Design Thinking for the Greater Good


New Book by Jeanne Liedtka, Randy Salzman, and Daisy Azer:  “Facing especially wicked problems, social sector organizations are searching for powerful new methods to understand and address them. Design Thinking for the Greater Good goes in depth on both the how of using new tools and the why. As a way to reframe problems, ideate solutions, and iterate toward better answers, design thinking is already well established in the commercial world. Through ten stories of struggles and successes in fields such as health care, education, agriculture, transportation, social services, and security, the authors show how collaborative creativity can shake up even the most entrenched bureaucracies—and provide a practical roadmap for readers to implement these tools.

The design thinkers Jeanne Liedtka, Randy Salzman, and Daisy Azer explore how major agencies like the Department of Health and Human Services and the Transportation and Security Administration in the United States, as well as organizations in Canada, Australia, and the United Kingdom, have instituted principles of design thinking. In each case, these groups have used the tools of design thinking to reduce risk, manage change, use resources more effectively, bridge the communication gap between parties, and manage the competing demands of diverse stakeholders. Along the way, they have improved the quality of their products and enhanced the experiences of those they serve. These strategies are accessible to analytical and creative types alike, and their benefits extend throughout an organization. This book will help today’s leaders and thinkers implement these practices in their own pursuit of creative solutions that are both innovative and achievable….(More)”.

Responding to problems: actions are rewarded, regardless of the outcome


 at Public Management Review: “When faced with a problem, policymakers have a choice of action or inaction. Psychological research shows varying results on how individuals evaluate (in)actions conditional on the subsequent outcome. I replicate, generalize, and extend this research into a public management setting with two independent experiments embedded in a nationally representative sample of Danish citizens (= 2,007).

Both experiments show that actions are evaluated more positively than inactions – regardless of the outcome. This finding runs contrary to the inaction (or omission) bias but is consistent with evidence on a “norm of action”, in response to poor performance in political–administrative settings….(More)”

Using Social Media To Predict the Future: A Systematic Literature Review


Review by Lawrence Phillips, Chase Dowling, Kyle Shaffer, Nathan Hodas and Svitlana Volkov: “Social media (SM) data provides a vast record of humanity’s everyday thoughts, feelings, and actions at a resolution previously unimaginable. Because user behavior on SM is a reflection of events in the real world, researchers have realized they can use SM in order to forecast, making predictions about the future. The advantage of SM data is its relative ease of acquisition, large quantity, and ability to capture socially relevant information, which may be difficult to gather from other data sources. Promising results exist across a wide variety of domains, but one will find little consensus regarding best practices in either methodology or evaluation. In this systematic review, we examine relevant literature over the past decade, tabulate mixed results across a number of scientific disciplines, and identify common pitfalls and best practices. We find that SM forecasting is limited by data biases, noisy data, lack of generalizable results, a lack of domain-specific theory, and underlying complexity in many prediction tasks. But despite these shortcomings, recurring findings and promising results continue to galvanize researchers and demand continued investigation. Based on the existing literature, we identify research practices which lead to success, citing specific examples in each case and making recommendations for best practices. These recommendations will help researchers take advantage of the exciting possibilities offered by SM platforms….(More)”

#WhereIsMyName ?


Mujb Mashal the New York Times: “These are some of the terms Afghan men use to refer to their wives in public instead of their names, the sharing of which they see as a grave dishonor worthy of violence: Mother of Children, My Household, My Weak One or sometimes, in far corners, My Goat or My Chicken.

Women also may be called Milk-sharer or Black-headed. The go-to word for Afghans to call a woman in public, no matter her status, is Aunt.

But a social media campaign to change this custom has been percolating in recent weeks, initiated by young women. The campaign comes with a hashtag in local languages that addresses the core of the issue and translates as #WhereIsMyName.

The activists’ aim is both to challenge women to reclaim their most basic identity, and to break the deep-rooted taboo that prevents men from mentioning their female relatives’ names in public….

Like many social media efforts, this one began small, with several posts out of Herat Province in the west. Since then, more activists have tried to turn it into a topic of conversation by challenging celebrities and government officials to share the names of their wives and mothers.

The discussion has now made it to the regular media, with articles in newspapers and conversations on television and radio talk shows.

Members of the Parliament, senior government officials and artists have come forward in support, publicly declaring the identities of the female members of their families….(More)”

Data Africa


Data Africa is an open data platform designed to provide information on key themes for research and development such as: agriculture, climate, poverty and child health across Sub-Saharan Africa at the sub-national level. The main goal of the online tool is to present the themes to a wide, even non-technical audience through easily accessible visual narratives.

In its first stage, the platform is focused on national and sub-national level data for 13 countries:

  • Burkina Faso
  • Ethiopia
  • Ghana
  • Kenya
  • Malawi
  • Mali
  • Mozambique
  • Nigeria
  • Rwanda
  • Senegal
  • Tanzania
  • Uganda
  • Zambia

Over time, we anticipate expanding the coverage of the platform with additional countries and increasing the amount of data available through the platform….

