Governance Innovation ver.2: A Guide to Designing and Implementing Agile Governance


Draft report by the Ministry of Economy, Trade and Industry (METI): “Japan has been aiming at the realization of “Society 5.0,” a policy for building a human-centric society which realizes both economic development and solutions to social challenges by taking advantage of a system in which cyberspaces, including AI, IoT and big data, and physical spaces are integrated in a sophisticated manner (CPSs: cyber-physical systems). In advancing social implementation of innovative technologies toward the realization of the Society 5.0, it is considered necessary to fundamentally reform governance models in view of changes in social structures which new technologies may bring about.

Triggered by this problem awareness, at the G20 Ministerial Meeting on Trade and Digital Economy, which Japan hosted in June 2019, the ministers declared in the ministerial statement the need for “governance innovation” tailored to social changes which will be brought about by digital technologies and social implementation thereof.

In light of this, METI inaugurated its Study Group on a New Governance Model in Society 5.0 (hereinafter referred to as the “study group”) and in July 2020, the study group published a report titled “GOVERNANCE INNOVATION: Redesigning Law and Architecture for Society 5.0” (hereinafter referred to as the “first report”). The first report explains ideal approaches to cross-sectoral governance by multi-stakeholders, including goal-based regulations, importance for businesses to fulfill their accountability, and enforcement of laws with an emphasis on incentives.

Against this backdrop, the study group, while taking into consideration the outcomes of the first report, presented approaches to “agile governance” as an underlying idea of the governance shown in the Society 5.0 policy, and then prepared the draft report titled “Governance Innovation ver.2: A Guide to Designing and Implementing Agile Governance” as a compilation presenting a variety of ideal approaches to governance mechanisms based on agile governance, including corporate governance, regulations, infrastructures, markets and social norms.

In response, METI opened a call for public comments on this draft report in order to receive opinions from a variety of people. As the subjects shown in the draft report are common challenges seen across the world and many parts of the subjects require international cooperation, METI wishes to receive wide-ranging, frank opinions not only from people in Japan but also from those in overseas countries….(More)”.

European Data Economy: Between Competition and Regulation


Report by René Arnold, Christian Hildebrandt, and Serpil Taş: “Data and its economic impact permeates all sectors of the economy. The data economy is not a new sector, but more like a challenge for all firms to compete and innovate as part of a new wave of economic value creation.

With data playing an increasingly important role across all sectors of the economy, the results of this report point European policymakers to promote the development and adoption of unified reference architectures. These architectures constitute a technology-neutral and cross-sectoral approach that will enable companies small and large to compete and to innovate—unlocking the economic potential of data capture in an increasingly digitized world.

Data access appears to be less of a hindrance to a thriving data economy due to the net increase in capabilities in data capture, elevation, and analysis. What does prove difficult for firms is discovering existing datasets and establishing their suitability for achieving their economic objectives. Reference architectures can facilitate this process as they provide a framework to locate potential providers of relevant datasets and carry sufficient additional information (metadata) about datasets to enable firms to understand whether a particular dataset, or parts of it, fits their purpose.

Whether third-party data access is suitable to solve a specific business task in the first place ought to be a decision at the discretion of the economic actors involved. As our report underscores, data captured in one context with a specific purpose may not be fit for another context or another purpose. Consequently, a firm has to evaluate case-by-case whether first-party data capture, third-party data access, or a mixed approach is the best solution. This evaluation will naturally depend on whether there is any other firm capturing data suitable for the task that is willing to negotiate conditions for third-party access to this data. Unified data architectures may also lower the barriers for a firm capturing suitable data to engage in negotiations, since its adoption will lower the costs of making the data ready for a successful exchange. Such architectures may further integrate licensing provisions ensuring that data, once exchanged, is not used beyond the agreed purpose. It can also bring in functions that improve the discoverability of potential data providers….(More)”.

How can we measure productivity in the public sector?


Ravi Somani at the World Bank: “In most economies, the public sector is a major purchaser of goods, services and labor. According to the Worldwide Bureaucracy Indicators, globally the public sector accounts for around 25% of GDP and 38% of formal employment. Generating efficiency gains in the public sector can, therefore, have important implications for a country’s overall economic performance.  

Public-sector productivity measures the rate with which inputs are converted into desirable outputs in the public sector. Measures can be developed at the level of the employee, organization, or overall public sector, and can be tracked over time. Such information allows policymakers to identify good and bad performers, understand what might be correlated with good performance, and measure the returns to different types of public expenditures. This knowledge can be used to improve the allocation of public resources in the future and maximize the impact of the public purse.

But how can we measure it?

However, measuring productivity in the public sector can be tricky because:

  • There are often no market transactions for public services, or they are distorted by subsidies and other market imperfections.
  • Many public services are complex, requiring (often immeasurable) inputs from multiple individuals and organizations.
  • There is often a substantial time lag between investments in inputs and the realization of outputs and outcomes.

