Article by Paloma Caravantes and Emanuela Lombardo: “This article examines the potential of feminist democratic innovations in policy and institutional politics. It examines how feminist democratic innovations can be conceptualised and articulated in local institutions. Combining theories on democratic governance, feminist democracy, social movements, municipalism, decentralisation, gender equality policies and state feminism, it conceptualises feminist democratic innovations in policy and politics as innovations oriented at (a) transforming knowledge, (b) transforming policymaking and public funding, (c) transforming institutions, and (d) transforming actors’ coalitions. Through analysis of municipal plans and interviews with key actors, the article examines feminist democratic innovations in the policy and politics of Barcelona’s local government from 2015 to 2023. Emerging from the mobilisation of progressive social movements after the 2008 economic crisis, the findings uncover a laboratory of feminist municipal politics, following the election of a new government and self-proclaimed feminist mayor. Critical actors and an enabling political context play a pivotal role in the adoption of this feminist institutional politics. The article concludes by arguing that feminist institutional politics at the local level contribute to democratising policy and politics in innovative ways, in particular encouraging inclusive intersectionality and participatory discourses and practices…(More)”.
Regulatory experimentation: Moving ahead on the agile regulatory governance agenda
OECD Policy Paper: “This policy paper aims to help governments develop regulatory experimentation constructively and appropriately as part of their implementation of the 2021 OECD Recommendation for Agile Regulatory Governance to Harness Innovation. Regulatory experimentation can help promote adaptive learning and innovative and better-informed regulatory policies and practices. This policy paper examines key concepts, definitions and constitutive elements of regulatory experimentation. It outlines the rationale for using regulatory experimentation, discusses enabling factors and governance requirements, and presents a set of forward-looking conclusions…(More)”.
Plurality: The Future of Collaborative Technology and Democracy
Book by E. Glen Weyl, Audrey Tang and ⿻ Community: “Technology and democracy today are at odds: technology reinforces authoritarian oversight and corrupts democratic institutions, while democracies fight back with restrictive regulation and public sector conservatism. However, this conflict is not inevitable. This is the consequence of choosing to invest in technologies such as AI and cryptocurrencies at the expense of democratic principles. In some places, such as the Ether community, Estonia, Colorado, and especially Taiwan, the focus has shifted to technologies that promote pluralistic collaboration, and have witnessed the co-prosperity of both democracy and technology. Written by the paradigm leaders of the Plurality, this book shows for the first time how every technologist, policymaker, business leader, and activist can use it to build a more collaborative, diverse, and productive democratic world.
When Uber arrived in Taiwan, it sparked a lot of controversy, as it has in most parts of the world. But instead of fueling the controversy, social media, with the help of vTaiwan, a platform developed with the help of cabinet ministers, encouraged citizens to share their feelings and engage in deep conversations with thousands of participants to brainstorm how to regulate online ride-hailing services. The technology, which uses statistical tools often associated with AI to aggregate opinions, allows each participant to quickly view a clear representation of all people’s viewpoints and provide feedback on their own thoughts. From the outset, a broadly supported viewpoint is brought to the forefront among a diverse group of people with different perspectives, creating a rough consensus that ensures the benefits of this new form of ridesharing while protecting the rights of the drivers, and is implemented by the government. This process has been used in Taiwan to solve dozens of controversial problems and has quickly spread to governments, cooperatives, and blockchain communities around the world…(More)”.
The Unintended Consequences of Data Standardization
Article by Cathleen Clerkin: “The benefits of data standardization within the social sector—and indeed just about any industry—are multiple, important, and undeniable. Access to the same type of data over time lends the ability to track progress and increase accountability. For example, over the last 20 years, my organization, Candid, has tracked grantmaking by the largest foundations to assess changes in giving trends. The data allowed us to demonstrate philanthropy’s disinvestment in historically Black colleges and universities. Data standardization also creates opportunities for benchmarking—allowing individuals and organizations to assess how they stack up to their colleagues and competitors. Moreover, large amounts of standardized data can help predict trends in the sector. Finally—and perhaps most importantly to the social sector—data standardization invariably reduces the significant reporting burdens placed on nonprofits.
Yet, for all of its benefits, data is too often proposed as a universal cure that will allow us to unequivocally determine the success of social change programs and processes. The reality is far more complex and nuanced. Left unchecked, the unintended consequences of data standardization pose significant risks to achieving a more effective, efficient, and equitable social sector…(More)”.
Data Authenticity, Consent, and Provenance for AI Are All Broken: What Will It Take to Fix Them?
Article by Shayne Longpre et al: “New AI capabilities are owed in large part to massive, widely sourced, and underdocumented training data collections. Dubious collection practices have spurred crises in data transparency, authenticity, consent, privacy, representation, bias, copyright infringement, and the overall development of ethical and trustworthy AI systems. In response, AI regulation is emphasizing the need for training data transparency to understand AI model limitations. Based on a large-scale analysis of the AI training data landscape and existing solutions, we identify the missing infrastructure to facilitate responsible AI development practices. We explain why existing tools for data authenticity, consent, and documentation alone are unable to solve the core problems facing the AI community, and outline how policymakers, developers, and data creators can facilitate responsible AI development, through universal data provenance standards…(More)”.
