Paper by Alessandro Narduzzo and Valentina Forrer: “Failure, even in the context of innovation, is primarily conceived and experienced as an inevitable (e.g., innovation funnel) or unintended (e.g., unexpected drawbacks) outcome. This paper aims to provide a more systematic understanding of innovation failure by considering and problematizing the case of “intelligent failures”, namely experiments that are intentionally designed and implemented to explore technological and market uncertainty. We conceptualize intelligent failure through an epistemic perspective that recognizes its contribution to challenging and revising the organizational knowledge system. We also outline an original process model of intelligent failure that fully reveals its potential and distinctiveness in the context of learning from failure (i.e., failure as an outcome vs failure of expectations and initial beliefs), analyzing and comparing intended and unintended innovation failures. By positioning intelligent failure in the context of innovation and explaining its critical role in enhancing the ability of innovative firms to achieve breakthroughs, we identify important landmarks for practitioners in designing an intelligent failure approach to innovation…(More)”.
Artificial intelligence for modelling infectious disease epidemics
Paper by Moritz U. G. Kraemer et al: “Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI…(More)”.
A Roadmap to Accessing Mobile Network Data for Statistics
Guide by Global Partnership for Sustainable Development Data: “… introduces milestones on the path to mobile network data access. While it is aimed at stakeholders in national statistical systems and across national governments in general, the lessons should resonate with others seeking to take this route. The steps in this guide are written in the order in which they should be taken, and some readers who have already embarked on this journey may find they have completed some of these steps.
This roadmap is meant to be followed in steps, and readers may start, stop, and return to points on the path at any point.
The path to mobile network data access has three milestones:
- Evaluating the opportunity – setting clear goals for the desired impact of data innovation.
- Engaging with stakeholders – getting critical stakeholders to support your cause.
- Executing collaboration agreements – signing a written agreement among partners…(More)”
Moving Toward the FAIR-R principles: Advancing AI-Ready Data
Paper by Stefaan Verhulst, Andrew Zahuranec and Hannah Chafetz: “In today’s rapidly evolving AI ecosystem, making data ready for AI-optimized for training, fine-tuning, and augmentation-is more critical than ever. While the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) have guided data management and open science, they do not inherently address AI-specific needs. Expanding FAIR to FAIR-R, incorporating Readiness for AI, could accelerate the responsible use of open data in AI applications that serve the public interest. This paper introduces the FAIR-R framework and identifies current efforts for enhancing AI-ready data through improved data labeling, provenance tracking, and new data standards. However, key challenges remain: How can data be structured for AI without compromising ethics? What governance models ensure equitable access? How can AI itself be leveraged to improve data quality? Answering these questions is essential for unlocking the full potential of AI-driven innovation while ensuring responsible and transparent data use…(More)”.
Announcing the Youth Engagement Toolkit for Responsible Data Reuse: An Innovative Methodology for the Future of Data-Driven Services
Blog by Elena Murray, Moiz Shaikh, and Stefaan G. Verhulst: “Young people seeking essential services — whether mental health support, education, or government benefits — often face a critical challenge: they are asked to share their data without having a say in how it is used or for what purpose. While the responsible use of data can help tailor services to better meet their needs and ensure that vulnerable populations are not overlooked, a lack of trust in data collection and usage can have the opposite effect.
When young people feel uncertain or uneasy about how their data is being handled, they may adopt privacy-protective behaviors — choosing not to seek services at all or withholding critical information out of fear of misuse. This risks deepening existing inequalities rather than addressing them.
To build trust, those designing and delivering services must engage young people meaningfully in shaping data practices. Understanding their concerns, expectations, and values is key to aligning data use with their preferences. But how can this be done effectively?
This question was at the heart of a year-long global collaboration through the NextGenData project, which brought together partners worldwide to explore solutions. Today, we are releasing a key deliverable of that project: The Youth Engagement Toolkit for Responsible Data Reuse:
Based on a methodology developed and piloted during the NextGenData project, the Toolkit describes an innovative methodology for engaging young people on responsible data reuse practices, to improve services that matter to them…(More)”.
International Guidelines on People Centred Smart Cities
UN-Habitat: “…The guidelines aim to support national, regional and local governments, as well as relevant stakeholders, in leveraging digital technology for a better quality of life in cities and human settlements, while mitigating the associated risks to achieve global visions of sustainable urban development, in line with the New Urban Agenda, the 2030 Agenda for Sustainable Development and other relevant global agendas.
