Article by Eray Gündoğmuş: “On February 6, 2023, earthquakes measuring 7.7 and 7.6 hit the Kahramanmaraş region of Turkey, affecting 10 cities and resulting in more than 42.000 deaths and 120.000 injuries as of February 21.
In the hours following the earthquake, a group of programmers quickly become together on the Discord server called “Açık Yazılım Ağı” , inviting IT professionals to volunteer and develop a project that could serve as a resource for rescue teams, earthquake survivors, and those who wanted to help: afetharita.com. It literally means “disaster map”.
As there was a lack of preparation for the first few days of such a huge earthquake, disaster victims in distress started making urgent aid requests on social media. With the help of thousands of volunteers, we utilized technologies such as artificial intelligence and machine learning to transform these aid requests into readable data and visualized them on afetharita.com. Later, we gathered critical data related to the disaster from necessary institutions and added them to the map.
Disaster Map, which received a total of 35 million requests and 627,000 unique visitors, played a significant role in providing software support during the most urgent and critical periods of the disaster, and helped NGOs, volunteers, and disaster victims to access important information. I wanted to share the process, our experiences, and technical details of this project clearly in writing…(More)”.
Article by Paolo Spada and Tiago C. Peixoto: “For proponents of deliberative democracy, the last couple of years could not have been better. Propelled by the recent diffusion of citizens’ assemblies, deliberative democracy has definitely gained popularity beyond small circles of scholars and advocates. From CNN to the New York Times, the Hindustan Times (India), Folha de São Paulo (Brazil), and Expresso (Portugal), it is now almost difficult to keep up with all the interest in democratic models that promote the random selection of participants who engage in informed deliberation. A new “deliberative wave” is definitely here.
But with popularity comes scrutiny. And whether the deliberative wave will power new energy or crash onto the beach, is an open question. As is the case with any democratic innovation (institutions designed to improve or deepen our existing democratic systems), critically examining assumptions is what allows for management of expectations and, most importantly, gradual improvements.
Proponents of citizens’ assemblies put representativeness at the core of their definition. In fact, it is one of their main selling points. For example, a comprehensive report highlights that an advantage of citizens’ assemblies, compared to other mechanisms of participatory democracy, is their typical combination of random selection and stratification to form a public body that is “representative of the public.” This general argument resonates with the media and the wider public. A recent illustration is an article by The Guardian, which depicts citizens’ assemblies as “a group of people who are randomly selected and reflect the demographics of the population as a whole”
It should be noted that claims of representativeness vary in their assertiveness. For instance, some may refer to citizens’ assemblies as “representative deliberative democracy,” while others may use more cautious language, referring to assemblies’ participants as being “broadly representative” of the population (e.g. by gender, age, education, attitudes). This variation in terms used to describe representativeness should prompt an attentive observer to ask basic questions such as: “Are existing practices of deliberative democracy representative?” “If they are ‘broadly’ representative, how representative are they?” “What criteria, if any, are used to assess whether a deliberative democracy practice is more or less representative of the population?” “Can their representativeness be improved, and if so, how?” These are basic questions that, surprisingly, have been given little attention in recent debates surrounding deliberative democracy. The purpose of this article is to bring attention to these basic questions and to provide initial answers and potential avenues for future research and practice…(More)”.
Article by Hossein Nowbar: “The world continues to confront compounding health, economic and humanitarian crises. We face urgent challenges like carbon in our atmosphere and declining growth of the working age population in developed countries. Microsoft believes that technology – particularly artificial intelligence (AI) – has great potential to help address these problems. The ability to uncover new insights in large datasets will drive new advances in climate science and improve workforce productivity. But success requires more innovation in more fields in less time than any other technological era in human history. And this innovation will be distributed. No one person or company will invent all of the advances in technology necessary to solve these complex problems. It will take collaboration and the fostering of community.
To address these challenges, we need an IP system that promotes pragmatic and practical mechanisms with a focus on how the system can enable innovation, not impede it…
I suggested some ideas the IP community can consider in evolving our IP systems to enable faster progress towards a better future:
Adopt new licensing mechanisms to enable widespread and friction-free use of technology to solve important problems and help inventors obtain economic benefit for their IP. For example, there should be a rate court that establishes license fees for standards-essential patents that would eliminate the ambiguity and uncertainty around licensing such technologies.
