OECD Report: “Cross-border data flows are the lifeblood of today’s social and economic interactions, but they also raise a range of new challenges, including for privacy and data protection, national security, cybersecurity, digital protectionism and regulatory reach. This has led to a surge in regulation conditioning (or prohibiting) its flow or mandating that data be stored or processed domestically (data localisation). However, the economic implications of these measures are not well understood. This report provides estimates on what is at stake, highlighting that full fragmentation could reduce global GDP by 4.5%. It also underscores the benefits associated with open regimes with safeguards which could see global GDP increase by 1.7%. In a world where digital fragmentation is growing, global discussions on these issues can help harness the benefits of an open and safeguarded internet…(More)”.
Sandboxes for AI
Report by Datasphere Initiative: “The Sandboxes for AI report explores the role of regulatory sandboxes in the development and governance of artificial intelligence. Originally presented as a working paper at the Global Sandbox Forum Inaugural Meeting in July 2024, the report was further refined through expert consultations and an online roundtable in December 2024. It examines sandboxes that have been announced, are under development, or have been completed, identifying common patterns in their creation, timing, and implementation. By providing insights into why and how regulators and companies should consider AI sandboxes, the report serves as a strategic guide for fostering responsible innovation.
In a rapidly evolving AI landscape, traditional regulatory processes often struggle to keep pace with technological advancements. Sandboxes offer a flexible and iterative approach, allowing policymakers to test and refine AI governance models in a controlled environment. The report identifies 66 AI, data, or technology-related sandboxes globally, with 31 specifically designed for AI innovation across 44 countries. These initiatives focus on areas such as machine learning, data-driven solutions, and AI governance, helping policymakers address emerging challenges while ensuring ethical and transparent AI development…(More)”.
Recommendations for Better Sharing of Climate Data
Creative Commons: “…the culmination of a nine-month research initiative from our Open Climate Data project. These guidelines are a result of collaboration between Creative Commons, government agencies and intergovernmental organizations. They mark a significant milestone in our ongoing effort to enhance the accessibility, sharing, and reuse of open climate data to address the climate crisis. Our goal is to share strategies that align with existing data sharing principles and pave the way for a more interconnected and accessible future for climate data.
Our recommendations offer practical steps and best practices, crafted in collaboration with key stakeholders and organizations dedicated to advancing open practices in climate data. We provide recommendations for 1) legal and licensing terms, 2) using metadata values for attribution and provenance, and 3) management and governance for better sharing.
Opening climate data requires an examination of the public’s legal rights to access and use the climate data, often dictated by copyright and licensing. This legal detail is sometimes missing from climate data sharing and legal interoperability conversations. Our recommendations suggest two options: Option A: CC0 + Attribution Request, in order to maximize reuse by dedicating climate data to the public domain, plus a request for attribution; and Option B: CC BY 4.0, for retaining data ownership and legal enforcement of attribution. We address how to navigate license stacking and attribution stacking for climate data hosts and for users working with multiple climate data sources.
We also propose standardized human- and machine-readable metadata values that enhance transparency, reduce guesswork, and ensure broader accessibility to climate data. We built upon existing model metadata schemas and standards, including those that address license and attribution information. These recommendations address a gap and provide metadata schema that standardize the inclusion of upfront, clear values related to attribution, licensing and provenance.
Lastly, we highlight four key aspects of effective climate data management: designating a dedicated technical managing steward, designating a legal and/or policy steward, encouraging collaborative data sharing, and regularly revisiting and updating data sharing policies in accordance with parallel open data policies and standards…(More)”.
Net zero: the role of consumer behaviour
Horizon Scan by the UK Parliament: “According to research from the Centre for Climate Change and Social Transformation, reaching net zero by 2050 will require individual behaviour change, particularly when it comes to aviation, diet and energy use.
The government’s 2023 Powering Up Britain: Net Zero Growth Plan referred to low carbon choices as ‘green choices’, and described them as public and businesses choosing green products, services, and goods. The plan sets out six principles regarding policies to facilitate green choices. Both the Climate Change Committee and the House of Lords Environment and Climate Change Committee have recommended that government strategies should incorporate greater societal and behavioural change policies and guidance.
Contributors to the horizon scan identified managing consumer behaviour and habits to help achieve net zero as a topic of importance for parliament over the next five years. Change in consumer behaviour could result in approximately 60% of required emission reductions to reach net zero.[5] Behaviour change will be needed from the wealthiest in society, who according to Oxfam typically lead higher-carbon lifestyles.
Incorporating behavioural science principles into policy levers is a well-established method of encouraging desired behaviours. Common examples of policies aiming to influence behaviour include subsidies, regulation and information campaigns (see below).
