Report by the Alliance for Useful Evidence: “This inventory is about how you can use experiments to solve public and social problems. It aims to provide a framework for thinking about the choices available to a government, funder or delivery organisation that wants to experiment more effectively. We aim to simplify jargon and do some myth-busting on common misperceptions.
There are other guides on specific areas of experimentation – such as on randomised controlled trials – including many specialist technical textbooks. This is not a technical manual or guide about how to run experiments. Rather, this inventory is useful for anybody wanting a jargon-free overview of the types and uses of experiments. It is unique in its breadth – covering the whole landscape of social and policy experimentation, including prototyping, rapid cycle testing, quasi-experimental designs, and a range of different types of randomised trials. Experimentation can be a confusing landscape – and there are competing definitions about what constitutes an experiment among researchers, innovators and evaluation practitioners. We take a pragmatic approach, including different designs that are useful for public problem-solving, under our experimental umbrella. We cover ways of experimenting that are both qualitative and quantitative, and highlight what we can learn from different approaches….(More)”.
Report by Alison J. Head, Ph.D., Barbara Fister, Margy MacMillan: “…Three sets of questions guided this report’s inquiry:
- What is the nature of our current information environment, and how has it influenced how we access, evaluate, and create knowledge today? What do findings from a decade of PIL research tell us about the information skills and habits students will need for the future?
- How aware are current students of the algorithms that filter and shape the news and information they encounter daily? What
concerns do they have about how automated decision-making systems may influence us, divide us, and deepen inequalities?
- What must higher education do to prepare students to understand the new media landscape so they will be able to participate in sharing and creating information responsibly in a changing and challenged world?
To investigate these questions, we draw on qualitative data that PIL researchers collected from student focus groups and faculty interviews during fall 2019 at eight U.S. colleges and universities. Findings from a sample of 103 students and 37 professors reveal levels of awareness and concerns about the age of algorithms on college campuses. They are presented as research takeaways….(More)”.
Eye on Design: “How often do we think of data as missing? Data is everywhere—it’s used to decide what products to stock in stores, to determine which diseases we’re most at risk for, to train AI models to think more like humans. It’s collected by our governments and used to make civic decisions. It’s mined by major tech companies to tailor our online experiences and sell to advertisers. As our data becomes an increasingly valuable commodity—usually profiting others, sometimes at our own expense—to not be “seen” or counted might seem like a good thing. But when data is used at such an enormous scale, gaps in the data take on an outsized importance, leading to erasure, reinforcing bias, and, ultimately, creating a distorted view of humanity. As Tea Uglow, director of Google’s Creative Lab, has said in reference to the exclusion of queer and transgender communities, “If the data does not exist, you do not exist.”
“In spaces that are oversaturated with data, there are blank spots where there’s nothing collected at all.”
This is something that artists and designers working in the digital realm understand better than most, and a growing number of them are working on projects that bring in the nuance, ethical outlook, and humanist approach necessary to take on the problem of data bias. This group includes artists like Onuoha that have the vision to seek out and highlight these absences (and offer a blueprint for others), as well as those like artist and software engineer Omayeli Arenyeka, who are working on projects that collect necessary data. It also includes artist and researcher Caroline Sinders and the collective Feminist Internet, who are working on building AI models, chatbots, and systems that take into account data bias and exclusion in every step of their processes. Others are academics like Catherine D’Ignazio and Lauren Klein, whose book Data Feminism considers how a feminist approach to data science would curb widespread bias. Still others are activists, like María Salguero, who saw there was a lack of comprehensive data on gender-based killings in Mexico and decided to collect it herself….(More)”.
Edelman: “The 2020 Edelman Trust Barometer reveals that despite a strong global economy and near full employment, none of the four societal institutions that the study measures—government, business, NGOs and media—is trusted. The cause of this paradox can be found in people’s fears about the future and their role in it, which are a wake-up call for our institutions to embrace a new way of effectively building trust: balancing competence with ethical behavior…
Since Edelman began measuring trust 20 years ago, it has been spurred by economic growth. This continues in Asia and the Middle East, but not in developed markets, where income inequality is now the more important factor. A majority of respondents in every developed market do not believe they will be better off in five years’ time, and more than half of respondents globally believe that capitalism in its current form is now doing more harm than good in the world. The result is a world of two different trust realities. The informed public—wealthier, more educated, and frequent consumers of news—remain far more trusting of every institution than the mass population. In a majority of markets, less than half of the mass population trust their institutions to do what is right. There are now a record eight markets showing all-time-high gaps between the two audiences—an alarming trust inequality…
Distrust is being driven by a growing sense of inequity and unfairness in the system. The perception is that institutions increasingly serve the interests of the few over everyone. Government, more than any institution, is seen as least fair; 57 percent of the general population say government serves the interest of only the few, while 30 percent say government serves the interests of everyone….
Against the backdrop of growing cynicism around capitalism and the fairness of our current economic systems are deep-seated fears about the future. Specifically, 83 percent of employees say they fear losing their job, attributing it to the gig economy, a looming recession, a lack of skills, cheaper foreign competitors, immigrants who will work for less, automation, or jobs being moved to other countries….(More)”.
Report by the World Economic Forum: “The Fourth Industrial Revolution (4IR) is still in its early years yet it is already changing the way we work, live and interact. As 4IR technologies become faster, smarter, and more widely applied, the pace of transformation will only accelerate.
In parallel, we face global challenges of increasing magnitude and immediacy. The United Nation’s 17 Global Goals give a blueprint for what we globally and collectively must do if we are to end extreme poverty, protect our natural environment, revert climate change and create a more sustainable, equal and prosperous future for all.
