Geographic Citizen Science Design


Book edited by Artemis Skarlatidou and Muki Haklay: “Little did Isaac Newton, Charles Darwin and other ‘gentlemen scientists’ know, when they were making their scientific discoveries, that some centuries later they would inspire a new field of scientific practice and innovation, called citizen science. The current growth and availability of citizen science projects and relevant applications to support citizen involvement is massive; every citizen has an opportunity to become a scientist and contribute to a scientific discipline, without having any professional qualifications. With geographic interfaces being the common approach to support collection, analysis and dissemination of data contributed by participants, ‘geographic citizen science’ is being approached from different angles.

Geographic Citizen Science Design takes an anthropological and Human-Computer Interaction (HCI) stance to provide the theoretical and methodological foundations to support the design, development and evaluation of citizen science projects and their user-friendly applications. Through a careful selection of case studies in the urban and non-urban contexts of the Global North and South, the chapters provide insights into the design and interaction barriers, as well as on the lessons learned from the engagement of a diverse set of participants; for example, literate and non-literate people with a range of technical skills, and with different cultural backgrounds.

Looking at the field through the lenses of specific case studies, the book captures the current state of the art in research and development of geographic citizen science and provides critical insight to inform technological innovation and future research in this area….(More)”.

Digital platforms for development: Foundations and research agenda


Paper by Carla Bonina, Kari Koskinen, Ben Eaton, and Annabelle Gawer: “Digital platforms hold a central position in today’s world economy and are said to offer a great potential for the economies and societies in the global South. Yet, to date, the scholarly literature on digital platforms has largely concentrated on business while their developmental implications remain understudied. In part, this is because digital platforms are a challenging research object due to their lack of conceptual definition, their spread across different regions and industries, and their intertwined nature with institutions, actors and digital technologies. The purpose of this article is to contribute to the ongoing debate in information systems and ICT4D research to understand what digital platforms mean for development. To do so, we first define what digital platforms are and differentiate between transaction and innovation platforms, and explain their key characteristics in terms of purpose, research foundations, material properties and business models. We add the socio‐technical context digital platforms operate and the linkages to developmental outcomes. We then conduct an extensive review to explore what current areas, developmental goals, tensions and issues emerge in the literature on platforms and development and identify relevant gaps in our knowledge. We later elaborate on six research questions to advance the studies on digital platforms for development: on indigenous innovation, digital platforms and institutions, on exacerbation of inequalities, on alternative forms of value, on the dark side of platforms and on the applicability of the platform typology for development….(More)”.

Rising to the Challenge: how to get the best value from using prizes to drive innovation for development


Report by Cheryl Brown, Catherine Gould, Clare Stott: “An innovation inducement prize enables funders to pursue development goals without them having to know in advance which approaches or participants are most likely to succeed. Innovation prizes also often directly engage with the intended beneficiaries or those connected with them, in solving the problems.

At a time when development spending is under increasing pressure to show value for money (VFM), innovation prizes are considered as an alternative to mainstream funding options. While costs are likely to have accrued through prize design and management, no cash payments are made until the prize is successfully awarded. The funder may anticipate obtaining more results than those directly paid for through the prize award.

The purpose of this report is to answer two questions: do innovation prizes work for development, and if so, when do they offer value over other forms of funding?

To date, few evaluations have been published that would help funders answer these questions for themselves. DFID commissioned the Ideas to Impact programme, which was delivered by an IMC Worldwide-led consortium and evaluated by Itad, to fill this gap by testing a range of innovation prizes targeted at different development issues and this report synthesises the findings from the evaluations and follow-up reviews of six of these prizes….(More)”.

A Matter of Trust: Building Integrity into Data, Statistics and Records to Support the Achievement of the Sustainable Development Goals


Book edited by Anne Thurston: ” The United Nations Sustainable Development Goals initiative has the potential to set the direction for a future world that works for everyone. Approved by 193 United Nations member countries in September 2016 to help guide global and national development policies through the year 2030, the seventeen goals build on the successes of the Millennium Development Goals, but also include new priority areas, such as climate change, economic inequality, innovation, sustainable consumption, peace, and justice. Assessed against commonly agreed targets and indicators, the goals should facilitate inter-governmental cooperation and the development of regional and even global development strategies. This book explores, through a series of case studies, the substantial challenges for assembling reliable data and statistics to address pressing development challenges, particularly in Africa. By highlighting the enormous potential value of creating and using high quality data, statistics, and records as an interconnected resource and describing how this can be achieved, the book will contribute to defining meaningful and realistic global and national development policies in the critical period to 2030….(More)”.

Tackling Societal Challenges with Open Innovation


Introduction to Special Issue of California Management Review by Anita M. McGahan, Marcel L. A. M. Bogers, Henry Chesbrough, and Marcus Holgersson: “Open innovation includes external knowledge sources and paths to market as complements to internal innovation processes. Open innovation has to date been driven largely by business objectives, but the imperative of social challenges has turned attention to the broader set of goals to which open innovation is relevant. This introduction discusses how open innovation can be deployed to address societal challenges—as well as the trade-offs and tensions that arise as a result. Against this background we introduce the articles published in this Special Section, which were originally presented at the sixth Annual World Open Innovation Conference….(More)”.

