“The first available textbook on the rapidly growing and increasingly important field of government analytics” edited by Benjamin Ginsberg, Kathy Wagner Hill and Jennifer Bachner: “This first textbook on the increasingly important field of government analytics provides invaluable knowledge and training for students of government in the synthesis, interpretation, and communication of “big data,” which is now an integral part of governance and policy making. Integrating all the major components of this rapidly growing field, this invaluable text explores the intricate relationship of data analytics to governance while providing innovative strategies for the retrieval and management of information….(More)”
Be the Change: Saving the World with Citizen Science
Book by It’s so easy to be overwhelmed by everything that is wrong in the world. In 2010, there were 660,000 deaths from malaria. Dire predictions about climate change suggest that sea levels could rise enough to submerge both Los Angeles and London by 2100. Bees are dying, not by the thousands but by the millions.
But what can you do? You’re just one person, right? The good news is that you *can* do something.
It’s called citizen science, and it’s a way for ordinary people like you and me to do real, honest-to-goodness, help-answer-the-big-questions science.
This book introduces you to a world in which it is possible to go on a wildlife survey in a national park, install software on your computer to search for a cure for cancer, have your smartphone log the sound pollution in your city, transcribe ancient Greek scrolls, or sift through the dirt from a site where a mastodon died 11,000 years ago—even if you never finished high school….(More)”
Tinder for cities: how tech is making urban planning more inclusive
Oliver Wainwright at The Guardian: “Imagine if next time you saw a plan for an oversized monster tower block proposed for your street, you could get out your smartphone and swipe left to oppose it? Or see a carefully designed scheme for a new neighbourhood library and swipe right to support it?
Tinder for urban planning might sound far-fetched, but it is already being trialled in the sun-kissed Californian city of Santa Monica. City authorities are trying to gauge public opinion on everything from street furniture and parking, to murals and market stalls for their forthcoming urban plan, using a digital tool modelled on a dating app.
CitySwipe presents local residents with images of potential scenarios and simple yes/no questions, encouraging people to swipe through the options, as if assessing prospective partners. For the time being, it’s fairly basic: a photo of some street art appears with a caption asking: “Do you want more of this?” Folding cafe tables and chairs are shown next to pink park benches, asking: “Which do you prefer?”
It might sound superficial, but the questions move on to attitudes towards walking, bike lanes, housing and beyond. It makes the consultation process effortless, compared with the usual feedback mechanisms of filling in lengthy mailed-out response forms, downloading wordy PDFs, or being accosted by a chirpy volunteer with a clipboard.
It is one of the many tech tools cropping up in the world of town planning, in a bid to make what has always been an opaque and notoriously confusing system more transparent, inclusive and efficient for the public, planners and developers alike….
US platform Flux Metro has taken the idea a step further and built a 3D model that integrates zoning information with financial viability algorithms, to predict the likely profitability of a scheme in any given scenario. It allows developers to visualise a site’s context and constraints, including building heights and shadows, to inform what might be possible to build….(More)”
The Open Data Movement: Young Activists between Data Disclosure and Digital Reputation
Davide Arcidiacono and Giuseppe Reale in PArtecipazione e COnflitto: “Young citizens show an increasing interest for direct democracy tools and for the building of a new relationship with public administration through the use of digital platforms. The Open Data issue is part of this transformation. The paper analyzes the Open Data issue from the perspective of a spontaneous and informal group of digital activists with the aim of promoting data disclosure. The study is focused mainly on the case of a specific local movement, named Open Data Sicilia (ODS), combining traditional ethnographic observation with an ethnographic approach. The aim of the study is to detect the social profile of the Open Data movement activists, understanding how is it organized their network, what are the common purposes and solidarity models embodied by this type of movement, what are the resources mobilized and their strategies between on-line and off-line. The ODS case appears interesting for its evolution, its strategy and organizational structure: an elitist and technocratic movement that aspires to a broad constituency. It is an expressive or a reformist movement, rather than an anti-system actor, with features that are similar to a lobby. The case study also shows all the typical characteristics of digital activism, with its fluid boundaries between ethical inspiration of civic engagement and individual interests….(More)”
Algorithmic Life
Review of several books by Massimo Mazzotti at LARB: “…As a historian of science, I have been trained to think of algorithms as sets of instructions for solving certain problems — and so as neither glamorous nor threatening. Insert the correct input, follow the instructions, and voilà, the desired output. A typical example would be the mathematical formulas used since antiquity to calculate the position of a celestial body at a given time. In the case of a digital algorithm, the instructions need to be translated into a computer program — they must, in other words, be “mechanizable.” Understood in this way — as mechanizable instructions — algorithms were around long before the dawn of electronic computers. Not only were they implemented in mechanical calculating devices, they were used by humans who behaved in machine-like fashion. Indeed, in the pre-digital world, the very term “computer” referred to a human who performed calculations according to precise instructions — like the 200 women trained at the University of Pennsylvania to perform ballistic calculations during World War II. In her classic article “When Computers Were Women,” historian Jennifer Light recounts their long-forgotten story, which takes place right before those algorithmic procedures were automated by ENIAC, the first electronic general-purpose computer.
