Make Democracy Great Again: Let’s Try Some ‘Design Thinking’


Ken Carbone in the Huffington Post: “Allow me to begin with the truth. I’ve never studied political science, run for public office nor held a position in government. For the last forty years I’ve led a design agency working with enduring brands across the globe. As with any experienced person in my profession, I have used research, deductive reasoning, logic and “design thinking“ to solve complex problems and create opportunities. Great brands that are showing their age turn to our agency to get back on course. In this light, I believe American democracy is a prime target for some retooling….

The present campaign cycle has left many voters wondering how such divisiveness and national embarrassment could be happening in the land of the free and home of the brave. This could be viewed as symptomatic of deeper structural problems in our tradition bound 240 year-old democracy. Great brands operate on a “innovate or die” model to insure success. The continual improvement of how a business operates and adapts to market conditions is a sound and critical practice.

Although the current election frenzy will soon be over, I want to examine three challenges to our election process and propose possible solutions for consideration. I’ll use the same diagnostic thinking I use with major corporations:

Term Limits…

Voting and Voter registration…

Political Campaigns…

In June of this year I attended the annual leadership conference of AIGA, the professional association for design, in Raleigh NC. A provocative question posed to a select group of designers was “What would you do if you were Secretary of Design.” The responses addressed issues concerning positive social change, education and Veteran Affairs. The audience was full of several hundred trained professionals whose everyday problem solving methods encourage divergent thinking to explore many solutions (possible or impossible) and then use convergent thinking to select and realize the best resolution. This is the very definition of “design thinking.” That leads to progress….(More)”.

Beyond nudging: it’s time for a second generation of behaviourally-informed social policy


Katherine Curchin at LSE Blog: “…behavioural scientists are calling for a second generation of behaviourally-informed policy. In some policy areas, nudges simply aren’t enough. Behavioural research shows stronger action is required to attack the underlying cause of problems. For example, many scholars have argued that behavioural insights provide a rationale for regulation to protect consumers from manipulation by private sector companies. But what might a second generation of behaviourally-informed social policy look like?

Behavioural insights could provide a justification to change the trajectory of income support policy. Since the 1990s policy attention has focused on the moral character of benefits recipients. Inspired by Lawrence Mead’s paternalist philosophy, governments have tried to increase the resolve of the unemployed to work their way out of poverty. More and more behavioural requirements have been attached to benefits to motivate people to fulfil their obligations to society.

But behavioural research now suggests that these harsh policies are misguided. Behavioural science supports the idea that people often make poor decisions and do things which are not in their long term interests.  But the weakness of individuals’ moral constitution isn’t so much the problem as the unequal distribution of opportunities in society. There are circumstances in which humans are unlikely to flourish no matter how motivated they are.

Normal human psychological limitations – our limited cognitive capacity, limited attention and limited self-control – interact with environment to produce the behaviour that advocates of harsh welfare regimes attribute to permissive welfare. In their book Scarcity, Sendhil Mullainathan and Eldar Shafir argue that the experience of deprivation creates a mindset that makes it harder to process information, pay attention, make good decisions, plan for the future, and resist temptations.

Importantly, behavioural scientists have demonstrated that this mindset can be temporarily created in the laboratory by placing subjects in artificial situations which induce the feeling of not having enough. As a consequence, experimental subjects from middle-class backgrounds suddenly display the short-term thinking and irrational decision making often attributed to a culture of poverty.

Tying inadequate income support to a list of behavioural conditions will most punish those who are suffering most. Empirical studies of welfare conditionality have found that benefit claimants often do not comprehend the complicated rules that apply to them. Some are being punished for lack of understanding rather than deliberate non-compliance.

Behavioural insights can be used to mount a case for a more generous, less punitive approach to income support. The starting point is to acknowledge that some of Mead’s psychological assumptions have turned out to be wrong. The nature of the cognitive machinery humans share imposes limits on how self-disciplined and conscientious we can reasonably expect people living in adverse circumstances to be. We have placed too much emphasis on personal responsibility in recent decades. Why should people internalize the consequences of their behaviour when this behaviour is to a large extent the product of their environment?…(More)”

Self-organised scientific crowds to remedy research bureaucracy


 at EuroScientist: “Imagine a world without peer review committees, project proposals or activity reports. Imagine a world where research funds seamlessly flow where they are best employed, like nutrients in a food-web or materials in a river network. Many scientists would immediately signup to live in such a world.