This recent World Bank publication provides a summary of the different approaches to measuring productivity in the public sector, presented in the table below.  For simplicity, the approaches are separated into: ‘macro’ approaches, which provide aggregate information at the level of an organization, sector, or service as a whole; and ‘micro’ approaches, which can be applied to the individual employee, task, project, and process.   
 

Macro and Micro Approaches to measure public-sector productivity

There is no silver bullet for accurately measuring public-sector productivity – each approach has its own limitations.  For example, the cost-weighted-output approach requires activity-level data, necessitates different approaches for different sectors, and results in metrics with difficult-to-interpret absolute levels.  Project-completion rates require access to project-level data and may not fully account for differences in the quality and complexity of projects. The publication includes a list of the pros, cons, and implementation requirements for each approach….(More)”.

Wikipedia Is Finally Asking Big Tech to Pay Up


Noam Cohen at Wired: “From the start, Google and Wikipedia have been in a kind of unspoken partnership: Wikipedia produces the information Google serves up in response to user queries, and Google builds up Wikipedia’s reputation as a source of trustworthy information. Of course, there have been bumps, including Google’s bold attempt to replace Wikipedia with its own version of user-generated articles, under the clumsy name “Knol,” short for knowledge. Knol never did catch on, despite Google’s offer to pay the principal author of an article a share of advertising money. But after that failure, Google embraced Wikipedia even tighter—not only linking to its articles but reprinting key excerpts on its search result pages to quickly deliver Wikipedia’s knowledge to those seeking answers.

The two have grown in tandem over the past 20 years, each becoming its own household word. But whereas one mushroomed into a trillion-dollar company, the other has remained a midsize nonprofit, depending on the generosity of individual users, grant-giving foundations, and the Silicon Valley giants themselves to stay afloat. Now Wikipedia is seeking to rebalance its relationships with Google and other big tech firms like Amazon, Facebook, and Apple, whose platforms and virtual assistants lean on Wikipedia as a cost-free virtual crib sheet.

Today, the Wikimedia Foundation, which operates the Wikipedia project in more than 300 languages as well as other wiki-projects, is announcing the launch of a commercial product, Wikimedia Enterprise. The new service is designed for the sale and efficient delivery of Wikipedia’s content directly to these online behemoths (and eventually, to smaller companies too)….(More)”.

The Handbook: How to regulate?


Handbook edited by the Regulatory Institute: “…presents an inventory of regulatory techniques from over 40 jurisdictions and a basic universal method. The Handbook is based on the idea that officials with an inventory of regulatory techniques have more choices and can develop better regulations. The same goes for officials using methodological knowledge. The Handbook is made available free of charge because better regulations benefit us all….

The purpose of the Handbook is to assist officials involved in regulatory activities. Readers can draw inspiration from it, can learn how colleagues have tackled a certain regulatory challenge and can even develop a tailor-made systematic approach to improve their regulation. The Handbook can also be used as a basis for training courses or for self-training.

The Handbook is not intended to be read from A to Z. Instead, readers are invited to pick and choose the sections that are relevant to them. The Handbook was not developed to be the authoritative source of how to regulate, but to offer in the most neutral and objective way possibilities for improving regulation…

The Handbook explores the empty space between:

  • the constitution or similar documents setting the legal frame,
  • the sector-specific policies followed by the government, administration, or institution,
  • the impact assessment, better regulation, simplification, and other regulatory policies,
  • applicable drafting instructions or recommendations, and
  • the procedural settings of the respective jurisdiction….(More)”.

A new approach to problem-solving across the Sustainable Development Goals


Alexandra Bracken, John McArthur, and Jacob Taylor at Brookings: “The economic, social, and environmental challenges embedded throughout the world’s 17 Sustainable Development Goals (SDGs) will require many breakthroughs from business as usual. COVID-19 has only underscored the SDGs’ central message that the underlying problems are both interconnected and urgent, so new mindsets are required to generate faster progress on many fronts at once. Our recent report, 17 Rooms: A new approach to spurring action for the Sustainable Development Goals, describes an effort to innovate around the process of SDG problem-solving itself.

17 Rooms aims to advance problem-solving within and across all the SDGs. As a partnership between Brookings and The Rockefeller Foundation, the first version of the undertaking was convened in September 2018, as a single meeting on the eve of the U.N. General Assembly in New York. The initiative has since evolved into a two-pronged effort: an annual flagship process focused on global-scale policy issues and a community-level process in which local actors are taking 17 Rooms methods into their own hands.

In practical terms, 17 Rooms consists of participants from disparate specialist communities each meeting in their own “Rooms,” or working groups, one for each SDG. Each Room is tasked with a common assignment of identifying cooperative actions they can take over the subsequent 12-18 months. Emerging ideas are then shared across Rooms to spot opportunities for collaboration.

The initiative continues to evolve through ongoing experimentation, so methods are not overly fixed, but three design principles help define key elements of the 17 Rooms mindset:

  1. All SDGs get a seat at the table. Insights, participants, and priorities are valued equally across all the specialist communities focused on individual dimensions of the SDGs
  2. Take a next step, not the perfect step. The process encourages participants to identify—and collaborate on—actions that are “big enough to matter, but small enough to get done”
  3. Conversations, not presentations. Discussions are structured around collaboration and peer-learning, aiming to focus on what’s best for an issue, not any individual organization

These principles appear to contribute to three distinct forms of value: the advancement of action, the generation of insights, and a strengthened sense of community among participants….(More)”.

