Big-data analytics: the power of prediction

Curated on Posted on by Stefaan Verhulst

Rachel Willcox in Public Finance: “The ability to anticipate demands will improve planning and financial efficiency, and collecting and analysing data will enable the public sector to look ahead…

Hospitals around the country are well accustomed to huge annual rises in patient numbers as winter demand hits accident and emergency departments. But Wrightington, Wigan and Leigh NHS Foundation Trust (WWL) had to rethink service planning after unprecedented A&E demand during a sunny July 2014, which saw ambulances queuing outside the hospital. The trust now employs computer analysis to help predict and prepare for peaks in demand.

As public sector organisations grapple with ever-tighter savings targets, analysis of a broad range of historical data – big data analytics – offers an opportunity to pre-empt service requirements and so help the public sector manage demand more effectively and target scarce resources better. However, working with data to gain insight and save money is not without its challenges.

At WWL, a partnership with business support provider NHS Shared Business Services – a 50:50 joint venture between the Department of Health and technology firm Sopra Steria – resulted in a project that uses an analysis of historical data and complex algorithms to predict the most likely scenarios. In September, the partners launched HealthIntell, a suite of data reporting tools for A&E, procurement and finance.

The suite includes an application designed to help hospitals better cope with A&E pressures and meet waiting time targets. HealthIntell presents real-time data on attendances at A&E departments to doctors and other decision makers. It can predict demand on a daily and hourly basis, and allows trusts to use their own data to identify peaks and troughs – for example, the likely rise in attendances due to bad weather or major sporting events – to help deploy the right people with the right expertise at the right time….

Rikke Duus, a senior teaching fellow at University College London’s School of Management, agrees strongly that an evidence-based approach to providing services is key to efficiency gains, using data that is already available. Although the use of big data across the public sector is trailing well behind that in the private sector, pressure is mounting for it to catch up. Consumers’ experiences with private sector organisations – in particular the growing personalisation of services – is raising expectations about the sort of public services people expect to receive.

Transparency, openness and integration can benefit consumers, Duus says. “It’s about reinventing the business model to cut costs and improve efficiency. We have to use data to predict and prevent. The public-sector mindset is getting there and the huge repositories of data held across the public sector offer a great starting point, but often they don’t know how to get into it and skills are an issue,” Duus says.

Burgeoning demand for analytics expertise in retail, banking and finance has created a severe skills shortage that is allowing big-data professionals to command an average salary of £55,000 – 31% higher than the average IT position, according to a report published in November 2014 by the Tech Partnership employers’ network and business analytics company SAS. More than three quarters of posts were considered “fairly” or “very” difficult to fill, and the situation is unlikely to have eased in the interim.

Professor Robert Fildes, director of the Lancaster Centre for Forecasting, part of Lancaster University Management School, warns that public sector organisations are at a distinct disadvantage when it comes to competing for such sought-after skills.

The centre has worked on a number of public sector forecasting projects, including a Department of Health initiative to predict pay drift for its non-medical workforce and a scheme commissioned by NHS Blackpool to forecast patient activity.

“The other constraint is data,” Fildes observes. “People talk about data as if it is a uniform value. But the Department of Health doesn’t have any real data on the demand for, say, hip operations. They only have data on the operations they’ve done. The data required for analysis isn’t good enough,” he says….

Despite the challenges, projects are reaping rewards across a variety of public sector organisations. Since 2008, the London Fire Brigade (LFB) has been using software from SAS to prioritise the allocation of fire prevention resources, even pinpointing specific households most at risk of fire. The software brings together around 60 data inputs including demographic information, geographical locations, historical data, land use and deprivation levels to create lifestyle profiles for London households.

Deaths caused by fire in the capital fell by almost 50% between 2010 and 2015, according to the LFB. It attributes much of the reduction to better targeting of around 90,000 home visits the brigade carries out each year, to advise on fire safety….(More)”

 

Understanding Participatory Governance

Curated on Posted on by Stefaan Verhulst

An analysis of “Participants’ Motives for Participation” by Per Gustafson and Nils Hertting: “Despite the growing body of literature on participatory and collaborative governance, little is known about citizens’ motives for participation in such new governance arrangements. The present article argues that knowledge about these motives is essential for understanding the quality and nature of participatory governance and its potential contribution to the overall political and administrative system.