The Netherlands is set to become the place where this academic paradise will be tested, in the next few years. In July 2016, the Dutch parliament approved a motion related to implementing alternative funding procedures to alleviate the research bureaucracy, which is increasingly burdening scientists. Here EuroScientistinvestigates whether the self-organisation power of the scientific community could help resolve one of researchers’ worse burden.

Self-organisation

The Dutch national funding agency is planning to adopt a radically new system to allocate part of its funding, promoted by ecologist Marten Sheffer, who is professor of aquatic ecology and water quality management at Wageningen University and Research Centre. Under the proposed approach, funds would intially be evenly divided among all scientists in the country. Then, they would each have to allocate half of what they have received to the person who, in their opinion, is the most deserving scientist in their network. Then, the process would be iterated.

The promoters of the system believe that the “wisdom of the crowd” of the scientific community would assigning more funds to the most deserving scientists among them; with minimal amount of paperwork. The Dutch initiative is part of a broader effort to use a scientific approach to improve science.

In other words, it is part of a trend aiming to employ scientific evidence to tweak the social mechanisms of academia. Specifically, findings from what is known as complexity research are increasingly brought forward as a way of reducing bureaucracy, removing red tape, and maximising the time scientists spend in thinking….

Abandoning the current bureaucratic, top-down system to evaluate and fund research, based on labour-intensive peer-review, may not be too much of a loss. “Peer-review is an imperfect, fragile mechanism. Our simulations show that assigning funds at random would not distort too much the results of the traditional mechanism,” says Flaminio Squazzoni, an economist at the University of Brescia, Italy, and the coordinator of the PEERE-New Frontiers of Peer Review COST action.

In reality peer-review is never quite neutral. “If scientists behave perfectly, then peer review works,” Squazzoni explains, “but if strategic motivations are taken into account, like saving time or competition, then the results are worse than random.” Squazzoni believes that automation, economic incentives, or the creation of professional reviewers may improve the situation….(More)”

Power to the People: Addressing Big Data Challenges in Neuroscience by Creating a New Cadre of Citizen Neuroscientists


Jane Roskams and Zoran Popović in Neuron: “Global neuroscience projects are producing big data at an unprecedented rate that informatic and artificial intelligence (AI) analytics simply cannot handle. Online games, like Foldit, Eterna, and Eyewire—and now a new neuroscience game, Mozak—are fueling a people-powered research science (PPRS) revolution, creating a global community of “new experts” that over time synergize with computational efforts to accelerate scientific progress, empowering us to use our collective cerebral talents to drive our understanding of our brain….(More)”

Portugal has announced the world’s first nationwide participatory budget


Graça Fonseca at apolitical:”Portugal has announced the world’s first participatory budget on a national scale. The project will let people submit ideas for what the government should spend its money on, and then vote on which ideas are adopted.

Although participatory budgeting has become increasingly popular around the world in the past few years, it has so far been confined to cities and regions, and no country that we know of has attempted it nationwide. To reach as many people as possible, Portugal is also examining another innovation: letting people cast their votes via ATM machines.

‘It’s about quality of life, it’s about the quality of public space, it’s about the quality of life for your children, it’s about your life, OK?’ Graça Fonseca, the minister responsible, told Apolitical. ‘And you have a huge deficit of trust between people and the institutions of democracy. That’s the point we’re starting from and, if you look around, Portugal is not an exception in that among Western societies. We need to build that trust and, in my opinion, it’s urgent. If you don’t do anything, in ten, twenty years you’ll have serious problems.’

Although the official window for proposals begins in January, some have already been submitted to the project’s website. One suggests equipping kindergartens with technology to teach children about robotics. Using the open-source platform Arduino, the plan is to let children play with the tech and so foster scientific understanding from the earliest age.

