Chapter by Takeshi Osawa: “Citizen science is one of new paradigms of science. This concept features various project forms, participants, and motivations and implies the need for attention to ethical issues for every participant, which frequently includes nonacademics. In this chapter, I address ethical issues associated with citizen science projects that focus on the data treatment rule and demonstrate a concept on appropriate data policy for these projects. First, I demonstrate that citizen science projects tend to include different types of collaboration, which may lead to certain conflicts among participants in terms of data sharing. Second, I propose an idea that could integrate different types of collaboration according to the theory transcend. Third, I take a case of a citizen science project through which transcend occurred and elucidate the difference between ordinal research and citizen science projects, specifically in terms of the goals of these projects and the goals and motivations of participants, which may change. Finally, I proposed one conceptual idea on how the principal investigator (PI) of a citizen science project can establish data policy after assessing the rights of participants. The basic idea is the division and organization of the data policy in a hierarchy for the project and for the participants. Data policy is one of the important items for establishing the appropriate methods for citizen science as new style of science. As such, practice and framing related to data policy must be carefully monitored and reflected on…(More)”.
Embracing the Social in Social Science
Article by Jay Lloyd: “In a world where science is inextricably intermixed with society, the social sciences are essential to building trust in the scientific enterprise.
To begin thinking about why all the sciences should embrace the social in social science, I would like to start with cupcakes.
In my research, context is a recurring theme, so let me give you some context for cupcakes as metaphor. A few months ago, when I was asked to respond to an article in this magazine, I wrote: “In the production of science, social scientists can often feel like sprinkles on a cupcake: not essential. Social science is not the egg, the flour, or the sugar. Sprinkles are neither in the batter, nor do they see the oven. Sprinkles are a late addition. No matter the stylistic or aesthetic impact, they never alter the substance of the ‘cake’ in the cupcake.”
In writing these sentences, I was, and still am, hopeful that all kinds of future scientific research will make social science a key component of the scientific “batter” and bake social scientific knowledge, skill, and expertise into twenty-first-century scientific “cupcakes.”
But there are tensions and power differentials in the ways interdisciplinary science can be done. Most importantly, the formation of questions itself is a site of power. The questions we as a society ask science to address both reflect and create the values and power dynamics of social systems, whether the scientific disciplines recognize this influence or not. And some of those knowledge systems do not embrace the importance of insights from the social sciences because many institutions of science work hard to insulate the practice of science from the contingencies of society.
Moving forward, how do we, as researchers, develop questions that not only welcome intellectual variety within the sciences but also embrace the diversity represented in societies? As science continues to more powerfully blend, overlap, and intermix with society, embracing what social science can bring to the entire scientific enterprise is necessary. In order to accomplish these important goals, social concerns must be a key ingredient of the whole cupcake—not an afterthought, or decoration, but among the first thoughts…(More)”
Multi-disciplinary Perspectives on Citizen Science—Synthesizing Five Paradigms of Citizen Involvement
Paper by Susanne Beck, Dilek Fraisl, Marion Poetz and Henry Sauermann: “Research on Open Innovation in Science (OIS) investigates how open and collaborative practices influence the scientific and societal impact of research. Since 2019, the OIS Research Conference has brought together scholars and practitioners from diverse backgrounds to discuss OIS research and case examples. In this meeting report, we describe four session formats that have allowed our multi-disciplinary community to have productive discussions around opportunities and challenges related to citizen involvement in research. However, these sessions also highlight the need for a better understanding of the underlying rationales of citizen involvement in an increasingly diverse project landscape. Building on the discussions at the 2023 and prior editions of the conference, we outline a conceptual framework of five crowd paradigms and present an associated tool that can aid in understanding how citizen involvement in particular projects can help advance science. We illustrate this tool using cases presented at the 2023 conference, and discuss how it can facilitate discussions at future conferences as well as guide future research and practice in citizen science…(More)”.
Handbook on Public Policy and Artificial Intelligence
Book edited by Regine Paul, Emma Carmel and Jennifer Cobbe: “…explores the relationship between public policy and artificial intelligence (AI) technologies across a broad range of geographical, technical, political and policy contexts. It contributes to critical AI studies, focusing on the intersection of the norms, discourses, policies, practices and regulation that shape AI in the public sector.
Expert authors in the field discuss the creation and use of AI technologies, and how public authorities respond to their development, by bringing together emerging scholarly debates about AI technologies with longer-standing insights on public administration, policy, regulation and governance. Contributions in the Handbook mobilize diverse perspectives to critically examine techno-solutionist approaches to public policy and AI, dissect the politico-economic interests underlying AI promotion and analyse implications for sustainable development, fairness and equality. Ultimately, this Handbook questions whether regulatory concepts such as ethical, trustworthy or accountable AI safeguard a democratic future or contribute to a problematic de-politicization of the public sector…(More)”.
How to optimize the systematic review process using AI tools
Paper by Nicholas Fabiano et al: “Systematic reviews are a cornerstone for synthesizing the available evidence on a given topic. They simultaneously allow for gaps in the literature to be identified and provide direction for future research. However, due to the ever-increasing volume and complexity of the available literature, traditional methods for conducting systematic reviews are less efficient and more time-consuming. Numerous artificial intelligence (AI) tools are being released with the potential to optimize efficiency in academic writing and assist with various stages of the systematic review process including developing and refining search strategies, screening titles and abstracts for inclusion or exclusion criteria, extracting essential data from studies and summarizing findings. Therefore, in this article we provide an overview of the currently available tools and how they can be incorporated into the systematic review process to improve efficiency and quality of research synthesis. We emphasize that authors must report all AI tools that have been used at each stage to ensure replicability as part of reporting in methods….(More)”.