How Tech Companies Can Advance Data Science for Social Good


Essay by Nick Martin: “As the world struggles to achieve the UN’s Sustainable Development Goals (SDGs), the need for reliable data to track our progress is more important than ever. Government, civil society, and private sector organizations all play a role in producing, sharing, and using this data, but their information-gathering and -analysis efforts have been able to shed light on only 68 percent of the SDG indicators so far, according to a 2019 UN study.

To help fill the gap, the data science for social good (DSSG) movement has for years been making datasets about important social issues—such as health care infrastructure, school enrollment, air quality, and business registrations—available to trusted organizations or the public. Large tech companies such as Facebook, Google, Amazon, and others have recently begun to embrace the DSSG movement. Spurred on by advances in the field, the Development Data Partnership, the World Economic Forum’s 2030Vision consortium, and Data Collaboratives, they’re offering information about social media users’ mobility during COVID-19, cloud computing infrastructure to help nonprofits analyze large datasets, and other important tools and services.

But sharing data resources doesn’t mean they’ll be used effectively, if at all, to advance social impact. High-impact results require recipients of data assistance to inhabit a robust, holistic data ecosystem that includes assets like policies for safely handling data and the skills to analyze it. As tech firms become increasingly involved with using data and data science to help achieve the SDGs, it’s important that they understand the possibilities and limitations of the nonprofits and other civil society organizations they’re working with. Without a firm grasp on the data ecosystems of their partners, all the technical wizardry in the world may be for naught.

Companies must ask questions such as: What incentives or disincentives are in place for nonprofits to experiment with data science in their work? What gaps remain between what nonprofits or data scientists need and the resources funders provide? What skills must be developed? To help find answers, TechChange, an organization dedicated to using technology for social good, partnered with Project17, Facebook’s partnerships-led initiative to accelerate progress on the SDGs. Over the past six months, the team led interviews with top figures in the DSSG community from industry, academia, and the public sector. The 14 experts shared numerous insights into using data and data science to advance social good and the SDGs. Four takeaways emerged from our conversations and research…(More)”.

Algorithmic Colonisation of Africa Read


Abeba Birhane at The Elephant: “The African equivalents of Silicon Valley’s tech start-ups can be found in every possible sphere of life around all corners of the continent—in “Sheba Valley” in Addis Abeba, “Yabacon Valley” in Lagos, and “Silicon Savannah” in Nairobi, to name a few—all pursuing “cutting-edge innovations” in sectors like banking, finance, healthcare, and education. They are headed by technologists and those in finance from both within and outside the continent who seemingly want to “solve” society’s problems, using data and AI to provide quick “solutions”. As a result, the attempt to “solve” social problems with technology is exactly where problems arise. Complex cultural, moral, and political problems that are inherently embedded in history and context are reduced to problems that can be measured and quantified—matters that can be “fixed” with the latest algorithm.

As dynamic and interactive human activities and processes are automated, they are inherently simplified to the engineers’ and tech corporations’ subjective notions of what they mean. The reduction of complex social problems to a matter that can be “solved” by technology also treats people as passive objects for manipulation. Humans, however, far from being passive objects, are active meaning-seekers embedded in dynamic social, cultural, and historical backgrounds.

The discourse around “data mining”, “abundance of data”, and “data-rich continent” shows the extent to which the individual behind each data point is disregarded. This muting of the individual—a person with fears, emotions, dreams, and hopes—is symptomatic of how little attention is given to matters such as people’s well-being and consent, which should be the primary concerns if the goal is indeed to “help” those in need. Furthermore, this discourse of “mining” people for data is reminiscent of the coloniser’s attitude that declares humans as raw material free for the taking. Complex cultural, moral, and political problems that are inherently embedded in history and context are reduced to problems that can be measured and quantified Data is necessarily always about something and never about an abstract entity.

The collection, analysis, and manipulation of data potentially entails monitoring, tracking, and surveilling people. This necessarily impacts people directly or indirectly whether it manifests as change in their insurance premiums or refusal of services. The erasure of the person behind each data point makes it easy to “manipulate behavior” or “nudge” users, often towards profitable outcomes for companies. Considerations around the wellbeing and welfare of the individual user, the long-term social impacts, and the unintended consequences of these systems on society’s most vulnerable are pushed aside, if they enter the equation at all. For companies that develop and deploy AI, at the top of the agenda is the collection of more data to develop profitable AI systems rather than the welfare of individual people or communities. This is most evident in the FinTech sector, one of the prominent digital markets in Africa. People’s digital footprints, from their interactions with others to how much they spend on their mobile top ups, are continually surveyed and monitored to form data for making loan assessments. Smartphone data from browsing history, likes, and locations is recorded forming the basis for a borrower’s creditworthiness.

