Book by Carissa Carter: “Maps aren’t just geographic, they are also infographic and include all types of frameworks and diagrams. Any figure that sorts data visually and presents it spatially is a map. Maps are ways of organizing information and figuring out what’s important. Even stories can be mapped! The Secret Language of Maps provides a simple framework to deconstruct existing maps and then shows you how to create your own.
An embedded mystery story about a woman who investigates the disappearance of an old high school friend illustrates how to use different maps to make sense of all types of information. Colorful illustrations bring the story to life and demonstrate how the fictional character’s collection of data, properly organized and “mapped,” leads her to solve the mystery of her friend’s disappearance.
You’ll learn how to gather data, organize it, and present it to an audience. You’ll also learn how to view the many maps that swirl around our daily lives with a critical eye, aware of the forces that are in play for every creator…(More)”.
How Three False Starts Stifle Open Social Science
Article by Patrick Dunleavy: “Open social science is new, and like any beginner is still finding its way. However, to a large extent we are still operating in the shadow of open science (OS) in the Science, technology, engineering, mathematics, and medicine, or STEMM, disciplines. Nearly a decade ago an influential Royal Society report argued:
‘Open science is often effective in stimulating scientific discovery, [and] it may also help to deter, detect and stamp out bad science. Openness facilitates a systemic integrity that is conducive to early identification of error, malpractice and fraud, and therefore deters them. But this kind of transparency only works when openness meets standards of intelligibility and assessability – where there is intelligent openness’.
More recently, the Turing Way project defined open science far more broadly as a range of measures encouraging reproducibility, replication, robustness, and the generalisability of research. Alongside CIVICA researchers we have put forward an agenda for progressing open social science in line with these ambitions. Yet for open social science to take root it must develop an ‘intelligent’ concept of openness, one that is adapted to the wide range of concerns that our discipline group addresses, and is appropriate for the sharply varying conditions in which social research must be carried out.
This task has been made more difficult by a number of premature and partial efforts to ‘graft’ an ‘open science’ concept from STEMM disciplines onto the social sciences. Three false starts have already been made and have created misconceptions about open social science. Below, I want to show how each of the strategies may actually work to obstruct the wider development of open social science.
Bricolage – Reading across directly from STEMM
This approach sees open social science as just about picking up (not quite at random) the best-known or most discussed individual components of open science in STEMM disciplines – focusing on specific things like open access publishing, the FAIR principles for data management, replication studies, or the pre-registration of hypotheses…(More)”.
Efficient and stable data-sharing in a public transit oligopoly as a coopetitive game
Paper by Qi Liu and Joseph Y.J. Chow: “In this study, various forms of data sharing are axiomatized. A new way of studying coopetition, especially data-sharing coopetition, is proposed. The problem of the Bayesian game with signal dependence on actions is observed; and a method to handle such dependence is proposed. We focus on fixed-route transit service markets. A discrete model is first presented to analyze the data-sharing coopetition of an oligopolistic transit market when an externality effect exists. Given a fixed data sharing structure, a Bayesian game is used to capture the competition under uncertainty while a coalition formation model is used to determine the stable data-sharing decisions. A new method of composite coalition is proposed to study efficient markets. An alternative continuous model is proposed to handle large networks using simulation. We apply these models to various types of networks. Test results show that perfect information may lead to perfect selfishness. Sharing more data does not necessarily improve transit service for all groups, at least if transit operators remain non-cooperative. Service complementarity does not necessarily guarantee a grand data-sharing coalition. These results can provide insights on policy-making, like whether city authorities should enforce compulsory data-sharing along with cooperation between operators or setup a voluntary data-sharing platform…(More)”.
Responsible Data for Children Goes Polyglot: New Translations of Principles & Resources Available
Responsible Data for Children Blog: “In 2018, UNICEF and The GovLab launched the Responsible Data for Children (RD4C) initiative with the aim of supporting organisations and practitioners in ensuring that the interest of children is put at the centre of any work involving data for and about them.