Effects of Open Access. Literature study on empirical research 2010–2021
Paper by David Hopf, Sarah Dellmann, Christian Hauschke, and Marco Tullney: “Open access — the free availability of scholarly publications — intuitively offers many benefits. At the same time, some academics, university administrators, publishers, and political decision-makers express reservations. Many empirical studies on the effects of open access have been published in the last decade. This report provides an overview of the state of research from 2010 to 2021. The empirical results on the effects of open access help to determine the advantages and disadvantages of open access and serve as a knowledge base for academics, publishers, research funding and research performing institutions, and policy makers. This overview of current findings can inform decisions about open access and publishing strategies. In addition, this report identifies aspects of the impact of open access that are potentially highly relevant but have not yet been sufficiently studied…(More)”.
Artificial Intelligence Applications for Social Science Research
Report by Megan Stubbs-Richardson et al: “Our team developed a database of 250 Artificial Intelligence (AI) applications useful for social science research. To be included in our database, the AI tool had to be useful for: 1) literature reviews, summaries, or writing, 2) data collection, analysis, or visualizations, or 3) research dissemination. In the database, we provide a name, description, and links to each of the AI tools that were current at the time of publication on September 29, 2023. Supporting links were provided when an AI tool was found using other databases. To help users evaluate the potential usefulness of each tool, we documented information about costs, log-in requirements, and whether plug-ins or browser extensions are available for each tool. Finally, as we are a team of scientists who are also interested in studying social media data to understand social problems, we also documented when the AI tools were useful for text-based data, such as social media. This database includes 132 AI tools that may have use for literature reviews or writing; 146 tools that may have use for data collection, analyses, or visualizations; and 108 that may be used for dissemination efforts. While 170 of the AI tools within this database can be used for general research purposes, 18 are specific to social media data analyses, and 62 can be applied to both. Our database thus offers some of the recently published tools for exploring the application of AI to social science research…(More)”
Societal interaction plans—A tool for enhancing societal engagement of strategic research in Finland
Paper by Kirsi Pulkkinen, Timo Aarrevaara, Mikko Rask, and Markku Mattila: “…we investigate the practices and capacities that define successful societal interaction of research groups with stakeholders in mutually beneficial processes. We studied the Finnish Strategic Research Council’s (SRC) first funded projects through a dynamic governance lens. The aim of the paper is to explore how the societal interaction was designed and commenced at the onset of the projects in order to understand the logic through which the consortia expected broad impacts to occur. The Finnish SRC introduced a societal interaction plan (SIP) approach, which requires research consortia to consider societal interaction alongside research activities in a way that exceeds conventional research plans. Hence, the first SRC projects’ SIPs and the implemented activities and working logics discussed in the interviews provide a window into exploring how active societal interaction reflects the call for dynamic, sustainable practices and new capabilities to better link research to societal development. We found that the capacities of dynamic governance were implemented by integrating societal interaction into research, in particular through a ‘drizzling’ approach. In these emerging practices SIP designs function as platforms for the formation of communities of experts, rather than traditional project management models or mere communication tools. The research groups utilized the benefits of pooling academic knowledge and skills with other types of expertise for mutual gain. They embraced the limits of expertise and reached out to societal partners to truly broker knowledge, and exchange and develop capacities and perspectives to solve grand societal challenges…(More)”.
Will we run out of data? Limits of LLM scaling based on human-generated data
Paper by Pablo Villalobos: We investigate the potential constraints on LLM scaling posed by the availability of public human-generated text data. We forecast the growing demand for training data based on current trends and estimate the total stock of public human text data. Our findings indicate that if current LLM development trends continue, models will be trained on datasets roughly equal in size to the available stock of public human text data between 2026 and 2032, or slightly earlier if models are overtrained. We explore how progress in language modeling can continue when human-generated text datasets cannot be scaled any further. We argue that synthetic data generation, transfer learning from data-rich domains, and data efficiency improvements might support further progress…(More)”.
Japan’s push to make all research open access is taking shape
Article by Dalmeet Singh Chawla: “The Japanese government is pushing ahead with a plan to make Japan’s publicly funded research output free to read. In June, the science ministry will assign funding to universities to build the infrastructure needed to make research papers free to read on a national scale. The move follows the ministry’s announcement in February that researchers who receive government funding will be required to make their papers freely available to read on the institutional repositories from April 2025.
The Japanese plan “is expected to enhance the long-term traceability of research information, facilitate secondary research and promote collaboration”, says Kazuki Ide, a health-sciences and public-policy scholar at Osaka University in Suita, Japan, who has written about open access in Japan.
The nation is one of the first Asian countries to make notable advances towards making more research open access (OA) and among the first countries in the world to forge a nationwide plan for OA.
The plan follows in the footsteps of the influential Plan S, introduced six years ago by a group of research funders in the United States and Europe known as cOAlition S, to accelerate the move to OA publishing. The United States also implemented an OA mandate in 2022 that requires all research funded by US taxpayers to be freely available from 2026…(More)”.