However, others suggest deliberative public engagement approaches, such as the UK Climate Change Assembly,[7] may be needed to determine which pro-environmental policies are acceptable.[8] Repeated public engagement is seen as key to achieve a just transition as different groups will need different support to enable their green choices (PN 706).
Researchers debate the extent to which individuals should be responsible for making green choices as opposed to the regulatory and physical environment facilitating them, or whether markets, businesses and governments should be the main actors responsible for driving action. They highlight the need for different actions based on the context and the different ways individuals act as consumers, citizens, and within organisations and groups. Health, time, comfort and status can strongly influence individual decisions while finance and regulation are typically stronger motivations for organisations (PN 714)…(More)”
Network architecture for global AI policy
Article by Cameron F. Kerry, Joshua P. Meltzer, Andrea Renda, and Andrew W. Wyckoff: “We see efforts to consolidate international AI governance as premature and ill-suited to respond to the immense, complex, novel, challenges of governing advanced AI, and the current diverse and decentralized efforts as beneficial and the best fit for this complex and rapidly developing technology.
Exploring the vast terra incognita of AI, realizing its opportunities, and managing its risks requires governance that can adapt and respond rapidly to AI risks as they emerge, develop deep understanding of the technology and its implications, and mobilize diverse resources and initiatives to address the growing global demand for access to AI. No one government or body will have the capacity to take on these challenges without building multiple coalitions and working closely with experts and institutions in industry, philanthropy, civil society, and the academy.
A distributed network of networks can more effectively address the challenges and opportunities of AI governance than a centralized system. Like the architecture of the interconnected information technology systems on which AI depends, such a decentralized system can bring to bear redundancy, resiliency, and diversity by channeling the functions of AI governance toward the most timely and effective pathways in iterative and diversified processes, providing agility against setbacks or failures at any single point. These multiple centers of effort can harness the benefit of network effects and parallel processing.
We explore this model of distributed and iterative AI governance below…(More)”.
Call to make tech firms report data centre energy use as AI booms
Article by Sandra Laville: “Tech companies should be required by law to report the energy and water consumption for their data centres, as the boom in AI risks causing irreparable damage to the environment, experts have said.
AI is growing at a rate unparalleled by other energy systems, bringing heightened environmental risk, a report by the National Engineering Policy Centre (NEPC) said.
The report calls for the UK government to make tech companies submit mandatory reports on their energy and water consumption and carbon emissions in order to set conditions in which data centres are designed to use fewer vital resources…(More)”.
Public Policy Evaluation
Implementation Toolkit by the OECD: “…offers practical guidance for government officials and evaluators seeking to improve their evaluation capacities and systems, by enabling a deeper understanding of their strengths and weaknesses and learning from OECD member country experiences and trends. The toolkit supports the practical implementation of the principles contained in the 2022 OECD Recommendation on Public Policy Evaluation, which is the first international standard aimed at driving the establishment of robust institutions and practices that promote the use of public policy evaluations. Together, the Recommendation and this accompanying toolkit seek to help governments build a culture of continuous learning and evidence-informed policymaking, potentially leading to more impactful policies and greater trust in government action...(More)”.
The new politics of AI
Report by the IPPR: AI is fundamentally different from other technologies – it is set to unleash a vast number of highly sophisticated ‘artificial agents’ into the economy. AI systems that can take actions and make decisions are not just tools – they are actors. This can be a good thing. But it requires a novel type of policymaking and politics. Merely accelerating AI deployment and hoping it will deliver public value will likely be insufficient.
In this briefing, we outline how the summit constitutes the first event of a new era of AI policymaking that links AI policy to delivering public value. We argue that AI needs to be directed towards societies’ goals, via ‘mission-based policies’….(More)”.
Enhancing Access to and Sharing of Data in the Age of Artificial Intelligence
OECD Report: “Artificial intelligence (AI) is transforming economies and societies, but its full potential is hindered by poor access to quality data and models. Based on comprehensive country examples, the OECD report “Enhancing Access to and Sharing of Data in the Age of AI” highlights how governments can enhance access to and sharing of data and certain AI models, while ensuring privacy and other rights and interests such as intellectual property rights. It highlights the OECD Recommendation on Enhancing Access to and Sharing of Data, which provides principles to balance openness while ensuring effective legal, technical and organisational safeguards. This policy brief highlights the key findings of the report and their relevance for stakeholders seeking to promote trustworthy AI through better policies for data and AI models that drive trust, investment, innovation, and well-being….(More)”
Artificial Intelligence for Participation
Policy Brief by the Brazil Centre of the University of Münster: “…provides an overview of current and potential applications of artificial intelligence (AI) technologies in the context of political participation and democratic governance processes in cities. Aimed primarily at public managers, the document also highlights critical issues to consider in the implementation of these technologies, and proposes an agenda for debate on the new state capabilities they require…(More)”.