Since its inception, the RD4C initiative has aimed to be field-oriented, driven by the needs of both children and practitioners across sectors and contexts. It has done so by ensuring that actors from the data responsibility sphere are informed and engaged on the RD4C work.
We want them to know what responsible data for and about children entails, why it is important, and how they can realize it in their own work.
In this spirit, the RD4C initiative has started translating its resources into different languages. We would like anyone willing to enhance their responsible data handling practices for and about children to be equipped with resources they can understand. As a global effort, we want to guarantee anyone willing to share their expertise and contribute be given the opportunity to do it.
Importantly, we would like children around the world—including the most marginalised and vulnerable groups—to be aware of what they can expect from organisations handling data for and about them and to have the means to demand and enforce their rights.
Last month, we released the RD4C Video, which is now available in Arabic, French and Spanish. Soon, the rest of the RD4C resources, such as our principles, tools and case studies will be translated as well.”
The Privacy Elasticity of Behavior: Conceptualization and Application
Paper by Inbal Dekel, Rachel Cummings, Ori Heffetz & Katrina Ligett: “We propose and initiate the study of privacy elasticity—the responsiveness of economic variables to small changes in the level of privacy given to participants in an economic system. Individuals rarely experience either full privacy or a complete lack of privacy; we propose to use differential privacy—a computer-science theory increasingly adopted by industry and government—as a standardized means of quantifying continuous privacy changes. The resulting privacy measure implies a privacy-elasticity notion that is portable and comparable across contexts. We demonstrate the feasibility of this approach by estimating the privacy elasticity of public-good contributions in a lab experiment…(More)”.
Responsible by Design – Principles for the ethical use of behavioural science in government
OECD Report: “The use of behavioural insights (BI) in public policy has grown over the last decade, with the largest increase of new behavioural teams emerging in the last five years. More and more governments are turning to behavioural science – a multidisciplinary approach to policy making encompassing lessons from psychology, cognitive science, neuroscience, anthropology, economics and more. There are a wide variety of frameworks and resources currently available, such as the OECD BASIC framework, designed with the purpose of helping BI practitioners and government officials infusing behavioural science throughout the policy cycle.
Despite the availability of such frameworks, there are less resources available with the primary purpose of safeguarding the responsible use of behavioural science in government. Oftentimes, teams are left to establish their own ethical standards and practices, which has resulted in an uncoordinated mosaic of procedures guiding the international community interested in upholding ethical behavioural practices. Until now, few attempts have been made to standardize ethical principles for behavioural science in public policy, and to concisely gather and present international best practices.
In light of this, we developed the first-of-its-kind Good Practice Principles for the Ethical Use of Behavioural Science in Public Policy to advance the responsible use of BI in government…(More)”.
How Does the Public Sector Identify Problems It Tries to Solve with AI?
Article by Maia Levy Daniel: “A correct analysis of the implementation of AI in a particular field or process needs to start by identifying if there actually is a problem to be solved. For instance, in the case of job matching, the problem would be related to the levels of unemployment in the country, and presumably addressing imbalances in specific fields. Then, would AI be the best way to address this specific problem? Are there any alternatives? Is there any evidence that shows that AI would be a better tool? Building AI systems is expensive and the funds being used by the public sector come from taxpayers. Are there any alternatives that could be less expensive?
Moreover, governments must understand from the outset that these systems could involve potential risks for civil and human rights. Thus, it should be justified in detail why the government might be choosing a more expensive or riskier option. A potential guide to follow is the one developed by the UK’s Office for Artificial Intelligence on how to use AI in the public sector. This guide includes a section specifically devoted to how to assess whether AI is the right solution to a problem.
AI is such a buzzword that it has become appealing for governments to use as a solution to any public problem, without even starting to look for available alternatives. Although automation could accelerate decision-making processes, speed should not be prioritized over quality or over human rights protection. As Daniel Susser argues in his recent paper, the speed at which automated decisions are reached has normative implications. By incorporating digital technologies in decision-making processes, temporal norms and values that govern them are impacted, disrupting prior norms, re-calibrating balanced trade-offs, or displacing automation’s costs. As Susser suggests, speed is not necessarily bad; however, “using computational tools to speed up (or slow down) certain decisions is not a ‘neutral’ adjustment without further explanations.”
