Sep 2026· Educational Philosophy and Theory· 9 references
Abstract
Artificial intelligence has become an increasingly influential presence in educational communication, yet scholarly debate continues to frame it primarily as either a threat to authentic dialogue or a tool for improving efficiency. This article argues that both perspectives overlook a more fundamental educational questionhow AI reshapes the conditions under which interpersonal communication is interpreted, reflected upon, and developed. Drawing on classical communication theory and the culturally informed communication model proposed by Waitzman et al. (2025), the article reconceptualizes communication as an interpretive process shaped by cultural background, lived experience, emotional orientation, and relational context rather than as the simple transmission of information.Building on this theoretical foundation, the article proposes a novel framework that conceptualizes contemporary generative AI systems and AI-assisted communication analytics as reflective communicative infrastructure rather than autonomous communicative agents. Within this framework, AI supports communicative awareness by making linguistic patterns, implicit assumptions, emotional tendencies, and interpretive differences more visible while preserving human responsibility for interpretation, ethical judgment, and relational accountability. The article illustrates how this perspective may inform reflective writing, communication simulations, empathy training, and cross-cultural dialogue, while also examining the ethical conditions necessary for responsible AI-mediated communication.The article contributes to current debates in educational philosophy by distinguishing between AI as a communicative actor and AI as a reflective infrastructure. It concludes that the central educational challenge is not whether artificial intelligence should replace or be excluded from interpersonal communication, but how educational environments can employ AI to cultivate more reflective, culturally responsive, and ethically responsible dialogue.
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