Survey data were used to explore participants’ motives for participating in a large-scale urban renewal program in Stockholm, Sweden. The program was neighborhood-based, characterized by self-selected and repeated participation, and designed to influence local decisions on the use of public resources.

Three types of motives were identified among the participants: (a) Common good motives concerned improving the neighborhood in general and contributing knowledge and competence. (b) Self-interest motives reflected a desire to improve one’s own political efficacy and to promote the interest of one’s own group or family. (c) Professional competence motives represented a largely apolitical type of motive, often based on a professional role. Different motives were expressed by different categories of participants and were also associated with different perceptions concerning program outcomes.

Further analysis suggested that participatory governance may represent both an opportunity for marginalized groups to empower themselves and an opportunity for more privileged groups to act as local “citizen representatives” and articulate the interests of their neighborhoods. These findings call for a more complex understanding of the role and potential benefits of participatory governance…(More).”

 

Core Concepts: Computational social science

Curated on Posted on by Stefaan Verhulst

Adam Mann at PNAS: “Cell phone tower data predicts which parts of London can expect a spike in crime (1). Google searches for polling place information on the day of an election reveal the consequences of different voter registration laws (2). Mathematical models explain how interactions among financial investors produce better yields, and even how they generate economic bubbles (3).

Figure

Using cell-phone and taxi GPS data, researchers classified people in San Francisco into “tribal networks,” clustering them according to their behavioral patterns. Student’s, tourists, and businesspeople all travel through the city in various ways, congregating and socializing in different neighborhoods. Image courtesy of Alex Pentland (Massachusetts Institute of Technology, Cambridge, MA).

Figure

Where people hail from in the Mexico City area, here indicated by different colors, feeds into a crime-prediction model devised by Alex Pentland and colleagues (6). Image courtesy of Alex Pentland (Massachusetts Institute of Technology, Cambridge, MA).

 These are just a few examples of how a suite of technologies is helping bring sociology, political science, and economics into the digital age. Such social science fields have historically relied on interviews and survey data, as well as censuses and other government databases, to answer important questions about human behavior. These tools often produce results based on individuals—showing, for example, that a wealthy, well-educated, white person is statistically more likely to vote (4)—but struggle to deal with complex situations involving the interactions of many different people.

 

A growing field called “computational social science” is now using digital tools to analyze the rich and interactive lives we lead. The discipline uses powerful computer simulations of networks, data collected from cell phones and online social networks, and online experiments involving hundreds of thousands of individuals to answer questions that were previously impossible to investigate. Humans are fundamentally social creatures and these new tools and huge datasets are giving social scientists insights into exactly how connections among people create societal trends or heretofore undetected patterns, related to everything from crime to economic fortunes to political persuasions. Although the field provides powerful ways to study the world, it’s an ongoing challenge to ensure that researchers collect and store the requisite information safely, and that they and others use that information ethically….(More)”

Can We Use Data to Stop Deadly Car Crashes?

Curated on Posted on by Stefaan Verhulst

Allison Shapiro in Pacific Standard Magazine: “In 2014, New York City Mayor Bill de Blasio decided to adopt Vision Zero, a multi-national initiative dedicated to eliminating traffic-related deaths. Under Vision Zero, city services, including the Department of Transportation, began an engineering and public relations plan to make the streets safer for drivers, pedestrians, and cyclists. The plan included street re-designs, improved accessibility measures, and media campaigns on safer driving.

The goal may be an old one, but the approach is innovative: When New York City officials wanted to reduce traffic deaths, they crowdsourced and used data.

Many cities in the United States—from Washington, D.C., all the way to Los Angeles—have adopted some version of Vision Zero, which began in Sweden in 1997. It’s part of a growing trend to make cities “smart” by integrating data collection into things like infrastructure and policing.

Map of high crash corridors in Portland, Oregon. (Map: Portland Bureau of Transportation)
Map of high crash corridors in Portland, Oregon. (Map: Portland Bureau of Transportation)

Cities have access to an unprecedented amount of data about traffic patterns, driving violations, and pedestrian concerns. Although advocacy groups say Vision Zero is moving too slowly, de Blasio has invested another $115 million in this data-driven approach.