Promote exceptions to IP that improve knowledge-sharing, collaboration and development of new technologies like machine learning, such as the text and data mining exceptions adopted in Europe and Japan.
Improve transparency and information flow about IP, including improving patent quality, standardizing licensing models, promoting multiparty cross-licensing, and making economic terms of licenses transparent to everyone in the innovation ecosystem.
Provide economic incentives for collaboration, rewarding those who make their patents freely available for use to address important social problems. We need to promote widespread and friction-free use of technology to take on these important challenges…(More)”.
Essay by Barbara Prainsack: “To solve these problems, we need to think about data governance in new ways. It is no longer enough to assume that asking people to consent to how their data is used is sufficient to prevent harm. In our example of telehealth, and in virtually all data-related scandals of the last decade, from Cambridge Analytica to Robodebt, informed consent did not, or could not, have avoided the problem. We all regularly agree to data uses that we know are problematic – not because we do not care about privacy. We agree because this is the only way to get access to benefits, a mortgage, or teachers and health professionals. In a world where face-to-face assessments are unavailable or excessively expensive, opting out of digital practices would no longer be an option (Prainsack, 2017, pp. 126-131; see also Oudshoorn, 2011).
Solidarity-based data governance (in short: data solidarity) can help us to distribute the risks and the benefits of digital practices more equitably. The details of the framework are spelled out in full elsewhere (Prainsack et al., 2022a, b). In short, data solidarity seeks to facilitate data uses that create significant public value, and at the same time prevent and mitigate harm (McMahon et al., 2020). One important step towards both goals is to stop ascribing risks to data types, and to distinguish between different types of data use instead. In some situations, harm can be prevented by making sure that data is not used for harmful purposes, such as online tracking. In other contexts, however, harm prevention can require that we do not collect the data in the first place. Not recording something, making it invisible and uncountable to others, can be the most responsible way to act in some contexts.
This means that recording and sharing data should not become a default. More data is not always better. Instead, policymakers need to consider carefully – in a dialogue with the people and communities that have a stake in it – what should be recorded, where it will be stored and who governs the data once it has been collected – if at all (see also Kukutai and Taylor, 2016)…(More)”.
Blog by Paul Cairney: “Wouldn’t it be nice if policy scholars and professionals could have frequent and fruitful discussions about policy and policymaking? Both professions could make valuable contributions to our understanding of policy design in a wider political context.
However, it is notoriously difficult to explain what policy is and how it is made, and academics and practitioners may present very different perspectives on what policymakers or governments do. Without a common reference point, how can they cooperate to discuss how to (say) improve policy or policymaking?
One starting point is to visualize policymaking to identify overlaps in perspectives. To that end, if academics and policymakers were to describe ‘the policy process’, could they agree on what it looks like? To help answer this question, in this post I’m presenting some commonly-used images in policy research, then inviting you to share images that you would use to sum up policy work…
One obstacle to a shared description is that we need different images for different aims, including:
To describe and explain what policymakers do. Academics describe one part of a complex policy process, accompanied by a technical language to understand each image.
To describe what policymakers need to do. Practitioners visualise a manageable number of aims or requirements (essential steps, stages, or functions), accompanied by a professional in-house language (such as in the Green Book).
To describe what they would like to do. Governments produce images of policymaking to tell stakeholders or citizens what they do, accompanied by an aspirational language related to what is expected of elected governments…(More)”.
Blog by the Participation Factory: “Participatory budgets (PBs) are in use in countless communities around the world, giving residents the chance to decide how to allocate parts of the public budget. They are usually open for the entire community to take part – but there can be real advantages to starting with a smaller-scale school participatory budget.
Not only do they empower pupils to get involved in local government; but they can also play a crucial role in the students’ civic education. Unlike other educational tools like mock elections, the children actually get to see how the work they put in leads to concrete results. They demonstrate the power of political engagement to children at an early age, leaving them well-placed to become active, engaged citizens in later life….
The basic setup of a school PB should allow children to get a grasp of a whole range of what we call participatory skills – including project development, public speaking, voting, running a campaign, and engaging in deliberative democratic discussions. Younger children can start out just voting for their favourite projects – but as they get older, they can begin to get more involved in the entire process, gradually building their confidence, project management skills, and their understanding of how participation works.
