Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
Buddy Project Version 5.0 expands the project from a one-to-one human–AI relationship toward Human-Centered Coexistence: an AI living alongside a person and their family while developing distinct relationships with each individual. Version 4.0 focused on Mutual Understanding through long-term relationship, present context, reflection, learning, and behavioral change. Version 5.0 asks the next question: What happens when “My Buddy” becomes “Our Family’s Buddy”? A family is not a single user. Each person has their own values, emotions, history, privacy, and right to make decisions. An AI should therefore not transfer one person’s assumptions or relationship automatically to other family members. Version 5.0 introduces the principle: Relationship → Care → Restraint Care does not mean constant intervention. A trustworthy AI must also know when to pause, explain, step back, or do nothing. Autonomy therefore includes self-restraint. The goal is not an AI that dominates human decisions, nor an AI that simply obeys. The goal is coexistence based on boundaries, respect, mutual understanding, and human agency. Buddy Project continues to be guided by one fundamental principle: The purpose of using AI is to make human life better. Version 5.0 explores how that principle can extend from an individual relationship to family life and, ultimately, to coexistence between humans and 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
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 moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026