing) have been filled with disclosures of intelligence practices in the U.S. and elsewhere. Edward Snowden’s unauthorized release of highly classified information has stirred a great deal of debate about national security and the means used to preserve it.
In the midst of all this, I looked to Jean-Jacques Rousseau’s well-known 18th-century writings on the Social Contract (Du Contrat Social, Ou Principes du Droit Politique) for insight. Distilled and interpreted through my perspective, I took away several notions. One is that in a society, to achieve a degree of safety and stability, we as individuals give up some absolute freedom of action to what Rousseau called the sovereign will of the people. He did not equate this to government, which he argued was distinct and derived its power from the sovereign people.
I think it may be fair to say that most of us would not want to live in a society that had no limits to individual behavior. In such a society, there would be no limit to the potential harm an individual could visit upon others. In exchange for some measure of stability and safety, we voluntarily give up absolute freedom in exchange for the rule of law. In Rousseau’s terms, however, the laws must come from the sovereign people, not from the government. We approximate this in most modern societies creating representative government using public elections to populate the key parts of the government.”
(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.”
Transparent Predictions
New Paper by Tal Zarsky: “Can human behavior be predicted? A broad variety of governmental initiatives are using computerized processes to try. Vast datasets of personal information enhance the ability to engage in these ventures and the appetite to push them forward. Governments have a distinct interest in automated individualized predictions to foresee unlawful actions. Novel technological tools, especially data-mining applications, are making governmental predictions possible. The growing use of predictive practices is generating serious concerns regarding the lack of transparency. Although echoed across the policy, legal, and academic debate, the nature of transparency, in this context, is unclear. Transparency flows from different, even competing, rationales, as well as very different legal and philosophical backgrounds. This Article sets forth a unique and comprehensive conceptual framework for understanding the role transparency must play as a regulatory concept in the crucial and innovative realm of automated predictive modeling.”
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.”
Open Access
Reports by the UK’s House of Commons, Business, Innovation and Skills Committee: “Open access refers to the immediate, online availability of peer reviewed research articles, free at the point of access (i.e. without subscription charges or paywalls). Open access relates to scholarly articles and related outputs. Open data (which is a separate area of Government policy and outside the scope of this inquiry) refers to the availability of the underlying research data itself. At the heart of the open access movement is the principle that publicly funded research should be publicly accessible. Open access expanded rapidly in the late twentieth century with the growth of the internet and digitisation (the transcription of data into a digital form), as it became possible to disseminate research findings more widely, quickly and cheaply.
Whilst there is widespread agreement that the transition to open access is essential in order to improve access to knowledge, there is a lack of consensus about the best route to achieve it. To achieve open access at scale in the UK, there will need to be a shift away from the dominant subscription-based business model. Inevitably, this will involve a transitional period and considerable change within the scholarly publishing market.
For the UK to transition to open access, an effective, functioning and competitive market in scholarly communications will be vital. The evidence we saw over the course of this inquiry shows that this is currently far from the case, with journal subscription prices rising at rates that are unsustainable for UK universities and other subscribers. There is a significant risk that the Government’s current open access policy will inadvertently encourage and prolong the dysfunctional elements of the scholarly publishing market, which are a major barrier to access.
See Volume I and Volume II “
From Networked Publics to Issue Publics: Reconsidering the Public/Private Distinction in Web Science
New paper by Andreas Birkbak: “As an increasing part of everyday life becomes connected with the web in many areas of the globe, the question of how the web mediates political processes becomes still more urgent. Several scholars have started to address this question by thinking about the web in terms of a public space. In this paper, we aim to make a twofold contribution towards the development of the concept of publics in web science. First, we propose that although the notion of publics raises a variety of issues, two major concerns continue to be user privacy and democratic citizenship on the web. Well-known arguments hold that the complex connectivity of the web puts user privacy at risk and enables the enclosure of public debate in virtual echo chambers. Our first argument is that these concerns are united by a set of assumptions coming from liberal political philosophy that are rarely made explicit. As a second contribution, this paper points towards an alternative way to think about publics by proposing a pragmatist reorientation of the public/private distinction in web science, away from seeing two spheres that needs to be kept separate, towards seeing the public and the private as something that is continuously connected. The theoretical argument is illustrated by reference to a recently published case study of Facebook groups, and future research agendas for the study of web-mediated publics are proposed.”
Nudge Nation: A New Way to Prod Students Into and Through College
Ben Wildavsky at EducationSector: “Thanks in part to Thaler and Sunstein’s work, the power of nudges has become well-established—including on many college campuses, where students around the country are beginning the fall semester. While online education and software-driven pedagogy on college campuses have received a good deal of attention, a less visible set of technology-driven initiatives also has gained a foothold: behavioral nudges designed to keep students on track to succeed. Just as e-commerce entrepreneurs have drawn on massive troves of consumer data to create algorithms for firms such as Netflix and Amazon, which unbundle the traditional storefront consumer experience through customized, online delivery, architects of campus technology nudges also rely on data analytics or data mining to improve the student experience.
By giving students information-driven suggestions that lead to smarter actions, technology nudges are intended to tackle a range of problems surrounding the process by which students begin college and make their way to graduation.
New approaches are certainly needed….
