Article by Daniel J. Finkenstadt et al: “Businesses are increasingly leveraging strategic foresight and scenario planning to navigate uncertainties stemming from climate change, global conflicts, and technological advancements. Traditional methods, however, struggle with identifying key trends, exploring multiple scenarios, and providing actionable guidance. Generative AI offers a robust alternative, enabling rapid, cost-effective, and comprehensive contingency planning. This AI-driven approach enhances scenario creation, narrative exploration, and strategy generation, providing detailed, adaptable strategies rather than conclusive solutions. This approach demands accurate, relevant data and encourages iterative refinement, transforming how organizations forecast and strategize for the future…(More)”.
Atlas of Intangibles
About: “Atlas of Intangibles is a data experience designed to highlight the rich, interconnected web of sensory information that lies beneath our everyday encounters. Showcasing sensory data collected by me around the city of London through score-based data walks, the digital experience allows viewers to choose specific themes and explore related data as views — journeys, connections, and typologies. Each data point is rich in context, encompassing images and audio recordings…(More)”.
The future of agricultural data-sharing policy in Europe: stakeholder insights on the EU Code of Conduct
Paper by Mark Ryan, Can Atik, Kelly Rijswijk, Marc-Jeroen Bogaardt, Eva Maes & Ella Deroo: “n 2018, the EU Code of Conduct of Agricultural Data Sharing by Contractual Agreement (EUCC) was published. This voluntary initiative is considered a basis for rights and responsibilities for data sharing in the agri-food sector, with a specific farmer orientation. While the involved industry associations agreed on its content, there are limited insights into how and to what extent the EUCC has been received and implemented within the sector. In 2024, the Data Act was introduced, a horizontal legal framework that aims to enforce specific legal requirements for data sharing across sectors. Yet, it remains to be seen if it will be the ultimate solution for the agricultural sector, as some significant agricultural data access issues remain. It is thus essential to determine if the EUCC may still play a significant role to address sector-specific issues in line with the horizontal rules of the Data Act. During six workshops across Europe with 89 stakeholders, we identified how the EUCC has been (1) received by stakeholders, (2) implemented, and (3) its future use (particularly in response to the Data Act). Based on the workshop results and continued engagements with researchers and stakeholders, we conclude that the EUCC is still an important document for the agricultural sector but should be updated in response to the content of the Data Act. Hence we propose the following improvements to the EUCC: 1. Provide clear, practical examples for applying the EUCC combined with the Data Act; 2. Generate model contractual terms based on the EUCC provisions; 3. Clarify GDPR-centric concepts like anonymisation and pseudonymisation in the agricultural data-sharing setting; 4. Develop a functional enforcement and implementation framework; and 5. Play a role in increasing interoperability and trust among stakeholders…(More)”
Chasing Shadows: Cyber Espionage, Subversion, and the Global Fight for Democracy
Book by Ronald Deibert: “In this real-life spy thriller, cyber security expert Ronald Deibert details the unseemly marketplace for high-tech surveillance, professional disinformation, and computerized malfeasance. He reveals how his team of digital sleuths at the Citizen Lab have lifted the lid on dozens of covert operations targeting innocent citizens everywhere.
Chasing Shadows provides a front-row seat to a dark underworld of digital espionage, disinformation, and subversion. There, autocrats and dictators peer into their targets’ lives with the mere press of a button, spreading their tentacles of authoritarianism through a digital ecosystem that is insecure, poorly regulated, and prone to abuse. The activists, opposition figures, and journalists who dare to advocate for basic political rights and freedoms are hounded, arrested, tortured, and sometimes murdered.
From the gritty streets of Guatemala City to the corridors of power in the White House, this compelling narrative traces the journey of the Citizen Lab as it evolved into a globally renowned source of counterintelligence for civil society. As this small team of investigators disarmed cyber mercenaries and helped to improve the digital security of billions of people worldwide, their success brought them, too, into the same sinister crosshairs that plagued the victims they worked to protect.