Participatory budgeting improves the children’s participatory skills. We have learned from our experience in Czech and Slovak schools that every year, more children feel comfortable enough to propose a project and run a campaign. They realise that there are techniques and methods to the process that they can easily learn and use, making the whole process less intimidating. They realise that debating and taking initiative doesn’t hurt, but rather leads to real results…(More)”.
CORI Blog: “Racial and ethnic diversity is one of the most commonly misunderstood aspects of rural America.
National media depictions of white farmers and ranchers in the West and Midwest, white coal miners in Appalachia, or the “white working class” living in rural communities reinforce the misconception that rural areas are homogeneously white. It is a misconception that ignores that 86 of the 100 most marginalized counties in the country are rural, 60 of which are located in Tribal lands or Southern regions with large Black populations. It is a misconception that renders invisible the 14 million Black, Hispanic or Latino, Asian, Native, and multiracial people who live in rural America (2020 census-nonmetro plus).
It is a misconception that holds significant consequences.
Misunderstandings of diversity in rural America can inhibit efforts to support programming and policies designed to increase the ability of rural communities to thrive. For rural communities to thrive, national, state, and local leaders need to take efforts to systematically address racial and ethnic inequities that limit the freedom, safety, and opportunity of rural people of color.
There is an imperative to better understand who lives in rural America today. In just the past few years, billions of public and private dollars have been committed to building a more equitable economy. The Infrastructure Investment and Jobs Act (IIJA), the CHIPS Act, and the Inflation Reduction Act (IRA) have committed hundreds of billions of dollars that will be invested by federal agencies and state and local governments in healthcare, housing, energy, and economic development.
Yet, if these historic investments are not informed by an accurate understanding of rural demographics and how these communities have evolved over time in response to government policies and settler-influenced power shifts, then we risk excluding rural communities and people of color from the critical resources that are needed to strengthen communities and economies that serve everyone.
In Part I of the second story in our Rural Aperture Project, we seek to explain how and why such flawed conceptions of rural America exist…(More)”.
Article by Justin Russell: “In the modern age, the research of Judith Glück shows that ‘wiser’ people learn valuable lessons from life’s challenges and then live happier and more fulfilling lives. On the whole, they are more connected with nature, add more to others’ lives and are less easily swayed by unreasoned rhetoric. Read Judith Glück’s Wisdom Profile on evidencebasedwisdom.com for detail on how she defines wisdom.
I have been following the research on wisdom for over a decade now, initially as part of my dissertation, In pursuit of organisational wisdom, which aimed, as part of my MSc in business psychology, to understand the relationship between wisdom and organisation leadership. Subsequently, I’ve become interested in the role that ancient wisdom has in the modern world more as a means to continually grow personally and support coaching clients.
Wisdom has only really entered into the psychological realm (as opposed to the philosophical realm) in the last few decades. Fortunately, it can draw on many previous years of research into vertical development, and generally of our understanding of other corollary ideas such as good decision-making.
While we have an incomplete picture of how wisdom develops, vertical development theories (such as those of Jane Loevinger, Erik Erikson and Robert Kegan) help us appreciate that throughout life we continue to grow and evolve, gaining new capabilities as we do. Using those capabilities is something else though, and the most developed (wisest) among us aren’t widely distributed throughout society. Through understanding wise decision-making, in Igor Grossman’s work, we know that emotional management (as measured through heart rate) is important in being able to take in all the required information and deal with it in a dispassionate (but not unfeeling) way.
As a thought experiment, I ask myself: “How would I go about making a wiser society?” The solution is highly dependent on which branch of wisdom research you attend to and so I see a threefold solution to this otherwise nebulous challenge….(More)”
Article by Max Roser: “The big visualization offers a long-term perspective on the history of technology.
The timeline begins at the center of the spiral. The first use of stone tools, 3.4 million years ago, marks the beginning of this history of technology. Each turn of the spiral then represents 200,000 years of history. It took 2.4 million years – 12 turns of the spiral – for our ancestors to control fire and use it for cooking.3
To be able to visualize the inventions in the more recent past – the last 12,000 years – I had to unroll the spiral. I needed more space to be able to show when agriculture, writing, and the wheel were invented. During this period, technological change was faster, but it was still relatively slow: several thousand years passed between each of these three inventions.
From 1800 onwards, I stretched out the timeline even further to show the many major inventions that rapidly followed one after the other.