Interactive safety map. (Map: District Department of Transportation)
Interactive safety map. (Map: District Department of Transportation)

De Blasio may have been vindicated. A 2015 year-end report released by the city last week analyzes the successes and shortfalls of data-driven city life, and the early results look promising. In 2015, fewer New Yorkers lost their lives in traffic accidents than in any year since 1910, according to the report, despite the fact that the population has almost doubled in those 105 years.

Below are some of the project highlights.

New Yorkers were invited to add to this public dialogue map, where they could list information ranging from “not enough time to cross” to “red light running.” The Department of Transportation ended up with over 10,000 comments, which led to 80 safety projects in 2015, including the creation of protected bike lanes, the introduction of leading pedestrian intervals, and the simplifying of complex intersections….

Data collected from the public dialogue map, town hall meetings, and past traffic accidents led to “changes to signals, street geometry and markings and regulations that govern actions like turning and parking. These projects simplify driving, walking and bicycling, increase predictability, improve visibility and reduce conflicts,” according to Vision Zero in NYC….(More)”

Collective Intelligence in Law Reforms: When the Logic of the Crowds and the Logic of Policymaking Collide

Curated on Posted on by Stefaan Verhulst

Paper by Tanja Aitamurto: “…shows how the two virtues of collective intelligence – cognitive diversity and large crowds –turn into perils in crowdsourced policymaking. That is because of a conflict between the logic of the crowds and the logic of policymaking. The crowd’s logic differs from that of traditional policymaking in several aspects. To mention some of those: In traditional policymaking it is a small group of experts making proposals to the policy, whereas in crowdsourced policymaking, it is a large, anonymous crowd with a mixed level of expertise. The crowd proposes atomic ideas, whereas traditional policymaking is used to dealing with holistic and synthesized proposals. By drawing on data from a crowdsourced law-making process in Finland, the paper shows how the logics of the crowds and policymaking collide in practice. The conflict prevents policymaking fully benefiting from the crowd’s input, and it also hinders governments from adopting crowdsourcing more widely as a practice for deploying open policymaking practices….(More)”

Daedalus Issue on “The Internet”

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Press release: “Thirty years ago, the Internet was a network that primarily delivered email among academic and government employees. Today, it is rapidly evolving into a control system for our physical environment through the Internet of Things, as mobile and wearable technology more tightly integrate the Internet into our everyday lives.

How will the future Internet be shaped by the design choices that we are making today? Could the Internet evolve into a fundamentally different platform than the one to which we have grown accustomed? As an alternative to big data, what would it mean to make ubiquitously collected data safely available to individuals as small data? How could we attain both security and privacy in the face of trends that seem to offer neither? And what role do public institutions, such as libraries, have in an environment that becomes more privatized by the day?

These are some of the questions addressed in the Winter 2016 issue of Daedalus on “The Internet.”  As guest editors David D. Clark (Senior Research Scientist at the MIT Computer Science and Artificial Intelligence Laboratory) and Yochai Benkler (Berkman Professor of Entrepreneurial Legal Studies at Harvard Law School and Faculty Co-Director of the Berkman Center for Internet and Society at Harvard University) have observed, the Internet “has become increasingly privately owned, commercial, productive, creative, and dangerous.”

Some of the themes explored in the issue include:

  • The conflicts that emerge among governments, corporate stakeholders, and Internet users through choices that are made in the design of the Internet
  • The challenges—including those of privacy and security—that materialize in the evolution from fixed terminals to ubiquitous computing
  • The role of public institutions in shaping the Internet’s privately owned open spaces
  • The ownership and security of data used for automatic control of connected devices, and
  • Consumer demand for “free” services—developed and supported through the sale of user data to advertisers….

