The use of algorithmic tools by journalists for information-gathering has received particular attention in recent years. While it might facilitate the research process, there are also concerns about their impact on journalism. Based on reconstruction interviews with 27 journalists, we first answer the primary question to what extent journalists actually use algorithmic-driven tools for research purposes. Then, we analyze which folk theories journalists create during their use of algorithm-driven tools. Results show that algorithmic tools specifically designed for the journalistic research process are rarely or not at all used. Yet, more crucially,search engines and social media, that are driven by algorithms,play a major role when it comes to the search, selection, and verification of sources and information. However, journalists are notaware of this hidden research assistant facilitating their research process. When explicitly asked, they profess specific notions regarding the use of algorithmic-driven tools in the form of folk theories, which are predominantly negative regarding the influence of AI on journalism. At the same time, there is a still a strong feeling of a professional authority among journalists who feel they are able to work autonomously of any kind of influence,including algorithms.
The idea that technologies influence society—both positively and negatively—is not new. This is mainly the terrain of the philosophy and the ethics of technolo-gy research. Similarly, design research aims to help create new technologies in line with individual, social, and societal needs and values. Against this backdrop, it seems essential to expose relations between design and philosophy of tech-nology research, particularly from a methodological perspective. The main goal of this paper is to suggest a preliminary overview of methods and approaches that can inspire and inform interdisciplinary collaboration and, with that, sys-tematic engagement with ethics in design processes. Through interdisciplinary exchange, we propose a preliminary typology of ethics-informed methods and approaches based on two main dimensions, namely theory-grounded approaches to theoretically-flexible techniques and assessment to accompaniment. This mapping intends to help navigate the ethical qualities of selected methods from both disciplines, and it aims to create a platform for fruitful interdisciplinary conversations.
MULTIFILE
The idea that technologies influence society—both positively and negatively—is not new. This is mainly the terrain of the philosophy and the ethics of technolo-gy research. Similarly, design research aims to help create new technologies in line with individual, social, and societal needs and values. Against this backdrop, it seems essential to expose relations between design and philosophy of tech-nology research, particularly from a methodological perspective. The main goal of this paper is to suggest a preliminary overview of methods and approaches that can inspire and inform interdisciplinary collaboration and, with that, sys-tematic engagement with ethics in design processes. Through interdisciplinary exchange, we propose a preliminary typology of ethics-informed methods and approaches based on two main dimensions, namely theory-grounded approaches to theoretically-flexible techniques and assessment to accompaniment. This mapping intends to help navigate the ethical qualities of selected methods from both disciplines, and it aims to create a platform for fruitful interdisciplinary conversations.
MULTIFILE
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
