Paper by James Andreoni, Nikos Nikiforakis, and Simon Siegenthaler: “Social tipping—instances of sudden change that upend social order—is rarely anticipated and usually understood only in hindsight. The ability to predict when societies will reach a tipping point has significant implications for welfare, especially when social norms are detrimental. In a large-scale laboratory experiment, we identify a model that accurately predicts social tipping and use it to address a long-standing puzzle: Why do norms sometimes persist when they are detrimental to social welfare? We show that beneficial norm change is often hindered by a desire to avoid the costs associated with transitioning to a new norm. We find that policies that help societies develop a common understanding of the benefits from change foster the abandonment of detrimental norms….(More)”.
You Are Here: A Field Guide for Navigating Polarized Speech, Conspiracy Theories, and Our Polluted Media Landscape
Book by Whitney Phillips and Ryan M. Milner: “Our media environment is in crisis. Polarization is rampant. Polluted information floods social media. Even our best efforts to help clean up can backfire, sending toxins roaring across the landscape. In You Are Here, Whitney Phillips and Ryan Milner offer strategies for navigating increasingly treacherous information flows. Using ecological metaphors, they emphasize how our individual me is entwined within a much larger we, and how everyone fits within an ever-shifting network map.
Phillips and Milner describe how our poisoned media landscape came into being, beginning with the Satanic Panics of the 1980s and 1990s—which, they say, exemplify “network climate change”—and proceeding through the emergence of trolling culture and the rise of the reactionary far right (as well as its amplification by journalists) during and after the 2016 election. They explore the history of conspiracy theories in the United States, focusing on those concerning the Deep State; explain why old media literacy solutions fail to solve new media literacy problems; and suggest how we can navigate the network crisis more thoughtfully, effectively, and ethically. We need a network ethics that looks beyond the messages and the messengers to investigate toxic information’s downstream effects….(More)”.
Why bad times call for good data
Tim Harford in the Financial Times: “Watching the Ever Given wedge itself across the Suez Canal, it would have taken a heart of stone not to laugh. But it was yet another unpleasant reminder that the unseen gears in our global economy can all too easily grind or stick.
From the shutdown of Texas’s plastic polymer manufacturing to a threat, to vaccine production from a shortage of giant plastic bags, we keep finding out the hard way that modern life relies on weak links in surprising places.
So where else is infrastructure fragile and taken for granted? I worry about statistical infrastructure — the standards and systems we rely on to collect, store and analyse our data.
Statistical infrastructure sounds less important than a bridge or a power line, but it can mean the difference between life and death for millions. Consider Recovery (Randomised Evaluations of Covid-19 Therapy). Set up in a matter of days by two Oxford academics, Martin Landray and Peter Horby, over the past year Recovery has enlisted hospitals across the UK to run randomised trials of treatments such as the antimalarial drug hydroxychloroquine and the cheap steroid dexamethasone.
With minimal expense and paperwork, it turned the guesses of physicians into simple but rigorous clinical trials. The project quickly found that dexamethasone was highly effective as a treatment for severe Covid-19, thereby saving a million lives.
Recovery relied on data accumulated as hospitals treated patients and updated their records. It wasn’t always easy to reconcile the different sources — some patients were dead according to one database and alive on another. But such data problems are solvable and were solved. A modest amount of forethought about collecting the right data in the right way has produced enormous benefits….
But it isn’t just poor countries that have suffered. In the US, data about Covid-19 testing was collected haphazardly by states. This left the federal government flying blind, unable to see where and how quickly the virus was spreading. Eventually volunteers, led by the journalists Robinson Meyer and Alexis Madrigal of the Covid Tracking Project, put together a serviceable data dashboard. “We have come to see the government’s initial failure here as the fault on which the entire catastrophe pivots,” wrote Meyer and Madrigal in The Atlantic. They are right.
What is more striking is that the weakness was there in plain sight. Madrigal recently told me that the government’s plan for dealing with a pandemic assumed that good data would be available — but did not build the systems to create them. It is hard to imagine a starker example of taking good statistical infrastructure for granted….(More)”.
Global inequality remotely sensed
Paper by M. Usman Mirza et al: “Economic inequality is notoriously difficult to quantify as reliable data on household incomes are missing for most of the world. Here, we show that a proxy for inequality based on remotely sensed nighttime light data may help fill this gap. Individual households cannot be remotely sensed. However, as households tend to segregate into richer and poorer neighborhoods, the correlation between light emission and economic thriving shown in earlier studies suggests that spatial variance of remotely sensed light per person might carry a signal of economic inequality.
