Sep 2026· Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)
Abstract
This developmental paper offers methodological musings at the point when we want to embark on a journey of empirically researching a philosophically complex and methodologically elusive concept: connoisseurship. The three authors are interested in connoisseurship for different reasons and thus from different perspectives: (1) the role of connoisseurship in developing mastery, (2) the role of connoisseurship in eminent creativity, and (3) the relationships between connoisseurship and authenticity. We believe that there is strength in this variety and we intend to undertake an empirical journey together albeit possibly finishing it with different insights. To frame our research, we have agreed about the philosophical positioning, and the main characteristics of the research design (strategy). Now we want to figure out how to collect the richest possible data, and while working on this manuscript, we managed to come up with a plausible approach. For analysing the data, we are playing with the idea of making use of AI, but not general-purpose generative AI, and not usual software tools for qualitative analyses tuned up with AI: we found an approach and tool that builds an AI tool from the ground up to conduct conversational qualitative data analysis. At this conference we hope to expose our ideas for data collection and analysis to friendly but thorough scrutiny and have engaging debates regarding the path forward.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduSep 16, 2026