Why data about people are so hard to govern
Paper by Wendy H. Wong, Jamie Duncan, and David A. Lake: “How data on individuals are gathered, analyzed, and stored remains largely ungoverned at both domestic and global levels. We address the unique governance problem posed by digital data to provide a framework for understanding why data governance remains elusive. Data are easily transferable and replicable, making them a useful tool. But this characteristic creates massive governance problems for all of us who want to have some agency and choice over how (or if) our data are collected and used. Moreover, data are co-created: individuals are the object from which data are culled by an interested party. Yet, any data point has a marginal value of close to zero and thus individuals have little bargaining power when it comes to negotiating with data collectors. Relatedly, data follow the rule of winner take all—the parties that have the most can leverage that data for greater accuracy and utility, leading to natural oligopolies. Finally, data’s value lies in combination with proprietary algorithms that analyze and predict the patterns. Given these characteristics, private governance solutions are ineffective. Public solutions will also likely be insufficient. The imbalance in market power between platforms that collect data and individuals will be reproduced in the political sphere. We conclude that some form of collective data governance is required. We examine the challenges to the data governance by looking a public effort, the EU’s General Data Protection Regulation, a private effort, Apple’s “privacy nutrition labels” in their App Store, and a collective effort, the First Nations Information Governance Centre in Canada…(More)”
Sludge Toolkit
About: “Sludge audits are a way to identify, quantify and remove sludge (unnecessary frictions) from government services. Using the NSW Government sludge audit method, you can
- understand where sludge is making your government service difficult to access
- quantify the impact of sludge on the community
- know where and how you can improve your service using behavioural science
- measure the impact of your service improvements…(More)”.
This City Pilots Web3 Quadratic Funding for Public Infrastructure
Article by Makoto Takahiro: “The city of Split, Croatia is piloting an innovative new system for deciding how to fund municipal infrastructure projects. Called “quadratic funding,” the mechanism aims to fairly account for both public and private preferences when allocating limited budget resources.
A coalition of organizations including BlockSplit, Funding the Commons, Gitcoin, and the City of Split launched the Municipal Quadratic Funding Initiative in September 2023. The project goals include implementing quadratic funding for prioritizing public spending, utilizing web3 tools to increase transparency and participation, and demonstrating the potential of these technologies to improve legacy processes.
If successful, the model could scale to other towns and cities or inspire additional quadratic funding experiments.
The partners believe that the transparency and configurability of blockchain systems make them well-suited to quadratic funding applications.
Quadratic funding mathematically accounts for the intensity of demand for public goods. Groups can create projects which individuals can support financially. The amount of money ultimately directed to each proposal is based on the square of support received. This means that projects attracting larger numbers of smaller contributions can compete with those receiving fewer large donations.
In this way, quadratic funding aims to reflect both willingness to pay and breadth of support in funding decisions. It attempts to break tendency towards corruption where influential groups lobby for their niche interests. The goal is a fairer allocation suited to the whole community’s preferences.
The initiative will build on open source quadratic funding infrastructure already deployed for other uses like funding public goods on Ethereum. Practical web3 tools can help teadministration manage funding rounds and disburse awards…(More)”.
Creating an Integrated System of Data and Statistics on Household Income, Consumption, and Wealth: Time to Build
Report by the National Academies: “Many federal agencies provide data and statistics on inequality and related aspects of household income, consumption, and wealth (ICW). However, because the information provided by these agencies is often produced using different concepts, underlying data, and methods, the resulting estimates of poverty, inequality, mean and median household income, consumption, and wealth, as well as other statistics, do not always tell a consistent or easily interpretable story. Measures also differ in their accuracy, timeliness, and relevance so that it is difficult to address such questions as the effects of the Great Recession on household finances or of the Covid-19 pandemic and the ensuing relief efforts on household income and consumption. The presence of multiple, sometimes conflicting statistics at best muddies the waters of policy debates and, at worst, enable advocates with different policy perspectives to cherry-pick their preferred set of estimates. Achieving an integrated system of relevant, high-quality, and transparent household ICW data and statistics should go far to reduce disagreement about who has how much, and from what sources. Further, such data are essential to advance research on economic wellbeing and to ensure that policies are well targeted to achieve societal goals…(More)”.
Designing an instrument for scaling public sector innovations
Paper by Mirte A R van Hout, Rik B Braams, Paul Meijer, and Albert J Meijer: “Governments worldwide invest in developing and diffusing innovations to deal with wicked problems. While experiments and pilots flourish, governments struggle to successfully scale innovations. Public sector scaling remains understudied, and scholarly suggestions for scaling trajectories are lacking. Following a design approach, this research develops an academically grounded, practice-oriented scaling instrument for planning and reflecting on the scaling of public sector innovations. We design this instrument based on the academic literature, an empirical analysis of three scaling projects at the Dutch Ministry of Infrastructure and Water Management, and six focus groups with practitioners. This research proposes a context-specific and iterative understanding of scaling processes and contributes a typology of scaling barriers and an additional scaling strategy to the literature. The presented instrument increases our academic understanding of scaling and enables teams of policymakers, in cooperation with stakeholders, to plan and reflect on a context-specific scaling pathway for public sector innovations…(More)”.