Despite a rapid rise of 4IR technologies being applied across many aspects of industry and commerce, the potential of these technologies to accelerate progress to the Global Goals is not being realised. Today’s technological revolution is a time of enormous promise to accelerate progress on the Global Goals, both broadening and deepening current action.
But unlocking this potential requires a change in priorities and significant challenges to be overcome. This presents us with a dilemma of how to drive systems-level change in priorities, and to overcome significant challenges to ensure that it has an impact over the next 10 years on the global goals, and also on these challenges in the long term.
In this report, developed in collaboration with PwC, we showcase the significant opportunity to harness new technologies for the Global Goals. Through analysis of over 300 technology applications, the report explores; 1) the extent to which this opportunity is being realised, 2) the barriers to scaling these applications, and 3) the enabling framework for unlocking this opportunity….(More)”.
Report by Accenture/NASCIO: “…exploring the future role of the state CIO and how the state CIO will drive innovation.
The research included interviews and a survey of state CIOs to understand the role of state CIOs in promoting innovation in government.
- The study explored how state IT organizations build the capacity to innovate and which best practices help in doing so.
- We also examined how state CIOs embrace new and emerging technologies to create the best government outcomes.
- Our report illuminates compelling opportunities, persistent obstacles, strategies for accelerating innovation and inspiring real-world case studies.
- The report presents a set of practical recommendations for driving innovation…(More)”.
Essay by Thomas Carothers: “Adverse political developments in both established and newer democracies, especially the abdication by the United States of its traditional leadership role, have cast international democracy support into doubt. Yet international action on behalf of democracy globally remains necessary and possible. Moreover, some important elements of continuity remain, including overall Western spending on democracy assistance. Democracy support must adapt to its changed circumstances by doing more to take new geopolitical realities into account; effacing the boundary between support for democracy in new and in established democracies; strengthening the economic dimension of democracy assistance; and moving technological issues to the forefront…(More)”.
Essay by Bapu Vaitla, Stefaan Verhulst, Linus Bengtsson, Marta C. González, Rebecca Furst-Nichols & Emily Courey Pryor in Special Issue on Big Data of Nature Medicine: “Women and girls are legally and socially marginalized in many countries. As a result, policymakers neglect key gendered issues such as informal labor markets, domestic violence, and mental health1. The scientific community can help push such topics onto policy agendas, but science itself is riven by inequality: women are underrepresented in academia, and gendered research is rarely a priority of funding agencies.
However, the critical importance of better gender data for societal well-being is clear. Mental health is a particularly striking example. Estimates from the Global Burden of Disease database suggest that depressive and anxiety disorders are the second leading cause of morbidity among females between 10 and 63 years of age2. But little is known about the risk factors that contribute to mental illness among specific groups of women and girls, the challenges of seeking care for depression and anxiety, or the long-term consequences of undiagnosed and untreated illness. A lack of data similarly impedes policy action on domestic and intimate-partner violence, early marriage, and sexual harassment, among many other topics.
‘Big data’ can help fill that gap. The massive amounts of information passively generated by electronic devices represent a rich portrait of human life, capturing where people go, the decisions they make, and how they respond to changes in their socio-economic environment. For example, mobile-phone data allow better understanding of health-seeking behavior as well as the dynamics of infectious-disease transmission3. Social-media platforms generate the world’s largest database of thoughts and emotions—information that, if leveraged responsibly, can be used to infer gendered patterns of mental health4. Remote sensors, especially satellites, can be used in conjunction with traditional data sources to increase the spatial and temporal granularity of data on women’s economic activity and health status5.
But the risk of gendered algorithmic bias is a serious obstacle to the responsible use of big data. Data are not value free; they reproduce the conscious and unconscious attitudes held by researchers, programmers, and institutions. Consider, for example, the training datasets on which the interpretation of big data depends. Training datasets establish the association between two or more directly observed phenomena of interest—for example, the mental health of a platform user (typically collected through a diagnostic survey) and the semantic content of the user’s social-media posts. These associations are then used to develop algorithms that interpret big data streams. In the example here, the (directly unobserved) mental health of a large population of social-media users would be inferred from their observed posts….(More)”.
Idea by Helena Rong and Juncheng Yang: “We propose an interactive design engagement platform which facilitates a continuous conversation between developers, designers and end users from pre-design and planning phases all the way to post-occupancy, adopting a citizen-centric and inclusive-oriented approach which would stimulate trust-building and invite active participation from end users from different age, ethnicity, social and economic background to participate in the design and development process. We aim to explore how collective intelligence through citizen engagement could be enabled by data to allow new collectives to emerge, confronting design as an iterative process involving scalable cooperation of different actors. As a result, design is a collaborative and conscious practice not born out of a single mastermind of the architect. Rather, its agency is reinforced by a cooperative ideal involving institutions, enterprises and single individuals alike enabled by data science….(More)”
Report by Shelly Culbertson, James Dimarogonas, Katherine Costello, and Serafina Lanna: “In the past two decades, the global population of forcibly displaced people has more than doubled, from 34 million in 1997 to 71 million in 2018. Amid this growing crisis, refugees and the organizations that assist them have turned to technology as an important resource, and technology can and should play an important role in solving problems in humanitarian settings. In this report, the authors analyze technology uses, needs, and gaps, as well as opportunities for better using technology to help displaced people and improving the operations of responding agencies. The authors also examine inherent ethical, security, and privacy considerations; explore barriers to the successful deployment of technology; and outline some tools for building a more systematic approach to such deployment. The study approach included a literature review, semi-structured interviews with stakeholders, and focus groups with displaced people in Colombia, Greece, Jordan, and the United States. The authors provide several recommendations for more strategically using and developing technology in humanitarian settings….(More)”.