Tackling Climate Change with Machine Learning


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)”.

Social Media and Polarization


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)”.

Exploring the Relationship between Trust in Government and Citizen Participation


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)”.

For Crowdsourcing to Work, Everyone Needs an Equal Voice


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)”.

Trust and Mistrust in Americans’ Views of Scientific Experts


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)”.

What can the labor flow of 500 million people on LinkedIn tell us about the structure of the global economy?


Paper by Jaehyuk Park et al: “…One of the most popular concepts for policy makers and business economists to understand the structure of the global economy is “cluster”, the geographical agglomeration of interconnected firms such as Silicon ValleyWall Street, and Hollywood. By studying those well-known clusters, we become to understand the advantage of participating in a geo-industrial cluster for firms and how it is related to the economic growth of a region. 

However, the existing definition of geo-industrial cluster is not systematic enough to reveal the whole picture of the global economy. Often, after defining as a group of firms in a certain area, the geo-industrial clusters are considered as independent to each other. As we should consider the interaction between accounting team and marketing team to understand the organizational structure of a firm, the relationships among those geo-industrial clusters are the essential part of the whole picture….

In this new study, my colleagues and I at Indiana University — with support from LinkedIn — have finally overcome these limitations by defining geo-industrial clusters through labor flow and constructing a global labor flow network from LinkedIn’s individual-level job history dataset. Our access to this data was made possible by our selection as one of 11 teams selected to participate in the LinkedIn Economic Graph Challenge.

The transitioning of workers between jobs and firms — also known as labor flow — is considered central in driving firms towards geo-industrial clusters due to knowledge spillover and labor market pooling. In response, we mapped the cluster structure of the world economy based on labor mobility between firms during the last 25 years, constructing a “labor flow network.” 

To do this, we leverage LinkedIn’s data on professional demographics and employment histories from more than 500 million people between 1990 and 2015. The network, which captures approximately 130 million job transitions between more than 4 million firms, is the first-ever flow network of global labor.

The resulting “map” allows us to:

  • identify geo-industrial clusters systematically and organically using network community detection
  • verify the importance of region and industry in labor mobility
  • compare the relative importance between the two constraints in different hierarchical levels, and
  • reveal the practical advantage of the geo-industrial cluster as a unit of future economic analyses.
  • show a better picture of what industry in what region leads the economic growth of the industry or the region, at the same time
  • find out emerging and declining skills based on the representativeness of them in growing and declining geo-industrial clusters…(More)”.

Blockchain and Democracy


Literature Review by Jörn Erbguth: “Democratic states are entities where issues are decided by a large group – the people. There is a democratic process that builds upon elections, a legislative procedure, judicial review and separation of powers by checks and balances. Blockchains rely on decentralization, meaning they rely on a large group of participants as well. Blockchains are therefore confronted with similar problems. Even further, blockchains try to avoid central coordinating authorities.

Consensus methods ensure that the systems align with the majority of their participants. Above the layer of the consensus method, blockchain governance coordinates decisions about software updates, bugfixes and possibly other interventions. What are the strengths and weaknesses of this blockchain governance?
Should we use blockchain to secure e-voting? Blockchain governance has two central aspects. First, it is decentralized governance based on a large group of people, which resembles democratic decision-making. Second, it is algorithmic decision-making and limits unwanted human intervention

Cornerstones
Blockchain and democracy can be split into three areas:

First, the use of democratic principles in order to make blockchain work. This ranges from the basic concensus algorithm to the (self-)governance of a blockchain.

Second, blockchain is seen as providing a reliable tool for democracy. This ranges from the use of blockchain for electronic voting to the use in administration.

Third, to study possible impacts of blockchain technology on a democratic society. This focusses on regulatory and legal aspects as well as ethical aspects….(More)”

Political innovation, digitalisation and public participation in party politics


Paper by Lisa Schmidthuber; Dennis Hilgers and Maximilian Rapp: “Citizen engagement is seen as a way to address a range of societal challenges, fiscal constraints, as well as wicked problems, and increasing public participation in political decisions could help to address low levels of trust in politicians and decreasing satisfaction with political parties. This paper examines the perceived impacts of an experiment by the Austrian People’s Party which, in response to reaching a historic low in the polls, opened up its manifesto process to public participation via digital technology. Analysis of survey data from participants found that self-efficacy is positively associated with participation intensity but negatively related to satisfaction. In contrast, collective efficacy is related to positive perceptions of public participation in party politics but does not influence levels of individual participation. Future research is needed to explore the outcomes of political innovations that use digital technologies to enable public participation on voting behaviour, party membership and attitudes to representative democracy….(More)”.

The Nollywood Nudge: An Entertaining Approach to Saving


Paper by Aidan Coville, Vincenzo Di Maro, Felipe Dunsch and Siegfried Zottel: “This paper investigates the immediate and medium-term behavioral response to an emotional trigger designed to affect biases in intertemporal financial decisions. The emotional trigger is provided by a narrative portraying the catastrophic consequences of poor financial choices. Even when people are fully aware of the most appropriate action to take, cognitive biases may prevent this knowledge from translating into action.

The paper contributes to the literature by directly testing the importance of linking emotional stimulus to financial messages, to influence borrowing and saving decisions, and identifying the interaction between emotional stimulus and the opportunity to act on this stimulus. The study randomly assigned individuals to a featured production — a Nollywood (the Nigerian Hollywood) movie — on the financial consequences of poor borrowing and saving behavior. This treatment is interacted with the option of opening a savings account at the screening of the movie. At the exit of the screening, individuals in the financial education movie treatment are more likely to open a savings account than individuals in the placebo movie treatment. However, the effects dissipate quickly. When savings and borrowing behavior is measured four months later, the study finds no differences between treatments. The paper concludes that emotional triggers delivered in the context of a one-time feature film might not be enough to secure sustained changes in behavior….(More)”.

Strategies and limitations in app usage and human mobility


Paper by Marco De Nadai, Angelo Cardoso, Antonio Lima, Bruno Lepri, and Nuria Oliver: “Cognition has been found to constrain several aspects of human behaviour, such as the number of friends and the number of favourite places a person keeps stable over time. this limitation has been empirically defined in the physical and social spaces. But do people exhibit similar constraints in the digital space? We address this question through the analysis of pseudonymised mobility and mobile application (app) usage data of 400,000 individuals in a European country for six months. Despite the enormous heterogeneity of apps usage, we find that individuals exhibit a conserved capacity that limits the number of applications they regularly use. Moreover, we find that this capacity steadily decreases with age, as does the capacity in the physical space but with more complex dynamics. Even though people might have the same capacity, applications get added and removed over time.

In this respect, we identify two profiles of individuals: app keepers and explorers, which differ in their stable (keepers) vs exploratory (explorers) behaviour regarding their use of mobile applications. Finally, we show that the capacity of applications predicts mobility capacity and vice-versa. By contrast, the behaviour of keepers and explorers may considerably vary across the two domains. Our empirical findings provide an intriguing picture linking human behaviour in the physical and digital worlds which bridges research studies from Computer Science, Social Physics and Computational Social Sciences…(More)”.