Paper by Nathan Schneider: “…outlines a theory of amnesia in the face of innovation: when apparent technological innovations occasion the disregard of preexisting cultural, legal, and infrastructural norms. Innovation amnesia depends on cultural patterns that appear to be increasingly widespread: the valorization of technological innovation and the sensation of limited political space for reforming social arrangements. The resulting amnesia is by default an extension of existing structural inequalities. If innovations arise through deploying concentrated private wealth, the amnesia will likely target institutions that facilitate collective power among less powerful people. Up and down social hierarchies, however, achieving amnesia through innovation can bear irresistible allure. When other paths for structural change become mired in inertia or gridlock, amnesia may appear to be the only available pathway to reform. The purpose of a theory of amnesia is to assist affected communities in noticing it when it occurs and wielding it to their advantage, particularly through mobilizing self-governance around moments of innovation…(More)”.
The Rise of AI-Generated Content in Wikipedia
Paper by Creston Brooks, Samuel Eggert, and Denis Peskoff: “The rise of AI-generated content in popular information sources raises significant concerns about accountability, accuracy, and bias amplification. Beyond directly impacting consumers, the widespread presence of this content poses questions for the long-term viability of training language models on vast internet sweeps. We use GPTZero, a proprietary AI detector, and Binoculars, an open-source alternative, to establish lower bounds on the presence of AI-generated content in recently created Wikipedia pages. Both detectors reveal a marked increase in AI-generated content in recent pages compared to those from before the release of GPT-3.5. With thresholds calibrated to achieve a 1% false positive rate on pre-GPT-3.5 articles, detectors flag over 5% of newly created English Wikipedia articles as AI-generated, with lower percentages for German, French, and Italian articles. Flagged Wikipedia articles are typically of lower quality and are often self-promotional or partial towards a specific viewpoint on controversial topics…(More)”
AI and Data Science for Public Policy
Introduction to Special Issue by Kenneth Benoit: “Artificial intelligence (AI) and data science are reshaping public policy by enabling more data-driven, predictive, and responsive governance, while at the same time producing profound changes in knowledge production and education in the social and policy sciences. These advancements come with ethical and epistemological challenges surrounding issues of bias, transparency, privacy, and accountability. This special issue explores the opportunities and risks of integrating AI into public policy, offering theoretical frameworks and empirical analyses to help policymakers navigate these complexities. The contributions explore how AI can enhance decision-making in areas such as healthcare, justice, and public services, while emphasising the need for fairness, human judgment, and democratic accountability. The issue provides a roadmap for harnessing AI’s potential responsibly, ensuring it serves the public good and upholds democratic values…(More)”.
Federated Data Infrastructures for Scientific Use
Policy paper by the German Council for Scientific Information Infrastructures: “…provides an overview and a comparative in-depth analysis of the emerging research (and research related) data infrastructures NFDI, EOSC, Gaia-X and the European Data Spaces. In addition, the Council makes recommendations for their future development and coordination. The RfII notes that access to genuine high-quality research data and related core services is a matter of basic public supply and strongly advises to achieve coherence between the various initiatives and approaches…(More)”.
Information Technology for Peace and Security
Book edited by Christian Reuter: “Technological and scientific progress, especially the rapid development in information technology (IT) and artificial intelligence (AI), plays a crucial role regarding questions of peace and security. This textbook, extended and updated in its second edition, addresses the significance, potential of IT, as well as the challenges it poses, with regard to peace and security.
It introduces the reader to the concepts of peace, conflict, and security research, especially focusing on natural, technical and computer science perspectives. In the following sections, it sheds light on cyber conflicts, war and peace, cyber arms control, cyber attribution, infrastructures, artificial intelligence, as well ICT in peace and conflict…(More)”.
Lottocracy: Democracy Without Elections
Book by Alexander Guerrero: “Democracy is in trouble. The system isn’t working. Inequality increases, many can barely get by, the elite control our political institutions. The earth, our only home, gets warmer year by year. We are deeply divided, unable to work together to address the problems we face. What if elections are the problem?
Lottocracy makes the case that electoral representative democracy—although the best form of government that has been tried—runs into deep problems in the modern world.
But it is not a message of despair. To the contrary. Lottocracy sets out a detailed vision of a new kind of democracy, as system that uses lotteries, rather than elections, to select our political representatives.
Perhaps we can use this wild ancient idea to build a new, better democracy for the 21st century and beyond…(More)”.