Terse definitions have now disappeared, however. We rarely use the word “algorithm” to refer solely to a set of instructions. Rather, the word now usually signifies a program running on a physical machine — as well as its effects on other systems. Algorithms have thus become agents, which is partly why they give rise to so many suggestive metaphors. Algorithms now do things. They determine important aspects of our social reality. They generate new forms of subjectivity and new social relationships. They are how a billion-plus people get where they’re going. They free us from sorting through multitudes of irrelevant results. They drive cars. They manufacture goods. They decide whether a client is creditworthy. They buy and sell stocks, thus shaping all-powerful financial markets. They can even be creative; indeed, according to engineer and author Christopher Steiner, they have already composed symphonies “as moving as those composed by Beethoven.”
Do they, perhaps, do too much? That’s certainly the opinion of a slew of popular books on the topic, with titles like Automate This: How Algorithms Took Over Our Markets, Our Jobs, and the World.
Algorithms have captured the scholarly imagination every bit as much as the popular one. Academics variously describe them as a new technology, a particular form of decision-making, the incarnation of a new epistemology, the carriers of a new ideology, and even as a veritable modern myth — a way of saying something, a type of speech that naturalizes beliefs and worldviews. In an article published in 2009 entitled “Power Through the Algorithm,” sociologist David Beer describes algorithms as expressions of a new rationality and form of social organization. He’s onto something fundamental that’s worth exploring further: scientific knowledge and machines are never just neutral instruments. They embody, express, and naturalize specific cultures — and shape how we live according to the assumptions and priorities of those cultures….(More)”
Big data and the measurement of public organizations’ performance and efficiency: The state-of-the-art
Nicky Rogge, Tommaso Agasisti, and Kristof De Witte in Public Policy and Administration: “The increasing availability of statistical data raises opportunities for ‘big’ data and learning analytics. Here, we review the academic literature and research relating to the use of big data analytics in the public sector, and its contribution to public organizations’ performance and efficiency. We outline the advantages as well as the limitations of using big data in public sector organizations and identify research gaps in recent studies and interesting areas for future research….(More)”
Citizenship, Social Media, and Big Data
Homero Gil de Zúñiga and Trevor Diehl introducing Special Issue of the Social Science Computer Review: “This special issue of the Social Science Computer Review provides a sample of the latest strategies employing large data sets in social media and political communication research. The proliferation of information communication technologies, social media, and the Internet, alongside the ubiquity of high-performance computing and storage technologies, has ushered in the era of computational social science. However, in no way does the use of źbig dataź represent a standardized area of inquiry in any field. This article briefly summarizes pressing issues when employing big data for political communication research. Major challenges remain to ensure the validity and generalizability of findings. Strong theoretical arguments are still a central part of conducting meaningful research. In addition, ethical practices concerning how data are collected remain an area of open discussion. The article surveys studies that offer unique and creative ways to combine methods and introduce new tools while at the same time address some solutions to ethical questions. (See Table of Contents)”
Using GitHub in Government: A Look at a New Collaboration Platform
Justin Longo at the Center for Policy Informatics: “…I became interested in the potential for using GitHub to facilitate collaboration on text documents. This was largely inspired by the 2012 TED Talk by Clay Shirky where he argued that open source programmers could teach us something about how to do open governance:
Somebody put up a tool during the copyright debate last year in the Senate, saying, “It’s strange that Hollywood has more access to Canadian legislators than Canadian citizens do. Why don’t we use GitHub to show them what a citizen-developed bill might look like?” …
For this research, we undertook a census of Canadian government and public servant accounts on GitHub and surveyed those users, supplemented by interviews with key government technology leaders.
This research has now been published in the journal Canadian Public Administration. (If you don’t have access to the full document through the publisher, you can also find it here).
Despite the growing enthusiasm for GitHub (mostly from those familiar with open source software development), and the general rhetoric in favour of collaboration, we suspected that getting GitHub used in public sector organizations for text collaboration might be an uphill battle – not least of which because of the steep learning curve involved in using GitHub, and its inflexibility when being used to edit text.