Artificial Intelligence technologies that aid decision-making in the social sphere are, for the most part, developed and implemented by the private sector whose primary aim is to maximise profit. Protecting individual privacy rights and cultivating a fair society is therefore the least of their concerns, especially if such practice gets in the way of “mining” data, building predictive models, and pushing products to customers. As decision-making of social outcomes is handed over to predictive systems developed by profit-driven corporates, not only are we allowing our social concerns to be dictated by corporate incentives, we are also allowing moral questions to be dictated by corporate interest.

“Digital nudges”, behaviour modifications developed to suit commercial interests, are a prime example. As “nudging” mechanisms become the norm for “correcting” individuals’ behaviour, eating habits, or exercise routines, those developing predictive models are bestowed with the power to decide what “correct” is. In the process, individuals that do not fit our stereotypical ideas of a “fit body”, “good health”, and “good eating habits” end up being punished, outcast, and pushed further to the margins. When these models are imported as state-of-the-art technology that will save money and “leapfrog” the continent into development, Western values and ideals are enforced, either deliberately or intentionally….(More)”.

This app is helping mothers in the Brazilian favelas survive the pandemic



Daniel Avelar at Open Democracy: “As Brazil faces one of the worst COVID-19 outbreaks in the world, a smartphone app is helping residents of impoverished areas known as favelas survive the virus threat amid sudden mass unemployment.

So far, the Latin American country has recorded over 115.000 deaths caused by COVID-19. The shutdown of economic activity wiped out 7.8 million jobs, mostly affecting low-skilled informal workers who form the bulk of the population in the favelas. Emergency income distributed by the government is limited to 60% of the minimum wage, so families are struggling to make ends meet.

Many blame president Jair Bolsonaro for the tragedy. Bolsonaro, a far-right populist, has consistently rallied against science-based policies in the management of the pandemic and pushed for an end to stay-at-home orders. A precocious reopening of the economy is likely to increase infection rates and cause more deaths.

In an attempt to stop the looming humanitarian catastrophe, a coalition of activists in the favelas and corporate partners developed an app that is facilitating the distribution of food and emergency income to thousands of women spearheading families. The app has a facial recognition feature that helps volunteers identify and register recipients of aid and prevents fraud.

So far, the Favela Mothers project has distributed the equivalent to US$ 26 million in food parcels and cash allowances to more than 1.1 million families in 5,000 neighborhoods across the country….(More)”.

Making Open Development Inclusive: Lessons from IDRC Research


Book edited by Matthew L. Smith and Ruhiya Kristine Seward: “A decade ago, a significant trend in using and supporting open practices emerged in international development. “Open development” describes initiatives as wide-ranging as open government and data, open science, open education, and open innovation. The driving theory was that these types of open practices enable more inclusive processes of human development. This volume, drawing on ten years of empirical work and research, analyzes how open development has played out in practice.

Focusing on development practices in the Global South, the contributors assess the crucial questions of who is able to participate and benefit from open practices, and who cannot. Examining a wide range of cases, they offer a macro analysis of how open development ecosystems are governed, and evaluate the inclusiveness of a variety of applications, including creating open educational resources, collaborating in science and knowledge production, and crowdsourcing information….(More)”.

Digital government in developing countries


Essay by Yasodara Córdova and Tiago Peixoto: “According to the World Bank’s Digital Dividends report, fewer than 20 percent of digital government projects are successes. Particularly in developing countries, these numbers are often associated with a number of challenges: limited funding, stretched implementation capacity, and political instability, to name a few. Yet, even in developing countries, despite similar conditions, some projects seem to fare better than others. Why is that? 

The projects we have worked with in the global south have followed a similar pattern. While there were successes, many projects have failed. We have learned a few things along the way, that we think relate directly to the success or failure of digital government projects. These are not scientific conclusions, they’re personal impressions based on what we’ve seen and experienced.   

1. Information first, services afterwards

A basic function of digital government is the provision of actionable information concerning public services, by they online or offline (e.g. opening hours, documents required for services, and so on). Even more so in developing countries, where most public services are in-person, paper-based, and often involve multiple steps. Yet, fueled by international rankings and benchmarks, governments are often eager to skip stages in their digital journey. This leads them to attempt, and often fail, to provide transactional digital services, before they can even learn  how to offer basic information about these services. The first step in effective transformation should be offering information to users in a simple and accessible manner. Done well, that forms a good foundation for the next step: delivering digital services.  

2. Prioritise the things that will make the biggest difference

Remember that public service delivery follows a power law distribution: a small number of services account for the vast majority of transactions with government. Which these services are will vary according to country, level of government, and models of public service delivery. When the time comes to decide where to start, don’t rely on cookie-cutter lists of services to be digitized. Instead, find out which ones are the most used, and will have the greatest impact. Start with the ones that can be delivered faster, and that are most likely to make users’ lives easier. 

3. Don’t digitise the mess

The fact that a process exists doesn’t mean it’s a good process. Transformation is an opportunity to radically rethink how things work. We’ve seen examples including, for instance, requiring multiple copies of a single document, or imposing more procedures on women than men to open a business. When there is inefficiency in a service, map the bottlenecks and think about how to streamline the process. Don’t just digitise the bottlenecks, they will keep on being an expensive problem. Resist the temptation to digitise things that should not exist in the first place. …(More)”.