So, conducting a thorough diagnosis including the identification of the specific problem to address and the best way to address it is key to protecting citizens’ rights. And this is why transparency must be mandatory. As citizens, we have a right to know how these processes are being conceived and designed, the reasons governments choose to implement technologies, as well as the risks involved.
In addition, maybe a good way to ultimately approach the systemic problem and change the structure of incentives is to stop using the pretentious terms “artificial intelligence”, “AI”, and “machine learning”, as Emily Tucker, the Executive Director of the Center on Privacy & Technology at Georgetown Law Center announced the Center would do. As Tucker explained, these terms are confusing for the average person, and the way they are typically employed makes us think it’s a machine rather than human beings making the decisions. By removing marketing terms from the equation and giving more visibility to the humans involved, these technologies may not ultimately seem so exotic…(More)”.
Moral Expansiveness Around the World: The Role of Societal Factors Across 36 Countries
Paper by Kelly Kirkland et al: “What are the things that we think matter morally, and how do societal factors influence this? To date, research has explored several individual-level and historical factors that influence the size of our ‘moral circles.’ There has, however, been less attention focused on which societal factors play a role. We present the first multi-national exploration of moral expansiveness—that is, the size of people’s moral circles across countries. We found low generalized trust, greater perceptions of a breakdown in the social fabric of society, and greater perceived economic inequality were associated with smaller moral circles. Generalized trust also helped explain the effects of perceived inequality on lower levels of moral inclusiveness. Other inequality indicators (i.e., Gini coefficients) were, however, unrelated to moral expansiveness. These findings suggest that societal factors, especially those associated with generalized trust, may influence the size of our moral circles…(More)”.
Kids Included: Enabling meaningful child participation within companies in a digital era
Report by KidsKnowBest and The LEGO Group: “As the impact of digital technology on children’s lives continues to grow, there are mounting calls for businesses that engage with children to deliver meaningful child participation throughout the design and development of their operations. Engaging children in how you take decisions and in how you design your digital products and services can, if done responsibly, create substantial value for both businesses and children. However, it also presents a broad number of challenges that businesses will need to address.
This report is a practical tool intended for businesses that are embarking on a journey towards meaningful child participation and encountering the challenges that come with it. It brings together expert voices from across sectors, including those of children and young people, to reflect on the following questions:
- What is meaningful child participation?
- Why is it important for children and businesses in relation to the digital environment?
- What are the key challenges to achieving this?
- How can businesses overcome these challenges?
While the report’s contributors passionately believe in the importance of meaningful child participation, they also recognise that nobody has all the answers. As such, this report is not intended to be referenced as an exhaustive resource, and is intended to be used together with the many other valuable resources for businesses.
However, we do hope it will inspire and enable businesses to move towards a future where children’s beliefs and perspectives are central to the design and development of the digital world. Children are asking to be heard. It’s time for businesses to sit up, listen, and learn…(More)”.
An anthology of warm data
Intro to anthology by Nora Bateson: “…The difficulty is that the studied living system is rarely put back into its multi contextual life-ing where it is in constant change. What would information look like that could change and shift in the field? The vitality of any living system is in the relationships between the parts. The relational vitality is constantly changing.
Warm Data is information that is alive within the transcontextual relating of a living system.
We may find it convenient to ignore this world of slippery, shifty information and choose instead that information that can be handled and pinned down. Still, the swirly stuff is underlying absolutely everything that is known as “action,” “decision,” or “learning.” Warm Data is necessary if for no other reason than a reminder that whatever information is currently available in a living process, “it is not just that and nothing more.”There are more contexts constantly shifting all the time. Think of a family, how it stays the same, and how it changes over time—or a city, pond, or a religion. To maintain any coherence, those systems must continually reshape and do so in relation to one another…(More)”.