To test this hypothesis, we quantified Gini coefficients of the spatial variation in average nighttime light emitted per person. We found a significant relationship between the resulting light-based inequality indicator and existing estimates of net income inequality. This correlation between light-based Gini coefficients and traditional estimates exists not only across countries, but also on a smaller spatial scale comparing the 50 states within the United States. The remotely sensed character makes it possible to produce high-resolution global maps of estimated inequality. The inequality proxy is entirely independent from traditional estimates as it is based on observed light emission rather than self-reported household incomes. Both are imperfect estimates of true inequality. However, their independent nature implies that the light-based proxy could be used to constrain uncertainty in traditional estimates. More importantly, the light-based Gini maps may provide an estimate of inequality where previously no data were available at all….(More)”.
Tech tools help deepen citizen input in drafting laws abroad and in U.S. states
Gopal Ratnam at RollCall: “Earlier this month, New Jersey’s Department of Education launched a citizen engagement process asking students, teachers and parents to vote on ideas for changes that officials should consider as the state reopens its schools after the pandemic closed classrooms for a year.
The project, managed by The Governance Lab at New York University’s Tandon School of Engineering, is part of a monthlong nationwide effort using an online survey tool called All Our Ideas to help state education officials prioritize policymaking based on ideas solicited from those who are directly affected by the policies.
Among the thousands of votes cast for various ideas nationwide, teachers and parents backed changes that would teach more problem-solving skills to kids. But students backed a different idea as the most important: making sure that kids have social and emotional skills, as well as “self-awareness and empathy.”
A government body soliciting ideas from those who are directly affected, via online technology, is one small example of greater citizen participation in governance that advocates hope can grow at both state and federal levels….
Taiwan has taken crowdsourcing legislative ideas to a new height.
Using a variety of open-source engagement and consultation tools that are collectively known as the vTaiwan process, government ministries, elected representatives, experts, civil society groups, businesses and ordinary citizens come together to produce legislation.
The need for an open consultation process stemmed from the 2014 Sunflower Student Movement, when groups of students and others occupied the Taiwanese parliament to protest the fast-tracking of a trade agreement with China with little public review.
After the country’s parliament acceded to the demands, the “consensus opinion was that instead of people having to occupy the parliament every time there’s a controversial, emergent issue, it might actually work better if we have a consultation mechanism in the very beginning of the issue rather than at the end,” said Audrey Tang, Taiwan’s digital minister. …
At about the same time that Taiwan’s Sunflower movement was unfolding, in Brazil then-President Dilma Rousseff signed into law the country’s internet bill of rights in April 2014.
The bill was drafted and refined through a consultative process that included not only legal and technical experts but average citizens as well, said Debora Albu, program coordinator at the Institute for Technology and Society of Rio, also known as ITS.
The institute was involved in designing the platform for seeking public participation, Albu said.
“From then onwards, we wanted to continue developing projects that incorporated this idea of collective intelligence built into the development of legislation or public policies,” Albu said….(More)”.
We’re Beating Systems Change to Death
Essay by Kevin Starr: “Systems change! Just saying the words aloud makes me feel like one of the cognoscenti, one of the elite who has transcended the ways of old-school philanthropy. Those two words capture our aspirations of lasting impact at scale: systems are big, and if you manage to change them, they’ll keep spinning out impact forever. Why would you want to do anything else?
There’s a problem, though. “Systems analysis” is an elegant and useful way to think about problems and get ideas for solutions, but “systems change” is accelerating toward buzzword purgatory. It’s so sexy that everyone wants to use it for everything. …
But when you rummage through the growing literature on systems change thinking, there are in fact a few recurring themes. One is the need to tackle the root causes of any problem you take on. Another is that a broad coalition must be assembled ASAP. Finally, the most salient theme is the notion that the systems involved are transformed as a result of the work (although in many of the examples I read about, it’s not articulated clearly just what system is being changed).
Taken individually or as a whole, these themes point to some of the ways in which systems change is a less-than-ideal paradigm for the work we need to get done:
1. It’s too hard to know to what degree systems change is or isn’t happening. It may be the case that “not everything that matters can be counted,” but most of the stuff that matters can, and it’s hard to get better at something if you’re unable to measure it. But these words of a so-called expert on systems change measurement are typical of what I’ve seen in in the literature: “Measuring systems change is about detecting patterns in the connections between the parts. It is about qualitative changes in the structure of the system, about its adaptiveness and resilience, about synergies emerging from collective efforts—and more…”
Like I said, it’s too hard to know to what is or isn’t happening.
