science

Making the Case for Evidence-Based Decision-Making

Curated on December 6, 2016August 3, 2018 by Stefaan Verhulst

Jennifer Brooks in Stanford Social Innovation Review: “After 15 years of building linkages between evidence, policy, and practice in social programs for children and families, I have one thing to say about our efforts to promote evidence-based decision-making: We have failed to capture the hearts and minds of the majority of decision-makers in the United States.

I’ve worked with state and federal leadership, as well as program administrators in the public and nonprofit spheres. Most of them just aren’t with us. They aren’t convinced that the payoffs of evidence-based practice (the method that uses rigorous tests to assess the efficacy of a given intervention) are worth the extra difficulty or expense of implementing those practices.

Why haven’t we gotten more traction for evidence-based decision-making? Three key reasons: 1) we have wasted time debating whether randomized control trials are the optimal approach, rather than building demand for more data-based decision-making; 2) we oversold the availability of evidence-based practices and underestimated what it takes to scale them; and 3) we did all this without ever asking what problems decision-makers are trying to solve.

If we want to gain momentum for evidence-based practice, we need to focus more on figuring out how to implement such approaches on a larger scale, in a way that uses data to improve programs on an ongoing basis….

We must start by understanding and analyzing the problem the decision-maker wants to solve. We need to offer more than lists of evidence-based strategies or interventions. What outcomes do the decision-makers want to achieve? And what do data tell us about why we aren’t getting those outcomes with current methods?…

None of the following ideas is rocket science, nor am I the first person to say them, but they do suggest ways that we can move beyond our current approaches in promoting evidence-based practice.

1. We need better data.

As Michele Jolin pointed out recently, few federal programs have sufficient resources to build or use evidence. There are limited resources for evaluation and other evidence-building activities, which too often are seen as “extras.” Moreover, many programs at the local, state, and national level have minimal information to use for program management and even fewer staff with the skills required to use it effectively…

2. We should attend equally to practices and to the systems in which they sit.

Systems improvements without changes in practice won’t get outcomes, but without systems reforms, evidence-based practices will have difficulty scaling up. …

3. You get what you pay for.

One fear I have is that we don’t actually know whether we can get better outcomes in our public systems without spending more money. And yet cost-savings seem to be what we promise when we sell the idea of evidence-based practice to legislatures and budget directors….

4. We need to hold people accountable for program results and promote ongoing improvement.

There is an inherent tension between using data for accountability and using it for program improvement….(More)”

How the Circle Line rogue train was caught with data

Curated on December 5, 2016August 3, 2018 by Stefaan Verhulst

Daniel Sim at the Data.gov.sg Blog: “Singapore’s MRT Circle Line was hit by a spate of mysterious disruptions in recent months, causing much confusion and distress to thousands of commuters.

Like most of my colleagues, I take a train on the Circle Line to my office at one-north every morning. So on November 5, when my team was given the chance to investigate the cause, I volunteered without hesitation.

From prior investigations by train operator SMRT and the Land Transport Authority (LTA), we already knew that the incidents were caused by some form of signal interference, which led to loss of signals in some trains. The signal loss would trigger the emergency brake safety feature in those trains and cause them to stop randomly along the tracks.

But the incidents — which first happened in August — seemed to occur at random, making it difficult for the investigation team to pinpoint the exact cause.

We were given a dataset compiled by SMRT that contained the following information:

Date and time of each incident
Location of incident
ID of train involved
Direction of train…

LTA and SMRT eventually published a joint press release on November 11 to share the findings with the public….

When we first started, my colleagues and I were hoping to find patterns that may be of interest to the cross-agency investigation team, which included many officers at LTA, SMRT and DSTA. The tidy incident logs provided by SMRT and LTA were instrumental in getting us off to a good start, as minimal cleaning up was required before we could import and analyse the data. We were also gratified by the effective follow-up investigations by LTA and DSTA that confirmed the hardware problems on PV46.

From the data science perspective, we were lucky that incidents happened so close to one another. That allowed us to identify both the problem and the culprit in such a short time. If the incidents were more isolated, the zigzag pattern would have been less apparent, and it would have taken us more time — and data — to solve the mystery….(More).”

Using Cloud Computing to Untangle How Trees Can Cool Cities

Curated on November 27, 2016August 3, 2018 by Stefaan Verhulst

Timothy Boucher at CoolGreenScience: “We’ve all used Google Earth — to explore remote destinations around the world or to check out our house from above. But Google Earth Engine is a valuable tool for conservationists and geographers like myself that allows us to tackle some tricky remote-sensing analysis.

After having completed a few smaller spatial science projects in the cloud (mostly on the Google Earth Engine, or GEE, platform), I decided to give it a real workout — by analyzing more than 300 gigabytes of data across 28 United States and seven Chinese cities.