Critical Datafication Literacy
Book by Ina Sander: “Despite the increasing influence of data technologies on our world, many people still lack a profound understanding of what this ›datafication‹ means for their lives and our societies. Ina Sander argues that this knowledge gap cannot be addressed by digital skills alone, but that more critical and empowering approaches are needed. Through a review of existing literacies, an analysis of established education concepts, and empirical research on online educational resources about datafication, she develops a framework for »critical datafication literacy«. Novel insights on the design strategies, pedagogical methods and challenges of practitioners who foster such education add to her analysis…(More)”.
Inside the New Nonprofit AI Initiatives Seeking to Aid Teachers and Farmers in Rural Africa
Article by Andrew R. Chow: “Over the past year, rural farmers in Malawi have been seeking advice about their crops and animals from a generative AI chatbot. These farmers ask questions in Chichewa, their native tongue, and the app, Ulangizi, responds in kind, using conversational language based on information taken from the government’s agricultural manual. “In the past we could wait for days for agriculture extension workers to come and address whatever problems we had on our farms,” Maron Galeta, a Malawian farmer, told Bloomberg. “Just a touch of a button we have all the information we need.”
The nonprofit behind the app, Opportunity International, hopes to bring similar AI-based solutions to other impoverished communities. In February, Opportunity ran an acceleration incubator for humanitarian workers across the world to pitch AI-based ideas and then develop them alongside mentors from institutions like Microsoft and Amazon. On October 30, Opportunity announced the three winners of this program: free-to-use apps that aim to help African farmers with crop and climate strategy, teachers with lesson planning, and school leaders with administration management. The winners will each receive about $150,000 in funding to pilot the apps in their communities, with the goal of reaching millions of people within two years.
Greg Nelson, the CTO of Opportunity, hopes that the program will show the power of AI to level playing fields for those who previously faced barriers to accessing knowledge and expertise. “Since the mobile phone, this is the biggest democratizing change that we have seen in our lifetime,” he says…(More)”.
The Routledge Handbook of Artificial Intelligence and Philanthropy
Open Access Book edited by Giuseppe Ugazio and Milos Maricic: “…acts as a catalyst for the dialogue between two ecosystems with much to gain from collaboration: artificial intelligence (AI) and philanthropy. Bringing together leading academics, AI specialists, and philanthropy professionals, it offers a robust academic foundation for studying both how AI can be used and implemented within philanthropy and how philanthropy can guide the future development of AI in a responsible way.
The contributors to this Handbook explore various facets of the AI‑philanthropy dynamic, critically assess hurdles to increased AI adoption and integration in philanthropy, map the application of AI within the philanthropic sector, evaluate how philanthropy can and should promote an AI that is ethical, inclusive, and responsible, and identify the landscape of risk strategies for their limitations and/or potential mitigation. These theoretical perspectives are complemented by several case studies that offer a pragmatic perspective on diverse, successful, and effective AI‑philanthropy synergies.
As a result, this Handbook stands as a valuable academic reference capable of enriching the interactions of AI and philanthropy, uniting the perspectives of scholars and practitioners, thus building bridges between research and implementation, and setting the foundations for future research endeavors on this topic…(More)”.
Unlocking Green Deal Data: Innovative Approaches for Data Governance and Sharing in Europe
JRC Report: “Drawing upon the ambitious policy and legal framework outlined in the Europe Strategy for Data (2020) and the establishment of common European data spaces, this Science for Policy report explores innovative approaches for unlocking relevant data to achieve the objectives of the European Green Deal.
The report focuses on the governance and sharing of Green Deal data, analysing a variety of topics related to the implementation of new regulatory instruments, namely the Data Governance Act and the Data Act, as well as the roles of various actors in the data ecosystem. It provides an overview of the current incentives and disincentives for data sharing and explores the existing landscape of Data Intermediaries and Data Altruism Organizations. Additionally, it offers insights from a private sector perspective and outlines key data governance and sharing practices concerning Citizen-Generated Data (CGD).
The main conclusions build upon the concept of “Systemic Data Justice,” which emphasizes equity, accountability, and fair representation to foster stronger connections between the supply and demand of data for a more effective and sustainable data economy. Five policy recommendations outline a set of main implications and actionable points for the revision of the INSPIRE Directive (2007) within the context of the common European Green Deal data space, and toward a more sustainable and fair data ecosystem. However, the relevance of these recommendations spills over Green Deal data only, as they outline key elements to ensure that any data ecosystem is both just and impact-oriented…(More)”.