Deibert recounts how the Lab exposed the world’s pre-eminent cyber-mercenary firm, Israel-based NSO Group—the creators of the phone-hacking marvel Pegasus—in a series of human rights abuses, from domestic spying scandals in Spain, Poland, Hungary, and Greece to its implication in the murder of Washington Post journalist Jamal Khashoggi in 2018…(More)”
Making the Global Digital Compact a reality: Four steps to establish a responsible, inclusive and equitable data future.
Article by Stefaan Verhulst: “In September of this year, as world leaders assemble in New York for the 78th annual meeting of the United Nations (UN) General Assembly, they will confront a weighty agenda. War and peace will be at the forefront of conversations, along with efforts to tackle climate change and the ongoing migration crisis. Alongside these usual topics, however, the gathered dignitaries will also turn their attention to digital governance.
In 2021, the UN Secretary General proposed that a Global Digital Compact (GDC) be agreed upon that would “outline shared principles for an open, free and secure digital future for all”. The development of this Compact, which builds on a range of adjacent work streams at the UN, including activities related to the Sustainable Development Goals (SDGs), has now reached a vital inflection point. After a wide-ranging process of consultation, the General Assembly is expected to ratify the latest draft of the Digital Compact, which contains five key objectives and a commitment to thirteen cross-cutting principles. We have reached a rare moment of near-consensus in the global digital ecosystem, one that offers undeniable potential for revamping (and improving) our frameworks for global governance.
The Global Digital Compact will be agreed upon by UN Member States at the Summit of the Future at the United Nations Headquarters in New York, establishing guidelines for the responsible use and governance of digital technologies.
The growing prominence of these objectives and principles at the seat of global governance is a welcome development. Each is essential to developing a healthy, safe and responsible digital ecosystem. In particular, the emphasis on better data governance is a step forward, as is the related call for an enhanced approach for international AI governance. Both cannot be separated: data governance is the bedrock of AI governance.
Yet now that we are moving toward ratification of the Compact, we must focus on the next crucial—and in some ways most difficult – step: implementation. This is particularly important given that the digital realm faces in many ways a growing crisis of credibility, marked by growing concerns over exclusion, extraction, concentrations of power, mis- and disinformation, and what we have elsewhere referred to as an impending “data winter”.
Manifesting the goals of the Compact to create genuine and lasting impact is thus critical. In what follows, we explore four key ways in which the Compact’s key objectives can be operationalized to create a more vibrant, responsive and free global digital commons…(More)”.
We finally have a definition for open-source AI
Article by Rhiannon Williams and James O’Donnell: “Open-source AI is everywhere right now. The problem is, no one agrees on what it actually is. Now we may finally have an answer. The Open Source Initiative (OSI), the self-appointed arbiters of what it means to be open source, has released a new definition, which it hopes will help lawmakers develop regulations to protect consumers from AI risks.
Though OSI has published much about what constitutes open-source technology in other fields, this marks its first attempt to define the term for AI models. It asked a 70-person group of researchers, lawyers, policymakers, and activists, as well as representatives from big tech companies like Meta, Google, and Amazon, to come up with the working definition.
According to the group, an open-source AI system can be used for any purpose without the need to secure permission, and researchers should be able to inspect its components and study how the system works.
It should also be possible to modify the system for any purpose—including to change its output—and to share it with others to use, with or without modifications, for any purpose. In addition, the standard attempts to define a level of transparency for a given model’s training data, source code, and weights.
The previous lack of an open-source standard presented a problem…(More)”.