2. “Root cause” thinking can—paradoxically—bog down progress. “Root cause” analysis is a common feature of most systems change discussions, and it’s a wonderful tool to generate ideas and avoid unintended consequences. However, broad efforts to tackle all of a problem’s root causes can turn anything into a complicated, hard-to-replicate project. It can also make things look so overwhelming as to result in a kind of paralysis. And however successful a systems change effort might be, that complication makes it hard to replicate, and you’re often stuck with a one-off project….(More)”.
Innovation in Real Places: Strategies for Prosperity in an Unforgiving World
Book by Dan Breznitz: “Across the world, cities and regions have wasted trillions of dollars blindly copying the Silicon Valley model of growth creation. We have lived with this system for decades, and the result is clear: a small number of regions and cities are at the top of the high-tech industry, but many more are fighting a losing battle to retain economic dynamism. But, as this books details, there are other models for innovation-based growth that don’t rely on a flourishing high-tech industry. Breznitz argues that the purveyors of the dominant ideas on innovation have a feeble understanding of the big picture on global production and innovation.
They conflate innovation with invention and suffer from techno-fetishism. In their devotion to start-ups, they refuse to admit that the real obstacle to growth for most cities is the overwhelming power of the real hubs, which siphon up vast amounts of talent and money. Communities waste time, money, and energy pursuing this road to nowhere. Instead, Breznitz proposes that communities focus on where they fit within the four stages in the global production process. Success lies in understanding the changed structure of the global system of production and then using those insights to enable communities to recognize their own advantages, which in turn allows to them to foster surprising forms of specialized innovation. All localities have certain advantages relative to at least one stage of the global production process, and the trick is in recognizing it….(More)”.
Budget transparency and governance quality: a cross-country analysis
Paper by Marco Bisogno and Beatriz Cuadrado-Ballesteros: “The aim of this study is to assess whether there is a relationship between budget transparency and governance quality. The so-called openness movement and the global financial crises, which have put significant pressure on governments to cut expenditures and ensure balanced budgets, have motivated this research. The public choice and principal-agent theories have been used to investigate this relationship, implementing econometric models based on a sample of 96 countries over the period 2008–2019. The results show that higher levels of budget transparency positively affect the quality of governance, and vice versa, documenting simultaneous causality between both issues….(More)”
Crowdsourcing: Citizens as coproducers of public services
Paper by Helen K. Liu: “Crowdsourcing serves as a distributed problem‐solving production model for modern governments, and it has the potential to transform citizens into coproducers of public services. To consolidate the theoretical basis, this article provides a typology for crowdsourcing public services based on theories of coproduction, public sector volunteerism, and government–citizen relations. This typology includes two dimensions—the policy stage, and the functionality of citizens’ effort—and four types of crowdsourcing, namely, complementary crowdsourcing in service implementation, supplementary crowdsourcing in service implementation, complementary crowdsourcing in policy and service design, and supplementary crowdsourcing in policy design. Four cases are selected for illustration. Designing crowdsourcing based on citizen and government relationships will help designers align goals and tasks to the right coproducers and enhance relationships in a democratic way. Furthermore, this typology will allow the field to systematically and collectively build knowledge….(More)”.
Towards intellectual freedom in an AI Ethics Global Community
Paper by Christoph Ebell et al: “The recent incidents involving Dr. Timnit Gebru, Dr. Margaret Mitchell, and Google have triggered an important discussion emblematic of issues arising from the practice of AI Ethics research. We offer this paper and its bibliography as a resource to the global community of AI Ethics Researchers who argue for the protection and freedom of this research community. Corporate, as well as academic research settings, involve responsibility, duties, dissent, and conflicts of interest. This article is meant to provide a reference point at the beginning of this decade regarding matters of consensus and disagreement on how to enact AI Ethics for the good of our institutions, society, and individuals. We have herein identified issues that arise at the intersection of information technology, socially encoded behaviors, and biases, and individual researchers’ work and responsibilities. We revisit some of the most pressing problems with AI decision-making and examine the difficult relationships between corporate interests and the early years of AI Ethics research. We propose several possible actions we can take collectively to support researchers throughout the field of AI Ethics, especially those from marginalized groups who may experience even more barriers in speaking out and having their research amplified. We promote the global community of AI Ethics researchers and the evolution of standards accepted in our profession guiding a technological future that makes life better for all….(More)”.