The End of Real Social Networks


Essay by Daron Acemoglu: “Social media platforms are not only creating echo chambers, propagating falsehoods, and facilitating the circulation of extremist ideas. Previous media innovations, dating back at least to the printing press, did that, too, but none of them shook the very foundations of human communication and social interaction.

CAMBRIDGE – Not only are billions of people around the world glued to their mobile phones, but the information they consume has changed dramatically – and not for the better. On dominant social-media platforms like Facebook, researchers have documented that falsehoods spread faster and more widely than similar content that includes accurate information. Though users are not demanding misinformation, the algorithms that determine what people see tend to favor sensational, inaccurate, and misleading content, because that is what generates “engagement” and thus advertising revenue.

As the internet activist Eli Pariser noted in 2011, Facebook also creates filter bubbles, whereby individuals are more likely to be presented with content that reinforces their own ideological leanings and confirms their own biases. And more recent research has demonstrated that this process has a major influence on the type of information users see.

Even leaving aside Facebook’s algorithmic choices, the broader social-media ecosystem allows people to find subcommunities that align with their interests. This is not necessarily a bad thing. If you are the only person in your community with an interest in ornithology, you no longer have to be alone, because you can now connect with ornithology enthusiasts from around the world. But, of course, the same applies to the lone extremist who can now use the same platforms to access or propagate hate speech and conspiracy theories.

No one disputes that social-media platforms have been a major conduit for hate speech, disinformation, and propaganda. Reddit and YouTube are breeding grounds for right-wing extremism. The Oath Keepers used Facebook, especially, to organize their role in the January 6, 2021, attack on the United States Capitol. Former US President Donald Trump’s anti-Muslim tweets were found to have fueled violence against minorities in the US.

True, some find such observations alarmist, noting that large players like Facebook and YouTube (which is owned by Google/Alphabet) do much more to police hate speech and misinformation than their smaller rivals do, especially now that better moderation practices have been developed. Moreover, other researchers have challenged the finding that falsehoods spread faster on Facebook and Twitter, at least when compared to other media.

Still others argue that even if the current social-media environment is treacherous, the problem is transitory. After all, novel communication tools have always been misused. Martin Luther used the printing press to promote not just Protestantism but also virulent anti-Semitism. Radio proved to be a powerful tool in the hands of demagogues like Father Charles Coughlin in the US and the Nazis in Germany. Both print and broadcast outlets remain full of misinformation to this day, but society has adjusted to these media and managed to contain their negative effects…(More)”.

Collection of Case Studies of Institutional Adoption of Citizen Science


About TIME4CS : “The first objective was to increase our knowledge about the actions leading to institutional changes in RPOs (which are necessary to promote CS in science and technology) through a complete and up-to-date picture based upon the identification, mapping, monitoring and analysis of ongoing CS practices. To accomplish this objective, we, the TIME4CS project team, have collected and analysed 37 case studies on the institutional adoption of Citizen Science and Open Science around the world, which this article addresses.

For an organisation to open up and accept data and information that was produced outside it, with a different framework for data collection and quality assurance, there are multiple challenges. These include existing practices and procedures, legal obligations, as well as resistance from within due to framing of such action as a threat. Research that was carried out with multiple international case studies (Haklay et al. 2014; GFDRR 2018), demonstrated the importance of different institutional and funding structures needed to enable such activities and the use of the resulting information…(More)”.

Another World Is Possible: How to Reignite Social and Political Imagination


Book by Geoff Mulgan: “As the world confronts the fast catastrophe of Covid and the slow calamity of climate change, we also face a third, less visible emergency: a crisis of imagination. We can easily picture ecological disaster or futures dominated by technology. But we struggle to imagine a world in which people thrive and where we improve our democracy, welfare, neighbourhoods or education. Many are resigned to fatalism—yet they desperately want transformational social change.

This book argues that, although the threats are real, we can use creative imagination to achieve a better future: visualising where we want to go and how to get there. Political and social thinker Geoff Mulgan offers lessons we can learn from the past, and methods we can use now to open up thinking about the future and spark action.

Drawing on social sciences, the arts, philosophy and history, Mulgan shows how we can recharge our collective imagination. From Socrates to Star Wars, he provides a roadmap for the future….(More)”.