It’s time we put agency into Behavioural Public Policy
Article by Sanchayan Banerjee et al: “Promoting agency – people’s ability to form intentions and to act on them freely – must become a primary objective for Behavioural Public Policy (BPP). Contemporary BPPs do not directly pursue this objective, which is problematic for many reasons. From an ethical perspective, goals like personal autonomy and individual freedom cannot be realised without nurturing citizens’ agency. From an efficacy standpoint, BPPs that override agency – for example, by activating automatic psychological processes – leave citizens ‘in the dark’, incapable of internalising and owning the process of behaviour change. This may contribute to non-persistent treatment effects, compensatory negative spillovers or psychological reactance and backfiring effects. In this paper, we argue agency-enhancing BPPs can alleviate these ethical and efficacy limitations to longer-lasting and meaningful behaviour change. We set out philosophical arguments to help us understand and conceptualise agency. Then, we review three alternative agency-enhancing behavioural frameworks: (1) boosts to enhance people’s competences to make better decisions; (2) debiasing to encourage people to reduce the tendency for automatic, impulsive responses; and (3) nudge+ to enable citizens to think alongside nudges and evaluate them transparently. Using a multi-dimensional framework, we highlight differences in their workings, which offer comparative insights and complementarities in their use. We discuss limitations of agency-enhancing BPPs and map out future research directions…(More)”.
The Complexities of Differential Privacy for Survey Data
Paper by Jörg Drechsler & James Bailie: “The concept of differential privacy (DP) has gained substantial attention in recent years, most notably since the U.S. Census Bureau announced the adoption of the concept for its 2020 Decennial Census. However, despite its attractive theoretical properties, implementing DP in practice remains challenging, especially when it comes to survey data. In this paper we present some results from an ongoing project funded by the U.S. Census Bureau that is exploring the possibilities and limitations of DP for survey data. Specifically, we identify five aspects that need to be considered when adopting DP in the survey context: the multi-staged nature of data production; the limited privacy amplification from complex sampling designs; the implications of survey-weighted estimates; the weighting adjustments for nonresponse and other data deficiencies, and the imputation of missing values. We summarize the project’s key findings with respect to each of these aspects and also discuss some of the challenges that still need to be addressed before DP could become the new data protection standard at statistical agencies…(More)”.
Artificial Intelligence for the Internal Democracy of Political Parties
Paper by Claudio Novelli et al: “The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, can improve the measurement and practice of IPD…(More)”.
Align or fail: How economics shape successful data sharing
Blog by Federico Bartolomucci: “…The conceptual distinctions between different data sharing models are mostly based on one fundamental element: the economic nature of data and its value.
Open data projects operate under the assumption that data is a non-rival (i.e. can be used by multiple people at the same time) and a non-excludable asset (i.e. anyone can use it, similar to a public good like roads or the air we breathe). This means that data can be shared with everyone, for any use, without losing its market and competitive value. The Humanitarian Data Exchange platform is a great example that allows organizations to share over 19,000 open data sets on all aspects of humanitarian response with others.
Data collaboratives treat data as an excludable asset that some people may be excluded from accessing (i.e. a ‘club good’, like a movie theater) and therefore share it only among a restricted pool of actors. At the same time, they overcome the rival nature of this data set up by linking its use to a specific purpose. These work best by giving the actors a voice in choosing the purpose for which the data will be used, and through specific agreements and governance bodies that ensure that those contributing data will not have their competitive position harmed, therefore incentivizing them to engage. A good example of this is the California Data Collaborative, which uses data from different actors in the water sector to develop high-level analysis on water distribution to guide policy, planning, and operations for water districts in the state of California.
Data ecosystems work by activating market mechanisms around data exchange to overcome reluctance to share data, rather than relying solely on its purpose of use. This means that actors can choose to share their data in exchange for compensation, be it monetary or in alternate forms such as other data. In this way, the compensation balances the potential loss of competitive advantage created by the sharing of a rival asset, as well as the costs and risks of sharing. The Enershare initiative aims to establish a marketplace utilizing blockchain and smart contracts to facilitate data exchange in the energy sector. The platform is based on a compensation system, which can be non-monetary, for exchanging assets and resources related to data (such as datasets, algorithms, and models) with energy assets and services (like heating system maintenance or the transfer of surplus locally self-produced energy).
These different models of data sharing have different operational implications…(More)”.