This project was part of a larger study looking at trees in cities. Why trees? Trees provide numerous valuable ecosystem services to communities: benefits associated with air and water quality, energy conservation, cooler air temperatures, and many other environmental and social benefits.

It’s easy to understand the benefits of trees: stand outside on a hot sunny day and you immediately feel cooler in the shade of a tree. But what’s not as obvious as the cooling effect are tree’s ability to remove particulate matter (PM_2.5) floating around in the air we breath. And this important, as this type of air pollution is implicated in the deaths of ~3 million people per year.

The Conservancy researched the relationship between city air quality and the cooling effects of trees. Results of this study will inform the Global Cities Program initiative on Planting Healthy Air for cities — the objective being to show how much trees can clean and cool, how much it will cost, and so forth….(More)”

New Institute Pushes the Boundaries of Big Data

Curated on November 23, 2016August 3, 2018 by Stefaan Verhulst

Press Release: “Each year thousands of genomes are sequenced, millions of neuronal activity traces are recorded, and light from hundreds of millions of galaxies is captured by our newest telescopes, all creating datasets of staggering size. These complex datasets are then stored for analysis.

Ongoing analysis of these information streams has illuminated a problem, however: Scientists’ standard methodologies are inadequate to the task of analyzing massive quantities of data. The development of new methods and software to learn from data and to model — at sufficient resolution — the complex processes they reflect is now a pressing concern in the scientific community.

To address these challenges, the Simons Foundation has launched a substantial new internal research group called the Flatiron Institute (FI). The FI is the first multidisciplinary institute focused entirely on computation. It is also the first center of its kind to be wholly supported by private philanthropy, providing a permanent home for up to 250 scientists and collaborating expert programmers all working together to create, deploy and support new state-of-the-art computational methods. Few existing institutions support the combination of scientists and programmers, instead leaving programming to relatively impermanent graduate students and postdoctoral fellows, and none have done so at the scale of the Flatiron Institute or with such a broad scope, at a single location.

The institute will hold conferences and meetings and serve as a focal point for computational science around the world….(More)”.

Playing politics: exposing the flaws of nudge thinking

Curated on November 20, 2016August 3, 2018 by Stefaan Verhulst

Book Review by Pat Kane in The New Scientist: “The cover of this book echoes its core anxiety. A giant foot presses down on a sullen, Michael Jackson-like figure – a besuited citizen coolly holding off its massive weight. This is a sinister image to associate with a volume (and its author, Cass Sunstein) that should be able to proclaim a decade of success in the government’s use of “behavioural science”, or nudge theory. But doubts are brewing about its long-term effectiveness in changing public behaviour – as well as about its selective account of evolved human nature.

Sunstein insists that the powers that be cannot avoid nudging us. Every shop floor plan, every new office design, every commercial marketing campaign, every public information campaign, is an “architecting of choices”. As anyone who ever tried to leave IKEA quickly will suspect, that endless, furniture-strewn path to the exit is no accident.

Nudges “steer people in particular directions, but also allow them to go their own way”. They are entreaties to change our habits, to accept old or new norms, but they presume thatwe are ultimately free to refuse the request.

However, our freedom is easily constrained by “cognitive biases”. Our brains, say the nudgers, are lazy, energy-conserving mechanisms, often overwhelmed by information. So a good way to ensure that people pay into their pensions, for example, is to set payment as a “default” in employment contracts, so the employee has to actively untick the box. Defaults of all kinds exploit our preference for inertia and the status quo in order to increase future security….

Sunstein makes useful distinctions between nudges and the other things governments and enterprises can do. Nudges are not “mandates” (laws, regulations, punishments). A mandate would be, for example, a rigorous and well-administered carbon tax, secured through a democratic or representative process. A “nudge” puts smiley faces on your energy bill, and compares your usage to that of the eco-efficient Joneses next door (nudgers like to game our herd-like social impulses).

In a fascinating survey section, which asks Americans and others what they actually think about being the subjects of the “architecting” of their choices, Sunstein discovers that “if people are told that they are being nudged, they will react adversely and resist”.

This is why nudge thinking may be faltering – its understanding of human nature unnecessarily (and perhaps expediently) downgrades our powers of conscious thought….(More)

See The Ethics of Influence: Government in the age of behavioral science Cass R. Sunstein, Cambridge University Press

Embracing Digital Democracy: A Call for Building an Online Civic Commons

Curated on November 19, 2016August 3, 2018 by Stefaan Verhulst

John Gastil and Robert C. Richards Jr. in Political Science & Politics (Forthcoming): “Recent advances in online civic engagement tools have created a digital civic space replete with opportunities to craft and critique laws and rules or evaluate candidates, ballot measures, and policy ideas. These civic spaces, however, remain largely disconnected from one another, such that tremendous energy dissipates from each civic portal. Long-term feedback loops also remain rare. We propose addressing these limitations by building an integrative online commons that links together the best existing tools by making them components in a larger “Democracy Machine.” Drawing on gamification principles, this integrative platform would provide incentives for drawing new people into the civic sphere, encouraging more sustained and deliberative engagement, and feedback back to government and citizen alike to improve how the public interfaces with the public sector. After describing this proposed platform, we consider the most challenging problems it faces and how to address them….(More)”

Who Is Doing Computational Social Science?

