Paper by David Rolnick et al: “Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change….(More)”.
Book by Barnali Choudhury and Martin Petrin: “In a world where the grocery store may be more powerful than the government and corporations are the governors rather than the governed, the notion of corporations being only private actors is slowly evaporating. Gone is the view that corporations can focus exclusively on maximizing shareholder wealth. Instead, the idea that corporations owe duties to the public is capturing the attention of not only citizens and legislators, but corporations themselves. This book explores the deepening connections between corporations and the public. It explores timely – and often controversial – public issues with which corporations must grapple including the corporate purpose, civil and criminal liability, taxation, human rights, the environment and corruption. Offering readers an encompassing, balanced, and systematic understanding of the most pertinent duties corporations should bear, how they work, whether they are justified, and how they should be designed in the future, this book clarifies corporations’ roles vis-à-vis the public….(More)”.
Paper by Arthur Campbell, C. Matthew Leister and Yves Zenou: “Because of its impacts on democracy, there is an important debate on whether the recent trends towards greater use of social media increases or decreases (political) polarization. One challenge for understanding this issue is how social media affects the equilibrium prevalence of different types of media content. We address this issue by developing a model of a social media network where there are two types of news content: mass-market (mainstream news) and niche-market (biased or more “extreme” news) and two different types of individuals who have a preference for recommending one or other type of content. We find that social media will amplify the prevalence of mass-market content and may result in it being the only type of content consumed. Further, we find that greater connectivity and homophily in the social media network will concurrently increase the prevalence of the niche market content and polarization. We then study an extension where there are two lobbying agents that can and wish to influence the prevalence of each type of content. We find that the lobbying agent in favor of the niche content will invest more in lobbying activities. We also show that lobbying activity will tend to increase polarization, and that this effect is greatest in settings where polarization would be small absent of lobbying activity. Finally, we allow individuals to choose the degree of homophily amongst their connections and demonstrate that niche-market individuals exhibit greater homophily than the mass-market ones, and contribute more to polarization….(More)”.
Paper by Yunsoo Lee and Hindy Lauer Schachter: “Theories of deliberative and stealth democracy offer different predictions on the relationship between trust in government and citizen participation. To help resolve the contradictory predictions, this study used the World Values Survey to examine the influence of trust in government on citizen participation. Regression analyses yielded mixed results. As deliberative democracy theory predicts, the findings showed that people who trust governmental institutions are more likely to vote and sign a petition. However, the data provided limited support for stealth democracy in that trust in government negatively affects the frequency of attending a demonstration….(More)”.
Joshua Becker and Edward “Ned” Smith in Havard Business Review: “How useful is the wisdom of crowds? For years, it has been recognized as producing incredibly accurate predictions by aggregating the opinions of many people, allowing even amateur forecasters to beat the experts. The belief is that when large numbers of people make forecasts independently, their errors are uncorrelated and ultimately cancel each other out, which leads to more accurate final answers.
However, researchers and pundits have argued that the wisdom of crowds is extremely fragile, especially in two specific circumstances: when people are influenced by the opinions of others (because they lose their independence) and when opinions are distorted by cognitive biases (for example, strong political views held by a group).
In new research, we and our colleagues zeroed in on these assumptions and found that the wisdom of crowds is more robust than previously thought — it can even withstand the groupthink of similar-minded people. But there’s one important caveat: In order for the wisdom of crowds to retain its accuracy for making predictions, every member of the group must be given an equal voice, without any one person dominating. As we discovered, the pattern of social influence within groups — that is, who talks to whom and when — is the key determinant of the crowd’s accuracy in making predictions….(More)”.