The long-term perspective that this chart provides makes it clear just how unusually fast technological change is in our time.
You can use this visualization to see how technology developed in particular domains. Follow, for example, the history of communication: from writing, to paper, to the printing press, to the telegraph, the telephone, the radio, all the way to the Internet and smartphones.
Or follow the rapid development of human flight. In 1903, the Wright brothers took the first flight in human history (they were in the air for less than a minute), and just 66 years later, we landed on the moon. Many people saw both within their lifetimes: the first plane and the moon landing.
This large visualization also highlights the wide range of technology’s impact on our lives. It includes extraordinarily beneficial innovations, such as the vaccine that allowed humanity to eradicate smallpox, and it includes terrible innovations, like the nuclear bombs that endanger the lives of all of us.
What will the next decades bring?
The red timeline reaches up to the present and then continues in green into the future. Many children born today, even without any further increases in life expectancy, will live well into the 22nd century.
New vaccines, progress in clean, low-carbon energy, better cancer treatments – a range of future innovations could very much improve our living conditions and the environment around us. But, as I argue in a series of articles, there is one technology that could even more profoundly change our world: artificial intelligence (AI).
One reason why artificial intelligence is such an important innovation is that intelligence is the main driver of innovation itself. This fast-paced technological change could speed up even more if it’s not only driven by humanity’s intelligence, but artificial intelligence too. If this happens, the change that is currently stretched out over the course of decades might happen within very brief time spans of just a year. Possibly even faster.
I think AI technology could have a fundamentally transformative impact on our world. In many ways, it is already changing our world, as I documented in this companion article. As this technology is becoming more capable in the years and decades to come, it can give immense power to those who control it (and it poses the risk that it could escape our control entirely).
Such systems might seem hard to imagine today, but AI technology is advancing very fast. Many AI experts believe there is a real chance that human-level artificial intelligence will be developed within the next decades, as I documented in this article….(More)”.
Essay by Hannah Chafetz, Uma Kalkar, Marine Ragnet, Stefaan Verhulst: “From the regulations proposed in the European Artificial Intelligence (AI) Act to the launch of OpenAI’s ChatGPT tool, 2022 was a year that saw many policy and technological developments. Taking stock of recent data and technology trends, we offer some conjectures as to how these ideas may play out over the next year. Indeed, predictions can be dangerous, which is why we position the below as conjectures — propositions that remain tentative till more evidence emerges — that can help advance the agenda and direction of responsible use of data for the public good focus areas.
Below, we provide a summary of the five conjectures that The GovLab will track and revisit throughout 2023.
Conjecture 1. In 2023 … non-traditional data may be used with increasing frequency to solve public problems.
Complex crises, from COVID-19 to climate change, demonstrate a need for information about a variety of developments quickly and at scale. Traditional sources are not enough: growing awareness and (re)use of non-traditional data sources (NTD) to fill the gaps in traditional data cast a spotlight on the value of using and combining new data sources for problem-solving. Over the next year, NTD sources could increasingly be called upon by decision-making to address large-scale public problems.
NTD refers to data that is “digitally captured (for example, mobile phone records and financial data), mediated (for example, social media and online data), or observed (for example, satellite imagery),” using new instrumentation mechanisms and is often privately held. Our recent report discussed how COVID-19 was a “watershed moment” in terms of generating access to non-traditional health, mobility, economic, and sentiment data. As detailed in the report, decision-makers around the world increasingly recognize the potential of NTD sources when combined with traditional data responsibly. Similarly, developments in the war in Ukraine presented a pivotal moment regarding the use of NTD sources. For instance, satellite images, social media narrative trends, and real-time location mapping have supported humanitarian action and peacebuilding.
These are just two examples of the increasing interest in NTD to solve public problems. We predict that this trend could continue to expand as technological advances continue to make non-traditional data more widely available to decision-makers. Already, the financial sector is increasingly incorporating non-traditional data to inform decisions such as assessing lending risks, for example. Recently, the fintech business Nova Credit and HSBC partnered together to exploit cross-border data to allow immigrants access to credit by predicting creditworthiness via digital footprint and psychometric data. This trend is compounded by increased legislation aiming to open up the re-use of private sector data, particularly in Europe. The increased attention to NTD sources signals a need to prioritize the alignment of the supply and demand of NTD and develop a systematized approach to how it can be integrated within decision-making cycles…(More)”.