Essays in the Winter 2016 issue of Daedalus include:

  • The Contingent Internet by David D. Clark (MIT)
  • Degrees of Freedom, Dimensions of Power by Yochai Benkler (Harvard Law School)
  • Edge Networks and Devices for the Internet of Things by Peter T. Kirstein (University College London)
  • Reassembling Our Digital Selves by Deborah Estrin (Cornell Tech and Weill Cornell Medical College) and Ari Juels (Cornell Tech)
  • Choices: Privacy and Surveillance in a Once and Future Internet by Susan Landau (Worcester Polytechnic Institute)
  • As Pirates Become CEOs: The Closing of the Open Internet by Zeynep Tufekci (University of North Carolina at Chapel Hill)
  • Design Choices for Libraries in the Digital-Plus Era by John Palfrey (Phillips Academy)…(More)

See also: Introduction

The Power of the Nudge to Change Our Energy Future

Curated on Posted on by Stefaan Verhulst

Sebastian Berger in the Scientific American: “More than ever, psychology has become influential not only in explaining human behavior, but also as a resource for policy makers to achieve goals related to health, well-being, or sustainability. For example, President Obama signed an executive order directing the government to systematically use behavioral science insights to “better serve the American people.” Not alone in this endeavor, many governments – including the UK, Germany, Denmark, or Australia – are turning to the insights that most frequently stem from psychological researchers, but also include insights from behavioral economics, sociology, or anthropology.

Particularly relevant are the analysis and the setting of “default-options.” A default is the option that a decision maker receives if he or she does not specifically state otherwise. Are we automatically enrolled in a 401(k), are we organ donors by default, or is the flu-shot a standard that is routinely given to all citizens? Research has given us many examples of how and when defaults can promote public safety or wealth.

One of the most important questions facing the planet, however, is how to manage the transition into a carbon-free economy. In a recent paper, Felix Ebeling of the University of Cologne and I tested whether defaults could nudge consumers into choosing a green energy contract over one that relies on conventional energy. The results were striking: setting the default to green energy increased participation nearly tenfold. This is an important result because it tells us that subtle, non-coercive changes in the decision making environment are enough to show substantial differences in consumers’ preferences in the domain of clean energy. It changes green energy participation from “hardly anyone” to “almost everyone”. Merely within the domain of energy behavior, one can think of many applications where this finding can be applied:  For instance, default engines of new cars could be set to hybrid and customers would need to actively switch to standard options. Standard temperatures of washing machines could be low, etc….(More)”

This Is How Visualizing Open Data Can Help Save Lives

Curated on Posted on by Stefaan Verhulst

Alexander Howard at the Huffington Post: “Cities are increasingly releasing data that they can use to make life better for their residents online — enabling journalists and researchers to better inform the public.

Los Angeles, for example, has analyzed data about injuries and deaths on its streets and published it online. Now people can check its conclusions and understand why LA’s public department prioritizes certain intersections.

The impact from these kinds of investments can lead directly to saving lives and preventing injuries. The work is part of a broader effort around the world to make cities safer.

Like New York City, San Francisco and Portland, Oregon, Los Angeles has adopted Sweden’s “Vision Zero” program as part of its strategy for eliminating traffic deaths. California led the nation in bicycle deaths in 2014.

At visionzero.lacity.org, you can see that the City of Los Angeles is using data visualization to identify the locations of “high injury networks,” or the 6 percent of intersections that account for 65 percent of the severe injuries in the area.

CITY OF LOS ANGELES

The work is the result of LA’s partnership with University of South California graduate students. As a result of these analyses, the Los Angeles Police Department has been cracking down on jaywalking near the University of Southern California.

Abhi Nemani, the former chief data officer for LA, explained why the city needed to “go back to school” for help.

“In resource-constrained environments — the environment most cities find themselves in these days — you often have to beg, borrow, and steal innovation; particularly so, when it comes to in-demand resources such as data science expertise,” he told the Huffington Post.

“That’s why in Los Angeles, we opted to lean on the community for support: both the growing local tech sector and the expansive academic base. The academic community, in particular, was eager to collaborate with the city. In fact, most — if not all — local institutions reached out to me at some point asking to partner on a data science project with their graduate students.”

The City of Los Angeles is now working with another member of its tech sector toeliminate traffic deaths. DataScience, based in Culver City, California, received $22 million dollars in funding in December to make predictive insights for customers.