Establishment of Sustainable Data Ecosystems


Report and Recommendations for the evolution of spatial data infrastructures by S. Martin, Gautier, P., Turki, and S., Kotsev: “The purpose of this study is to identify and analyse a set of successful data ecosystems and to address recommendations that can act as catalysts of data-driven innovation in line with the recently published European data strategy. The work presented here tries to identify to the largest extent possible actionable items.

Specifically, the study contributes with insights into the approaches that would help in the evolution of existing spatial data infrastructures (SDI), which are usually governed by the public sector and driven by data providers, to self-sustainable data ecosystems where different actors (including providers, users, intermediaries.) contribute and gain social and economic value in accordance with their specific objectives and incentives.

The overall approach described in this document is based on the identification and documentation of a set of case studies of existing data ecosystems and use cases for developing applications based on data coming from two or more data ecosystems, based on existing operational or experimental applications. Following a literature review on data ecosystem thinking and modelling, a framework consisting of three parts (Annex I) was designed. An ecosystem summary is drawn, giving an overall representation of the ecosystem key aspects. Two additional parts are detailed. One dedicated to ecosystem value dynamic illustrating how the ecosystem is structured through the resources exchanged between stakeholders, and the associated value.

Consequently, the ecosystem data flows represent the ecosystem from a complementary and more technical perspective, representing the flows and the data cycles associated to a given scenario. These two parts provide good proxies to evaluate the health and the maturity of a data ecosystem…(More)”.

The Third Wave of Open Data Toolkit


The GovLab: “Today, as part of Open Data Week 2021, the Open Data Policy Lab is launching  The Third Wave of Open Data Toolkit, which provides organizations with specific operational guidance on how to foster responsible, effective, and purpose-driven re-use. The toolkit—authored by Andrew Young, Andrew J. Zahuranec, Stefaan G. Verhulst, and Kateryna Gazaryan—supports the work of data stewards, responsible data leaders at public, private, and civil society organizations empowered to seek new ways to create public value through cross-sector data collaboration. The toolkit provides this support a few different ways. 

First, it offers a framework to make sense of the present and future open data ecosystem. Acknowledging that data re-use is the result of many stages, the toolkit separates each stage, identifying the ways the data lifecycle plays into data collaboration, the way data collaboration plays into the production of insights, the way insights play into conditions that enable further collaboration, and so on. By understanding the processes that data is created and used, data stewards can promote better and more impactful data management. 

Third Wave Framework

Second, the toolkit offers eight primers showing how data stewards can operationalize the actions previously identified as being part of the third wave. Each primer includes a brief explanation of what each action entails, offers some specific ways data stewards can implement these actions, and lists some supplementary pieces that might be useful in this work. The primers, which are available as part of the toolkit and as standalone two-pagers, are…(More)”.

2030 Compass CoLab


About: “2030 Compass CoLab invites a group of experts, using an online platform, to contribute their perspectives on potential interactions between the goals in the UN’s 2030 Agenda for Sustainable Development.

By combining the insight of participants who posses broad and diverse knowledge, we hope to develop a richer understanding of how the Sustainable Development Goals (SDGs) may be complementary or conflicting.

Compass 2030 CoLab is part of a larger project, The Agenda 2030 Compass Methodology and toolbox for strategic decision making, funded by Vinnova, Sweden’s government agency for innovation.

Other elements of the larger project include:

  • Deliberations by a panel of experts who will convene in a series of live meetings to undertake in-depth analysis on interactions between the goals. 
  • Quanitative analysis of SDG indicators time series data, which will examine historical correlations between progress on the SDGs.
  • Development of a knowledge repository, residing in a new software tool under development as part of the project. This tool will be made available as a resource to guide the decisions of corporate executives, policy makers, and leaders of NGOs.

The overall project was inspired by the work of researchers at the Stockholm Environment Institute, described in Towards systemic and contextual priority setting for implementing the 2030 Agenda, a 2018 paper in Sustainability Science by Nina Weitz, Henrik Carlsen, Måns Nilsson, and Kristian Skånberg….(More)”.

Intellectual Property and Artificial Intelligence


A literature review by the Joint Research Center: “Artificial intelligence has entered into the sphere of creativity and ingenuity. Recent headlines refer to paintings produced by machines, music performed or composed by algorithms or drugs discovered by computer programs. This paper discusses the possible implications of the development and adoption of this new technology in the intellectual property framework and presents the opinions expressed by practitioners and legal scholars in recent publications. The literature review, although not intended to be exhaustive, reveals a series of questions that call for further reflection. These concern the protection of artificial intelligence by intellectual property, the use of data to feed algorithms, the protection of the results generated by intelligent machines as well as the relationship between ethical requirements of transparency and explainability and the interests of rights holders….(More)”.