Handbook by Douwe Korff and Marie Georges: “This Handbook was prepared for and is used in the EU-funded “T4DATA” training‐of-trainers programme. Part I explains the history and development of European data protection law and provides an overview of European data protection instruments including the Council of Europe Convention and its “Modernisation” and the various EU data protection instruments relating to Justice and Home Affairs, the CFSP and the EU institutions, before focusing on the GDPR in Part II. The final part (Part III) consists of detailed practical advice on the various tasks of the Data Protection Officer now institutionalised by the GDPR. Although produced for the T4DATA programme that focusses on DPOs in the public sector, it is hoped that the Handbook will be useful also to anyone else interested in the application of the GDPR, including DPOs in the private sector….(More)”.
Report by the Pew Research Center: “In an era when science and politics often appear to collide, public confidence in scientists is on the upswing, and six-inten Americans say scientists should play an active role in policy debates about scientific
issues, according to a new Pew Research Center survey.
The survey finds public confidence in scientists on par with confidence in the military. It also exceeds the levels of public confidence in other groups and institutions, including the media, business leaders and elected officials.
At the same time, Americans are divided along party lines in terms of how they view the value and objectivity of scientists and their ability to act in the public interest. And, while political divides do not carry over to views of all scientists and scientific issues, there are particularly sizable gaps between Democrats and Republicans when it comes to trust in scientists whose work is related to the environment.
Higher levels of familiarity with the work of scientists are associated with more positive and more trusting views of scientists regarding their competence, credibility and commitment to the public, the survey shows….(More)”.
Centre for Humanitarian Data: “Survey and needs assessment data, or what is known as ‘microdata’, is essential for providing adequate response to crisis-affected people. However, collecting this information does present risks. Even as great effort is taken to remove unique identifiers such as names and phone numbers from microdata so no individual persons or communities are exposed, combining key variables such as location or ethnicity can still allow for re-identification of individual respondents. Statistical Disclosure Control (SDC) is one method for reducing this risk.
The Centre has developed a Guidance Note on Statistical Disclosure Control that outlines the steps involved in the SDC process, potential applications for its use, case studies and key actions for humanitarian data practitioners to take when managing sensitive microdata. Along with an overview of what SDC is and what tools are available, the Guidance Note outlines how the Centre is using this process to mitigate risk for datasets shared on HDX. …(More)”.
Book edited by Sébastien Lechevalier: ” The major purpose of this book is to clarify the importance of non-technological factors in innovation to cope with contemporary complex societal issues while critically reconsidering the relations between science, technology, innovation (STI), and society. For a few decades now, innovation—mainly derived from technological advancement—has been considered a driving force of economic and societal development and prosperity.
With that in mind, the following questions are dealt with in this book: What are the non-technological sources of innovation? What can the progress of STI bring to humankind? What roles will society be expected to play in the new model of innovation? The authors argue that the majority of so-called technological innovations are actually socio-technical innovations, requiring huge resources for financing activities, adapting regulations, designing adequate policy frames, and shaping new uses and new users while having the appropriate interaction with society.
This book gathers multi- and trans-disciplinary approaches in innovation that go beyond technology and take into account the inter-relations with social and human phenomena. Illustrated by carefully chosen examples and based on broad and well-informed analyses, it is highly recommended to readers who seek an in-depth and up-to-date integrated overview of innovation in its non-technological dimensions….(More)”.
Matthew Hutson at Science: “Artificial intelligence (AI) used to be the specialized domain of data scientists and computer programmers. But companies such as Wolfram Research, which makes Mathematica, are trying to democratize the field, so scientists without AI skills can harness the technology for recognizing patterns in big data. In some cases, they don’t need to code at all. Insights are just a drag-and-drop away. One of the latest systems is software called Ludwig, first made open-source by Uber in February and updated last week. Uber used Ludwig for projects such as predicting food delivery times before releasing it publicly. At least a dozen startups are using it, plus big companies such as Apple, IBM, and Nvidia. And scientists: Tobias Boothe, a biologist at the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden, Germany, uses it to visually distinguish thousands of species of flatworms, a difficult task even for experts. To train Ludwig, he just uploads images and labels….(More)”.