Blue Spoons: Sparking Communication About Appropriate Technology Use


Paper by Arun G. Chandrasekhar, Esther Duflo, Michael Kremer, João F. Pugliese, Jonathan Robinson & Frank Schilbach: “An enduring puzzle regarding technology adoption in developing countries is that new technologies often diffuse slowly through the social network. Two of the key predictions of the canonical epidemiological model of technology diffusion are that forums to share information and higher returns to technology should both spur social transmission. We design a large-scale experiment to test these predictions among farmers in Western Kenya, and we fail to find support for either. However, in the same context, we introduce a technology that diffuses very fast: a simple kitchen spoon (painted in blue) to measure out how much fertilizer to use. We develop a model that explains both the failure of the standard approaches and the surprising success of this new technology. The core idea of the model is that not all information is reliable, and farmers are reluctant to develop a reputation of passing along false information. The model and data suggest that there is value in developing simple, transparent technologies to facilitate communication…(More)”.

Macroscopes


Exhibit by Places and Spaces: “The term “macroscope” may strike many as being strange or even daunting. But actually, the term becomes friendlier when placed within the context of more familiar “scopes.” For instance, most of us have stared through a microscope. By doing so, we were able to see tiny plant or animal cells floating around before our very eyes. Similarly, many of us have peered out through a telescope into the night sky. There, we were able to see lunar craters, cloud belts on Jupiter, or the phases of Mercury. What both of these scopes have in common is that they allow the viewer to see objects that could otherwise not be perceived by the naked eye, either because they are too small or too distant.

But what if we want to better understand the complex systems or networks within which we operate and which have a profound, if often unperceived, impact on our lives? This is where macroscopes become such useful tools. They allow us to go beyond our focus on the single organism, the single social or natural phenomenon, or the single development in technology. Instead, macroscopes allow us to gather vast amounts of data about many kinds of organisms, environments, and technologies. And from that data, we can analyze and comprehend the way these elements co-exist, compete, or cooperate.

With the macroscope, we are allowed to see the “big picture,” a goal imagined in 1979 by Joël de Rosnay in his groundbreaking book, The Macroscope: A New World Scientific System. For the author, the macroscope would be the “symbol of a new way of seeing and understanding.” It was to be a tool “not used to make things larger or smaller but to observe what is at once too great, too slow, and too complex for our eyes.”

With these needs and insights in mind, the second decade of the Places & Spaces exhibit will invite and showcase interactive visualizations—our own exemplars of de Rosnay’s macroscope—that demonstrate the impact of different data cleaning, analysis, and visualization algorithms. It is the exhibit’s hope that this view of the “behind the scenes” process of data visualization will increase the ability of viewers to gain meaningful insights from such visualizations and empower people from all backgrounds to use data more effectively and endeavor to create maps that address their own needs and interests…(More)”.

Spirals of Delusion: How AI Distorts Decision-Making and Makes Dictators More Dangerous


Essay by Henry Farrell, Abraham Newman, and Jeremy Wallace: “In policy circles, discussions about artificial intelligence invariably pit China against the United States in a race for technological supremacy. If the key resource is data, then China, with its billion-plus citizens and lax protections against state surveillance, seems destined to win. Kai-Fu Lee, a famous computer scientist, has claimed that data is the new oil, and China the new OPEC. If superior technology is what provides the edge, however, then the United States, with its world class university system and talented workforce, still has a chance to come out ahead. For either country, pundits assume that superiority in AI will lead naturally to broader economic and military superiority.

But thinking about AI in terms of a race for dominance misses the more fundamental ways in which AI is transforming global politics. AI will not transform the rivalry between powers so much as it will transform the rivals themselves. The United States is a democracy, whereas China is an authoritarian regime, and machine learning challenges each political system in its own way. The challenges to democracies such as the United States are all too visible. Machine learning may increase polarization—reengineering the online world to promote political division. It will certainly increase disinformation in the future, generating convincing fake speech at scale. The challenges to autocracies are more subtle but possibly more corrosive. Just as machine learning reflects and reinforces the divisions of democracy, it may confound autocracies, creating a false appearance of consensus and concealing underlying societal fissures until it is too late.

Early pioneers of AI, including the political scientist Herbert Simon, realized that AI technology has more in common with markets, bureaucracies, and political institutions than with simple engineering applications. Another pioneer of artificial intelligence, Norbert Wiener, described AI as a “cybernetic” system—one that can respond and adapt to feedback. Neither Simon nor Wiener anticipated how machine learning would dominate AI, but its evolution fits with their way of thinking. Facebook and Google use machine learning as the analytic engine of a self-correcting system, which continually updates its understanding of the data depending on whether its predictions succeed or fail. It is this loop between statistical analysis and feedback from the environment that has made machine learning such a formidable force…(More)”

A little good goes an unexpectedly long way: Underestimating the positive impact of kindness on recipients.