The aim is to promote a people-centred smart cities approach that is consistent with the purpose and the principles of the Charter of the United Nations, including full respect for international law and the Universal Declaration of Human Rights, to ensure that innovation and digital technologies are used to help cities and human settlements in order to achieve the Sustainable Development Goals and the New Urban Agenda.
The guidelines serve as a reference for Member States to implement people-centred smart city approaches in the preparation and implementation of smart city regulations, plans and strategies to promote equitable access to, and life-long education and training of all people in, the opportunities provided by data, digital infrastructure and digital services in cities and human settlements, and to favour transparency and accountability.
The guidelines recognize local and regional governments (LRGs) as pivotal actors in ensuring closing digital divides and localizing the objectives and principles of these guidelines as well as the Global Digital Compact for an open, safe, sustainable and secure digital future. The guidelines are intended to complement existing global principles on digital development through a specific additional focus on the key role of local and regional governments, and local action, in advancing people-centred smart city development also towards the vision of global digital compact…(More)”.
Presenting the StanDat database on international standards: improving data accessibility on marginal topics
Article by Solveig Bjørkholt: “This article presents an original database on international standards, constructed using modern data gathering methods. StanDat facilitates studies into the role of standards in the global political economy by (1) being a source for descriptive statistics, (2) enabling researchers to assess scope conditions of previous findings, and (3) providing data for new analyses, for example the exploration of the relationship between standardization and trade, as demonstrated in this article. The creation of StanDat aims to stimulate further research into the domain of standards. Moreover, by exemplifying data collection and dissemination techniques applicable to investigating less-explored subjects in the social sciences, it serves as a model for gathering, systematizing, and sharing data in areas where information is plentiful yet not readily accessible for research…(More)”.
Disinformation: Definitions and examples
Explainer by Perthusasia Centre: “Disinformation has been a tool of manipulation and control for centuries, from ancient military strategies to Cold War propaganda. With the rapid advancement of technology,
it has evolved into a sophisticated and pervasive security threat that transcends traditional boundaries.
This explainer takes the definitions and examples from our recent Indo-Pacific Analysis Brief, Disinformation and cognitive warfare by Senior Fellow Alana Ford, and creates an simple, standalone guide for quick reference…(More)”.
Diversifying Professional Roles in Data Science
Policy Briefing by Emma Karoune and Malvika Sharan: The interdisciplinary nature of the data science workforce extends beyond the traditional notion of a “data scientist.” A successful data science team requires a wide range of technical expertise, domain knowledge and leadership capabilities. To strengthen such a team-based approach, this note recommends that institutions, funders and policymakers invest in developing and professionalising diverse roles, fostering a resilient data science ecosystem for the future.
By recognising the diverse specialist roles that collaborate within interdisciplinary teams, organisations can leverage deep expertise across multiple skill sets, enhancing responsible decision-making and fostering innovation at all levels. Ultimately, this note seeks to shift the perception of data science professionals from the conventional view of individual data scientists to a competency-based model of specialist roles within a team, each essential to the success of data science initiatives…(More)”.
GeoTechnoGraphy: Mapping Power and Identity in the Digital Age
Book by Samir Saran and Anirban Sarma: “In an era defined by rapid technological change, a seismic shift is underway. From the rise of digital platforms that mediate our interactions—with markets, with governments and perhaps most importantly with each other as citizens— to the growing tension between our online personas and our real-world identities, the forces of technology, geography and society are colliding in ways we are only beginning to understand.
Even as technology opens up new opportunities for civic engagement, it simultaneously disrupts the very foundations of societal cohesion. The digital age has given rise to a new stage for global drama—one where surveillance, the weaponization of information and the erosion of trust in national and multilateral institutions are playing out in real time. But as these forces evolve, so too must our understanding of how individuals and societies can navigate them.
Will digital societies endure, or are they doomed to collapse under the weight of their own contradictions? Can democracy as we know it survive in a world where power is increasingly concentrated in the hands of a few tech giants? And as nations grapple with the changing dynamics of governance, how will international norms, laws and institutions adapt?
In GeoTechnoGraphy, Samir Saran and Anirban Sarma offer a compelling analysis of the forces reshaping the modern world. Drawing on groundbreaking research and incisive insights, they examine how the convergence of geography and technology—geotechnography—is redefining power and writing new rules for its exercise…(More)”