The history of computer-supported collaborative work platforms is littered with really cool interfaces that failed to appeal to users. The experience to date with GitHub in Canadian governments reflects this, as far as our research shows.
We found few government agencies having an active presence on GitHub compared to social media presence in general. And while federal departments and public servants on GitHub are rare, provincial, territorial, First Nations and local governments are even rarer.
For individual accounts held by public servants, most were found in the federal government at higher rates than those found in broader society (see Mapping Collaborative Software). Within this small community, the distribution of contributions per user follows the classic long-tail distribution with a small number of contributors responsible for most of the work, a larger number of contributors doing very little on average, and many users contributing nothing.
GitHub is still resisted by all but the most technically savvy. With a peculiar terminology and work model that presupposes a familiarity with command line computer operations and the language of software coding, using GitHub presents many barriers to the novice user. But while it is tempting to dismiss GitHub, as it currently exists, as ill-suited as a collaboration tool to support document writing, it holds potential as a useful platform for facilitating collaboration in the public sector.
As an example, to help understand how GitHub might be used within governments for collaboration on text documents, we discuss a briefing note document flow in the paper (see the paper for a description of this lovely graphic).
A few other finding are addressed in the paper, from why public servants may choose not to collaborate even though they believe it’s the right thing to do, to an interesting story about what propelled the use of GitHub in the government of Canada in the first place….(More)”
Can artificial intelligence wipe out bias unconscious bias from your workplace?
Lydia Dishman at Fast Company: “Unconscious bias is exactly what it sounds like: The associations we make whenever we face a decision are buried so deep (literally—the gland responsible for this, the amygdala, is surrounded by the brain’s gray matter) that we’re as unaware of them as we are of having to breathe.
So it’s not much of a surprise that Ilit Raz, cofounder and CEO of Joonko, a new application that acts as diversity “coach” powered by artificial intelligence, wasn’t even aware at first of the unconscious bias she was facing as a woman in the course of a normal workday. Raz’s experience coming to grips with that informs the way she and her cofounders designed Joonko to work.
The tool joins a crowded field of AI-driven solutions for the workplace, but most of what’s on the market is meant to root out bias in recruiting and hiring. Joonko, by contrast, is setting its sights on illuminating unconscious bias in the types of workplace experiences where few people even think to look for it….
so far, a lot of these resources have been focused on addressing the hiring process. An integral part of the problem, after all, is getting enough diverse candidates in the recruiting pipeline so they can be considered for jobs. Apps like Blendoor hide a candidate’s name, age, employment history, criminal background, and even their photo so employers can focus on qualifications. Interviewing.io’s platform even masks applicants’ voices. Text.io uses AI to parse communications in order to make job postings more gender-neutral. Unitive’s technology also focuses on hiring, with software designed to detect unconscious bias in Applicant Tracking Systems that read resumes and decide which ones to keep or scrap based on certain keywords.
But as Intel recently discovered, hiring diverse talent doesn’t always mean they’ll stick around. And while one 2014 estimate by Margaret Regan, head of the global diversity consultancy FutureWork Institute, found that 20% of large U.S. employers with diversity programs now provide unconscious-bias training—a number that could reach 50% by next year—that training doesn’t always work as intended. The reasons why vary, from companies putting programs on autopilot and expecting them to run themselves, to the simple fact that many employees who are trained ultimately forget what they learned a few days later.
Joonko doesn’t solve these problems. “We didn’t even start with recruiting,” Raz admits. “We started with task management.” She explains that when a company finally hires a diverse candidate, it needs to understand that the best way to retain them is to make sure they feel included and are given the same opportunities as everyone else. That’s where Joonko sees an opening…(More)”.
Data Maturity Framework
Center for Data Science and Public Policy: “Want to know if your organization is ready to start a data-driven social impact project? See where you are in our data maturity framework and how to improve your organizational, tech, and data readiness.
The Data Maturity Framework has three content areas:
- Problem Definition
- Data and Technology Readiness
- Organizational Readiness
The Data Maturity Framework consists of:
- A questionnaire and survey to assess readiness
- Data and Technology Readiness Matrix
- Organizational Readiness Matrix
The framework materials can be downloaded here, and you can complete our survey here. When we collect enough responses from enough organizations, we’ll launch an aggregate benchmarking report around the state of data in non-profits and government organizations. We ask that each problem be entered as a separate entry (rather than multiple problems from one organization entered in the same response).
We have adapted the Data Maturity Framework for specific projects:
- Lead-prevention project: organizational readiness and data and tech readiness…(More)”.