AI is a transformative force in the digital age. The swift rise of generative AI technology, particularly with ChatGPT launched in Nov 2022, has sparked global interest. We hold technology to be best understood as a quasi-social movement that is mobilising symbolic and material resources for societal change. We are tracing this mobilisation effort for AI on three variables: the flow of media salience and shifts in topicality and public awareness. Over the period 2000-2023, the paper traces the salience of AI relative to other tech issues such as nuclear power, genetics and climate change. For the period 2015-2023 we analyse key themes and public awareness of AI and how they shift over time. Results show similarities and differences between the UK and Korea, reflecting the different impact of two landmark events. While AlphaGo 2016 shocked Korea into FOMO, fear of the Nation missing out on new technology, ChatGPT 2023 alarmed the UK about TOOC, a potential technology-out-of-control. The paper shows how 2015-2023 is likely to be another hype cycle of AI coming to a turning point. AI is a global challenge but played out to local logic. The AI challenge is confronted with different dispositions in the UK and in Korea despite similar geo-political positions on AI.
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