Proposals can be made in the areas of science, culture, agriculture and lifelong learning, and there will be more than forty events in the new year for people to present and discuss their ideas.

The organisers hope that it will go some way to restoring closer contact between government and its citizens. Previous projects have shown that people who don’t vote in general elections often do cast their ballot on the specific proposals that participatory budgeting entails. Moreover, those who make the proposals often become passionate about them, campaigning for votes, flyering, making YouTube videos, going door-to-door and so fuelling a public discussion that involves ever more people in the process.

On the other side, it can bring public servants nearer to their fellow citizens by sharpening their understanding of what people want and what their priorities are. It can also raise the quality of public services by directing them more precisely to where they’re needed as well as by tapping the collective intelligence and imagination of thousands of participants….

Although it will not be used this year, because the project is still very much in the trial phase, the use of ATMs is potentially revolutionary. As Fonseca puts it, ‘In every remote part of the country, you might have nothing else, but you have an ATM.’ Moreover, an ATM could display proposals and allow people to vote directly, not least because it already contains a secure way of verifying their identity. At the moment, for comparison, people can vote by text or online, sending in the number from their ID card, which is checked against a database….(More)”.

Wikipedia’s not as biased as you might think


Ananya Bhattacharya in Quartz: “The internet is as open as people make it. Often, people limit their Facebook and Twitter circles to likeminded people and only follow certain subreddits, blogs, and news sites, creating an echo chamber of sorts. In a sea of biased content, Wikipedia is one of the few online outlets that strives for neutrality. After 15 years in operation, it’s starting to see results

Researchers at Harvard Business School evaluated almost 4,000 articles in Wikipedia’s online database against the same entries in Encyclopedia Brittanica to compare their biases. They focused on English-language articles about US politics, especially controversial topics, that appeared in both outlets in 2012.

“That is just not a recipe for coming to a conclusion,” Shane Greenstein, one of the study’s authors, said in an interview. “We were surprised that Wikipedia had not failed, had not fallen apart in the last several years.”

Greenstein and his co-author Feng Zhu categorized each article as “blue” or “red.” Drawing from research in political science, they identified terms that are idiosyncratic to each party. For instance, political scientists have identified that Democrats were more likely to use phrases such as “war in Iraq,” “civil rights,” and “trade deficit,” while Republicans used phrases such as “economic growth,” “illegal immigration,” and “border security.”…

“In comparison to expert-based knowledge, collective intelligence does not aggravate the bias of online content when articles are substantially revised,” the authors wrote in the paper. “This is consistent with a best-case scenario in which contributors with different ideologies appear to engage in fruitful online conversations with each other, in contrast to findings from offline settings.”

More surprisingly, the authors found that the 2.8 million registered volunteer editors who were reviewing the articles also became less biased over time. “You can ask questions like ‘do editors with red tendencies tend to go to red articles or blue articles?’” Greenstein said. “You find a prevalence of opposites attract, and that was striking.” The researchers even identified the political stance for a number of anonymous editors based on their IP locations, and the trend held steadfast….(More)”

Big Data Is Not a Monolith


Book edited by Cassidy R. Sugimoto, Hamid R. Ekbia and Michael Mattioli: “Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies.

The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data’s ramifications. The contributors look at big data’s effect on individuals as it exerts social control through monitoring, mining, and manipulation; big data and society, examining both its empowering and its constraining effects; big data and science, considering issues of data governance, provenance, reuse, and trust; and big data and organizations, discussing data responsibility, “data harm,” and decision making….(More)”

Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective


 et al at Peer J. Computer Science: “Recent advances in Natural Language Processing and Machine Learning provide us with the tools to build predictive models that can be used to unveil patterns driving judicial decisions. This can be useful, for both lawyers and judges, as an assisting tool to rapidly identify cases and extract patterns which lead to certain decisions. This paper presents the first systematic study on predicting the outcome of cases tried by the European Court of Human Rights based solely on textual content. We formulate a binary classification task where the input of our classifiers is the textual content extracted from a case and the target output is the actual judgment as to whether there has been a violation of an article of the convention of human rights. Textual information is represented using contiguous word sequences, i.e., N-grams, and topics. Our models can predict the court’s decisions with a strong accuracy (79% on average). Our empirical analysis indicates that the formal facts of a case are the most important predictive factor. This is consistent with the theory of legal realism suggesting that judicial decision-making is significantly affected by the stimulus of the facts. We also observe that the topical content of a case is another important feature in this classification task and explore this relationship further by conducting a qualitative analysis….(More)”

Essays on collective intelligence


Thesis by Yiftach Nagar: “This dissertation consists of three essays that advance our understanding of collective-intelligence: how it works, how it can be used, and how it can be augmented. I combine theoretical and empirical work, spanning qualitative inquiry, lab experiments, and design, exploring how novel ways of organizing, enabled by advancements in information technology, can help us work better, innovate, and solve complex problems.

The first essay offers a collective sensemaking model to explain structurational processes in online communities. I draw upon Weick’s model of sensemaking as committed-interpretation, which I ground in a qualitative inquiry into Wikipedia’s policy discussion pages, in attempt to explain how structuration emerges as interpretations are negotiated, and then committed through conversation. I argue that the wiki environment provides conditions that help commitments form, strengthen and diffuse, and that this, in turn, helps explain trends of stabilization observed in previous research.

In the second essay, we characterize a class of semi-structured prediction problems, where patterns are difficult to discern, data are difficult to quantify, and changes occur unexpectedly. Making correct predictions under these conditions can be extremely difficult, and is often associated with high stakes. We argue that in these settings, combining predictions from humans and models can outperform predictions made by groups of people, or computers. In laboratory experiments, we combined human and machine predictions, and find the combined predictions more accurate and more robust than predictions made by groups of only people or only machines.

The third essay addresses a critical bottleneck in open-innovation systems: reviewing and selecting the best submissions, in settings where submissions are complex intellectual artifacts whose evaluation require expertise. To aid expert reviewers, we offer a computational approach we developed and tested using data from the Climate CoLab – a large citizen science platform. Our models approximate expert decisions about the submissions with high accuracy, and their use can save review labor, and accelerate the review process….(More)”

100 Stories: The Impact of Open Access


Report by Jean-Gabriel Bankier and Promita Chatterji: “It is time to reassess how we talk about the impact of open access. Early thought leaders in the field of scholarly communications sparked our collective imagination with a compelling vision for open access: improving global access to knowledge, advancing science, and providing greater access to education.1 But despite the fact that open access has gained a sizable foothold, discussions about the impact of open access are often still stuck at the level of aspirational or potential benefit. Shouldn’t we be able to gather real examples of positive outcomes to demonstrate the impact of open access? We need to get more concrete. Measurements like

Measurements like altmetrics and download counts provide useful data about usage, but remain largely indicators of early-level interest rather actual outcomes and benefits. There has been considerable research into how open access affects citation counts,2 but beyond that discussion there is still a gap between the hypothetical societal good of open access and the minutiae of usage and interest measurements. This report begins to bridge that gap by presenting a framework, drawn from 100 real stories that describe the impact of open access. Collected by bepress from across 500 institutions and 1400 journals using Digital Commons as their publishing and/or institutional repository platform, these stories present information about actual outcomes, benefits, and impacts.

This report brings to light the wide variety of scholarly and cultural activity that takes place on university campuses and the benefit resulting from greater visibility and access to these materials. We hope that administrators, authors, students, and others will be empowered to articulate and amplify the impact of their own work. We also created the framework to serve as a tool for stakeholders who are interested in advocating for open access on their campus yet lack the specific vocabulary and suitable examples. Whether it is a librarian hoping to make the case for open access with reluctant administrators or faculty, a faculty member who wants to educate students about changing modes of publishing, a funding agency looking for evidence in support of its open access requirement, or students advocating for educational affordability, the framework and stories themselves can be a catalyst for these endeavors. Put more simply, these are 100 stories to answer the question: “why does open access matter?”…(More)”

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