“The City of Los Angeles is very data-driven,” DataScience CEO Ian Swanson told HuffPost. “I commend Mayor Eric Garcetti and the City of Los Angeles on the openness, transparency, and availability of city data initiatives, like Vision Zero, put the City of Los Angeles‘ data into action and improve life in this great city.”

DataScience created an interactive online map showing the locations of collisions involving bicycles across the city….(More)”

Five Studies: How Behavioral Science Can Help in International Development

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 in Pacific Standard: “In 2012, there were 896 million people around the world—12.7 percent of the global population—living on less than two dollars a day. The World Food Programestimates that 795 million people worldwide don’t have enough food to “lead a healthy life”; 25 percent of people living in Sub-Saharan Africa are undernourished. Over three million children die every year thanks to poor nutrition, and hunger is the leading cause of death worldwide. In 2012, just three preventable diseases (pneumonia, diarrhea, and malaria) killed 4,600 children every day.

Last month, the World Bank announced the launch of the Global Insights Initiative (GINI). The initiative, which follows in the footsteps of so-called “nudge units” in the United Kingdom and United States, is the Bank’s effort to incorporate insights from the field of behavioral science into the design of international development programs; too often, those programs failed to account for how people behave in the real world. Development policy, according to the Bank’s 2015 World Development Report, is overdue for a “redesign based on careful consideration of human factors.” Researchers have applauded the announcement, but it raises an interesting question: What can nudges really accomplish in the face of the developing world’s overwhelming poverty and health-care deficits?

In fact, researchers have found that instituting small program changes, informed by a better understanding of people’s motivations and limitations, can have big effects on everything from savings rates to vaccination rates to risky sexual behavior. Here are five studies that demonstrate the benefits of bringing empirical social science into the developing world….(More)”

Eyes on the innovation prize

Curated on Posted on by Stefaan Verhulst

Tim Harford: “In 1737, a self-taught clockmaker from Yorkshire astonished the great scientists of London by solving the most pressing technological problem of the day: how to determine the longitude of a ship at sea. The conventional wisdom was that some kind of astronomical method would be needed. Other inventors suggested crackpot schemes that involved casting magic spells or ringing the world with a circle of outposts that would mark the time with cannon fire.

John Harrison’s solution — simple in principle, fiendishly hard to execute — was to build an accurate clock, one that despite fluctuating temperatures and rolling ocean swells, could show the time at Greenwich while anywhere in the world. Harrison and countless other creative minds were focused on the longitude problem by a £20,000 prize for the person who solved it, several million pounds in today’s money.

Why was the prize necessary? Because ideas are hard to develop and easy to imitate. Harrison’s clocks could, with effort, have been reverse engineered. An astronomical method for finding longitude could have been copied with ease. Inventing something new is for suckers; smart people sit back and rip off the idea later. One way to give non-suckers an incentive to research new ideas, then, is an innovation prize — that is, a substantial cash reward for solving a well-defined problem. (Retrospective awards such as the Nobel Prize are different.)

For decades after Harrison’s triumph, prizes were a well-established approach to the problem of encouraging innovation. Then they fell out of favour, with policymakers instead encouraging innovation with a mix of upfront research grants and patent protection. Now, however, prizes are making a comeback. The most eye-catching examples have been in the private sector: the $1m Netflix prize for improved personalisation of film recommendations or the $10m Ansari X prize for private space flight. Last year Nesta, a UK-based charity for the promotion of innovation, launched a “new longitude prize” of £10m for an improved test for bacterial infections, marking the anniversary of the original prize’s founding in 1714.

But the big money potential is in the public sector. In 2007, several governments (and the Gates Foundation) promised a $1.5bn prize for a vaccine for pneumococcal meningitis. The prize, called an “advanced market commitment”, is structured as a dose-by-dose subsidy rather than one giant cheque. It is being paid out and millions of children have already been vaccinated. Much bigger commitments are possible: before US senator Bernie Sanders began his run for the presidency, he introduced two Senate bills that would have provided almost $100bn a year as medical innovation prizes.

But why are innovation prizes attractive, when the existing system of grants and patents seems to have served us reasonably well so far?…(More)”