The data contained in the online tool draws from a variety of sources, including:

Crowd Research: Open and Scalable University Laboratories


Paper by Rajan Vaish et al: “Research experiences today are limited to a privileged few at select universities. Providing open access to research experiences would enable global upward mobility and increased diversity in the scientific workforce. How can we coordinate a crowd of diverse volunteers on open-ended research? How could a PI have enough visibility into each person’s contributions to recommend them for further study? We present Crowd Research, a crowdsourcing technique that coordinates open-ended research through an iterative cycle of open contribution, synchronous collaboration, and peer assessment. To aid upward mobility and recognize contributions in publications, we introduce a decentralized credit system: participants allocate credits to each other, which a graph centrality algorithm translates into a collectively-created author order. Over 1,500 people from 62 countries have participated, 74% from institutions with low access to research. Over two years and three projects, this crowd has produced articles at top-tier Computer Science venues, and participants have gone on to leading graduate programs….(More)”.

The Implementation of Open Data in Indonesia


Paper by Dani Gunawan and Amalia Amalia: “Nowadays, public demands easy access to nonconfidential government data, such as public digital information on health, industry, and culture that can be accessed on the Internet. This will lead departments within government to be efficient and more transparent. As the results, rapid development of applications will solve citizens’ problems in many sectors. One Data Initiatives is the prove that the Government of Indonesia supports data transparency. This research investigates the implementation of open data in Indonesia based on Tim BernersLee five-star rating and open stage model by Kalampokis. The result shows that mostly data in Indonesia is freely available in the Internet, but most of them are not machine-readable and do not support non-proprietary format. The drawback of Indonesia’s open data is lack of ability to link the existing data with other data sources. Therefore, Indonesia is still making initial steps with data inventories and beginning to publish key datasets of public interest…(More)”

Nudges in a post-truth world


Neil Levy at the Journal of Medical Ethics: “Nudges—policy proposals informed by work in behavioural economics and psychology that are designed to lead to better decision-making or better behaviour—are controversial. Critics allege that they bypass our deliberative capacities, thereby undermining autonomy and responsible agency. In this paper, I identify a kind of nudge I call a nudge to reason, which make us more responsive to genuine evidence. I argue that at least some nudges to reason do not bypass our deliberative capacities. Instead, use of these nudges should be seen as appeals to mechanisms partially constitutive of these capacities, and therefore as benign (so far as autonomy and responsible agency are concerned). I sketch some concrete proposals for nudges to reason which are especially important given the apparent widespread resistance to evidence seen in recent political events….(More)”.

Waste Is Information


Book by Dietmar Offenhuber: “Waste is material information. Landfills are detailed records of everyday consumption and behavior; much of what we know about the distant past we know from discarded objects unearthed by archaeologists and interpreted by historians. And yet the systems and infrastructures that process our waste often remain opaque. In this book, Dietmar Offenhuber examines waste from the perspective of information, considering emerging practices and technologies for making waste systems legible and how the resulting datasets and visualizations shape infrastructure governance. He does so by looking at three waste tracking and participatory sensing projects in Seattle, São Paulo, and Boston.

Offenhuber expands the notion of urban legibility—the idea that the city can be read like a text—to introduce the concept of infrastructure legibility. He argues that infrastructure governance is enacted through representations of the infrastructural system, and that these representations stem from the different stakeholders’ interests, which drive their efforts to make the system legible. The Trash Track project in Seattle used sensor technology to map discarded items through the waste and recycling systems; the Forager project looked at the informal organization processes of waste pickers working for Brazilian recycling cooperatives; and mobile systems designed by the city of Boston allowed residents to report such infrastructure failures as potholes and garbage spills. Through these case studies, Offenhuber outlines an emerging paradigm of infrastructure governance based on a complex negotiation among users, technology, and the city….(More)”.

Rage against the machines: is AI-powered government worth it?


Maëlle Gavet at the WEF: “…the Australian government’s new “data-driven profiling” trial for drug testing welfare recipients, to US law enforcement’s use of facial recognition technology and the deployment of proprietary software in sentencing in many US courts … almost by stealth and with remarkably little outcry, technology is transforming the way we are policed, categorized as citizens and, perhaps one day soon, governed. We are only in the earliest stages of so-called algorithmic regulation — intelligent machines deploying big data, machine learning and artificial intelligence (AI) to regulate human behaviour and enforce laws — but it already has profound implications for the relationship between private citizens and the state….

Some may herald this as democracy rebooted. In my view it represents nothing less than a threat to democracy itself — and deep scepticism should prevail. There are five major problems with bringing algorithms into the policy arena:

  1. Self-reinforcing bias…
  2. Vulnerability to attack…
  3. Who’s calling the shots?…
  4. Are governments up to it?…
  5. Algorithms don’t do nuance….

All the problems notwithstanding, there’s little doubt that AI-powered government of some kind will happen. So, how can we avoid it becoming the stuff of bad science fiction? To begin with, we should leverage AI to explore positive alternatives instead of just applying it to support traditional solutions to society’s perceived problems. Rather than simply finding and sending criminals to jail faster in order to protect the public, how about using AI to figure out the effectiveness of other potential solutions? Offering young adult literacy, numeracy and other skills might well represent a far superior and more cost-effective solution to crime than more aggressive law enforcement. Moreover, AI should always be used at a population level, rather than at the individual level, in order to avoid stigmatizing people on the basis of their history, their genes and where they live. The same goes for the more subtle, yet even more pervasive data-driven targeting by prospective employers, health insurers, credit card companies and mortgage providers. While the commercial imperative for AI-powered categorization is clear, when it targets individuals it amounts to profiling with the inevitable consequence that entire sections of society are locked out of opportunity….(More)”.