Curated on November 19, 2016August 3, 2018 by Stefaan Verhulst

Trends in Big Data Research, a Sage Whitepaper: “Information of all kinds is now being produced, collected, and analyzed at unprecedented speed, breadth, depth, and scale. The capacity to collect and analyze massive data sets has already transformed fields such as biology, astronomy, and physics, but the social sciences have been comparatively slower to adapt, and the path forward is less certain. For many, the big data revolution promises to ask, and answer, fundamental questions about individuals and collectives, but large data sets alone will not solve major social or scientific problems. New paradigms being developed by the emerging field of “computational social science” will be needed not only for research methodology, but also for study design and interpretation, cross-disciplinary collaboration, data curation and dissemination, visualization, replication, and research ethics (Lazer et al., 2009). SAGE Publishing conducted a survey with social scientists around the world to learn more about researchers engaged in big data research and the challenges they face, as well as the barriers to entry for those looking to engage in this kind of research in the future. We were also interested in the challenges of teaching computational social science methods to students. The survey was fully completed by 9412 respondents, indicating strong interest in this topic among our social science contacts. Of respondents, 33 percent had been involved in big data research of some kind and, of those who have not yet engaged in big data research, 49 percent (3057 respondents) said that they are either “definitely planning on doing so in the future” or “might do so in the future.”…(More)”

The ethical impact of data science

Curated on November 19, 2016July 19, 2019 by Stefaan Verhulst

Theme issue of Phil. Trans. R. Soc. A compiled and edited by Mariarosaria Taddeo and Luciano Floridi: “This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations—the interactions among hardware, software and data—rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments….(More)”

Table of Contents:

The dynamics of big data and human rights: the case of scientific research; Effy Vayena, John Tasioulas
Facilitating the ethical use of health data for the benefit of society: electronic health records, consent and the duty of easy rescue; Sebastian Porsdam Mann, Julian Savulescu, Barbara J. Sahakian
Faultless responsibility: on the nature and allocation of moral responsibility for distributed moral actions; Luciano Floridi
Compelling truth: legal protection of the infosphere against big data spills; Burkhard Schafer
Locating ethics in data science: responsibility and accountability in global and distributed knowledge production systems; Sabina Leonelli
Privacy is an essentially contested concept: a multi-dimensional analytic for mapping privacy; Deirdre K. Mulligan, Colin Koopman, Nick Doty
Beyond privacy and exposure: ethical issues within citizen-facing analytics; Peter Grindrod
The ethics of smart cities and urban science; Rob Kitchin
The ethics of big data as a public good: which public? Whose good? Linnet Taylor
Data philanthropy and the design of the infraethics for information societies; Mariarosaria Taddeo
The opportunities and ethics of big data: practical priorities for a national Council of Data Ethics; Olivia Varley-Winter, Hetan Shah
Data science ethics in government; Cat Drew
The ethics of data and of data science: an economist’s perspective; Jonathan Cave
What’s the good of a science platform? John Gallacher

Open Data Collection (PLOS)

Curated on November 15, 2016August 20, 2018 by Stefaan Verhulst

Daniella Lowenberg, Amy Ross, Emma Ganley at PLOS: “In the spirit of Open Con and highlighting the state of Open Data, PLOS is proud to release our Open Data Collection. The many values of Open Data are becoming increasingly apparent, and as a result, we are seeing an adoption of Open Data policies across publishers, funders and organizations. Open Data has proven a fantastic tool to help evaluate the replicability of published research, and even politicians are taking a stand in favor of Open Data as a mechanism to advance science rapidly. In March of 2014, PLOS updated our Data Policy to reflect the need for the underlying data to be as open as the paper itself resulting in complete transparency of the research. Two and-a-half years later, we have seen over 60,000 published papers with open data sets and an increase in submissions reflecting open data practices and policies….

To create this Open Data Collection, we exhaustively searched for relevant articles published across PLOS that discuss open data in some way. Then, in collaboration with our external advisor, Melissa Haendel, we have selected 26 of those articles with the aim to highlight a broad scope of research articles, guidelines, and commentaries about data sharing, data practices, and data policies from different research fields. Melissa has written an engaging blog post detailing the rubric and reasons behind her selections….(More)”

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

Curated on November 15, 2016August 3, 2018 by Stefaan Verhulst

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)”.