Paper by Kumar, A., & Epley, N. : “Performing random acts of kindness increases happiness in both givers and receivers, but we find that givers systematically undervalue their positive impact on recipients. In both field and laboratory settings (Experiments 1a through 2b), those performing an act of kindness reported how positive they expected recipients would feel and recipients reported how they actually felt. From giving away a cup of hot chocolate in a park to giving away a gift in the lab, those performing a random act of kindness consistently underestimated how positive their recipients would feel, thinking their act was of less value than recipients perceived it to be. Givers’ miscalibrated expectations are driven partly by an egocentric bias in evaluations of the act itself (Experiment 3). Whereas recipients’ positive reactions are enhanced by the warmth conveyed in a kind act, givers’ expectations are relatively insensitive to the warmth conveyed in their action. Underestimating the positive impact of a random act of kindness also leads givers to underestimate the behavioral consequences their prosociality will produce in recipients through indirect reciprocity (Experiment 4). We suggest that givers’ miscalibrated expectations matter because they can create a barrier to engaging in prosocial actions more often in everyday life (Experiments 5a and 5b), which may result in people missing out on opportunities to enhance both their own and others’ well-being…(More)”

A User’s Guide to the Periodic Table of Open Data


Guide by Stefaan Verhulst and Andrew Zahuranec: “Leveraging our research on the variables that determine Open Data’s Impact, The Open Data Policy Lab is pleased to announce the publication of a new report designed to assist organizations in implementing the elements of a successful data collaborative: A User’s Guide to The Periodic Table of Open Data.

The User’s Guide is a fillable document designed to empower data stewards and others seeking to improve data access. It can be used as a checklist and tool to weigh different elements based on their context and priorities. By completing the forms (offline/online), you will be able to take a more comprehensive and strategic view of what resources and interventions may be required.

Download and fill out the User’s Guide to operationalize the elements in your data initiative

In conjunction with the release of our User’s Guide, the Open Data Policy Lab is pleased to present a completely reworked version of our Periodic Table of Open Data Elements, first launched alongside in 2016. We sought to categorize the elements that matter in open data initiatives into five categories: problem and demand definition, capacity and culture, governance and standards, personnel and partnerships, and risk mitigation. More information on each can be found in the attached report or in the interactive table below.

Read more about the Periodic Table of Open Data Elements and how you can use it to support your work…(More)”.

State of Gender Data


Report by Data2X: “Gender data is fundamental to achieving gender equality and the Sustainable Development Goals. It helps identify inequalities, illuminate a path forward, and monitor global progress. As recognition of its importance has grown over the last decade, the availability of gender data—and its use in decision-making—has improved.

Yet overlapping crises, from the COVID-19 pandemic to climate change and conflict, have imperiled progress on gender equality and the Sustainable Development Goals. In 2022, UN Secretary General Antonio Gutierrez declared that the Sustainable Development Goals are in need of rescue. The 2022 SDG Gender Index by EM2030 found little progress on global gender equality between 2015 and 2020, and a recent assessment by UN Women demonstrates that more than one quarter of the indicators needed to measure progress on gender equality are “far or very far” from 2030 targets….The State of Gender Data is an evolving Data2X publication and digital experience designed to highlight global progress and spur action on gender data. Data2X will update the initiative annually, providing insight into a new dimension of gender data. For our initial launch, we focus on examining funding trends and highlighting promising solutions and key commitments….(More)”.

New Theory for Increasingly Tangled Banks


Essay by Saran Twombly: “Decades before the COVID-19 pandemic demonstrated how rapidly infectious diseases could emerge and spread, the world faced the AIDS epidemic. Initial efforts to halt the contagion were slow as researchers focused on understanding the epidemiology of the virus. It was only by integrating epidemiological theory with behavioral theory that successful interventions began to control the spread of HIV. 

As the current pandemic persists, it is clear that similar applications of interdisciplinary theory are needed to inform decisions, interventions, and policy. Continued infections and the emergence of new variants are the result of complex interactions among evolution, human behavior, and shifting policies across space and over time. Due to this complexity, predictions about the pandemic based on data and statistical models alone—in the absence of any broader conceptual framework—have proven inadequate. Classical epidemiological theory has helped, but alone it has also led to limited success in anticipating surges in COVID-19 infections. Integrating evolutionary theory with data and other theories has revealed more about how and under what conditions new variants arise, improving such predictions.  

AIDS and COVID-19 are examples of complex challenges requiring coordination across families of scientific theories and perspectives. They are, in this sense, typical of many issues facing science and society today—climate change, biodiversity decline, and environmental degradation, to name a few. Such problems occupy interdisciplinary space and arise from no-analog conditions (i.e., situations to which there are no current equivalents), as what were previously only local perturbations trigger global instabilities. As with the pandemic crises, they involve interdependencies and new sources of uncertainty, cross levels of governance, span national boundaries, and include interactions at different temporal and spatial scales. 

Such problems, while impossible to solve from a single perspective, may be successfully addressed by integrating multiple theories. …(More)”.