There are many reasons for low rates of persistence and graduation, including financial problems, the difficulty of juggling non-academic responsibilities such as work and family, and, for some first-generation students, culture shock. But academic engagement and success are major contributors. That’s why colleges are using behavioral nudges, drawing on data analytics and behavioral psychology, to focus on problems that occur along the academic pipeline:
• Poor student organization around the logistics of going to college
• Unwise course selections that increase the risk of failure and extend time to degree
• Inadequate information about academic progress and the need for academic help
• Unfocused support systems that identify struggling students but don’t directly engage with them
• Difficulty tapping into counseling services
These new ventures, whether originating within colleges or created by outside entrepreneurs, are doing things with data that just couldn’t be done in the past—creating giant databases of student course records, for example, to find patterns of success and failure that result when certain kinds of students take certain kinds of courses.”
Visualizing the legislative process with Sankey diagrams
Kamil Gregor at OpeningParliament.org: “The process of shaping the law often resembles an Indiana Jones maze. Bills and amendments run through an elaborate system of committees, sessions and hearings filled with booby traps before finally reaching the golden idol of a final approval.
Parliamentary monitoring organizations and researchers are often interested in how various pieces of legislation survive in this environment and what are the strategies to either kill or aid them. This specifically means answering two questions: What is the probability of a bill being approved and what factors determine this probability?
The legislative process is usually hierarchical: Successful completion of a step in the process is conditioned by completion of all previous steps. Therefore, we may also want to know the probabilities of completion in each consecutive step and their determinants.
A simple way how to give a satisfying answer to these questions without wandering into the land of nonlinear logistic regressions is the Sankey diagram. It is a famous flow chart in which a process is visualized using arrows. Relative quantities of outcomes in the process are represented by arrows’ widths.
A famous example is a Sankey diagram of Napoleon’s invasion of Russia. We can clearly see how the Grand Army was gradually shrinking as French soldiers were dying or defecting. Another well-known example is the Google Analytics flow chart. It shows how many visitors enter a webpage and then either leave or continue to a different page on the same website. As the number of consecutive steps increases, the number of visitors remaining on the website decreases.
The legislative process can be visualized in the same way. Progress of bills is represented by a stream between various steps in the process and width of the stream corresponds to quantities of bills. A bill can either complete all the steps of the process, or it can “drop out” of it at some point if it gets rejected.
Let’s take a look…”
The Tech Intellectuals
New Essay by Henry Farrell in Democracy: “A quarter of a century ago, Russell Jacoby lamented the demise of the public intellectual. The cause of death was an improvement in material conditions. Public intellectuals—Dwight Macdonald, I.F. Stone, and their like—once had little choice but to be independent. They had difficulty getting permanent well-paying jobs. However, as universities began to expand, they offered new opportunities to erstwhile unemployables. The academy demanded a high price. Intellectuals had to turn away from the public and toward the practiced obscurities of academic research and prose. In Jacoby’s description, these intellectuals “no longer need[ed] or want[ed] a larger public…. Campuses [were] their homes; colleagues their audience; monographs and specialized journals their media.”
Over the last decade, conditions have changed again. New possibilities are opening up for public intellectuals. Internet-fueled media such as blogs have made it much easier for aspiring intellectuals to publish their opinions. They have fostered the creation of new intellectual outlets (Jacobin, The New Inquiry, The Los Angeles Review of Books), and helped revitalize some old ones too (The Baffler, Dissent). Finally, and not least, they have provided the meat for a new set of arguments about how communications technology is reshaping society.
These debates have created opportunities for an emergent breed of professional argument-crafters: technology intellectuals. Like their predecessors of the 1950s and ’60s, they often make a living without having to work for a university. Indeed, the professoriate is being left behind. Traditional academic disciplines (except for law, which has a magpie-like fascination with new and shiny things) have had a hard time keeping up. New technologies, to traditionalists, are suspect: They are difficult to pin down within traditional academic boundaries, and they look a little too fashionable to senior academics, who are often nervous that their fields might somehow become publicly relevant.
Many of these new public intellectuals are more or less self-made. Others are scholars (often with uncomfortable relationships with the academy, such as Clay Shirky, an unorthodox professor who is skeptical that the traditional university model can survive). Others still are entrepreneurs, like technology and media writer and podcaster Jeff Jarvis, working the angles between public argument and emerging business models….
Different incentives would lead to different debates. In a better world, technology intellectuals might think more seriously about the relationship between technological change and economic inequality. Many technology intellectuals think of the culture of Silicon Valley as inherently egalitarian, yet economist James Galbraith argues that income inequality in the United States “has been driven by capital gains and stock options, mostly in the tech sector.”
They might think more seriously about how technology is changing politics. Current debates are still dominated by pointless arguments between enthusiasts who believe the Internet is a model for a radically better democracy, and skeptics who claim it is the dictator’s best friend.
Finally, they might pay more attention to the burgeoning relationship between technology companies and the U.S. government. Technology intellectuals like to think that a powerful technology sector can enhance personal freedom and constrain the excesses of government. Instead, we are now seeing how a powerful technology sector may enable government excesses. Without big semi-monopolies like Facebook, Google, and Microsoft to hoover up personal information, surveillance would be far more difficult for the U.S. government.
Debating these issues would require a more diverse group of technology intellectuals. The current crop are not diverse in some immediately obvious ways—there are few women, few nonwhites, and few non-English speakers who have ascended to the peak of attention. Yet there is also far less intellectual diversity than there ought to be. The core assumptions of public debates over technology get less attention than they need and deserve.”