Related papers: Towards Human-AI Synergy in Requirements Engineeri…
A paradigm shift is underway in Software Engineering, with AI systems such as LLMs playing an increasingly important role in boosting software development productivity. This trend is anticipated to persist. In the next years, we expect a…
Artificial intelligence (AI) has become a crucial instrument for streamlining processes in various industries, including electrical power systems, as a result of recent digitalization. Algorithms for artificial intelligence are data-driven…
Hardware Reverse Engineering (HRE) is a technique for analyzing integrated circuits. Experts employ HRE for security-critical tasks, like detecting Trojans or intellectual property violations, relying not only on their experience and…
As AI agents built on large language models (LLMs) become increasingly embedded in society, issues of coordination, control, delegation, and accountability are entangled with concerns over their reliability. To design and implement LLM…
With the increasing deployment of artificial intelligence (AI) technologies, the potential of humans working with AI agents has been growing at a great speed. Human-AI teaming is an important paradigm for studying various aspects when…
Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This raises the need for…
The use of artificial intelligence (AI) in working environments with individuals, known as Human-AI Collaboration (HAIC), has become essential in a variety of domains, boosting decision-making, efficiency, and innovation. Despite HAIC's…
As artificial intelligence (AI) becomes deeply integrated into critical infrastructures and everyday life, ensuring its safe deployment is one of humanity's most urgent challenges. Current AI models prioritize task optimization over safety,…
Recent advances in large language models (LLMs) have sparked growing interest in building fully autonomous agents. However, fully autonomous LLM-based agents still face significant challenges, including limited reliability due to…
The field of artificial intelligence (AI) is witnessing a recent upsurge in research, tools development, and deployment of applications. Multiple software companies are shifting their focus to developing intelligent systems; and many others…
Computer-Aided Engineering (CAE) enables simulation experts to optimize complex models, but faces challenges in user experience (UX) that limit efficiency and accessibility. While artificial intelligence (AI) has demonstrated potential to…
Machine Learning (ML)-enabled systems challenge traditional Requirements Engineering (RE) and agile management due to data dependence, experimentation, and uncertain model behavior. Existing RE and agile practices remain poorly integrated…
Artificial intelligence (AI) systems are deployed as collaborators in human decision-making. Yet, evaluation practices focus primarily on model accuracy rather than whether human-AI teams are prepared to collaborate safely and effectively.…
AI tools are proliferating in human resources management (HRM) and recruiting, helping to mediate access to the labor market. As these systems spread, profession-specific transparency needs emerging from black-boxed systems in HRM move into…
Artificial Intelligence (AI) is advancing at an unprecedented pace, with clear potential to enhance decision-making and productivity. Yet, the collaborative decision-making process between humans and AI remains underdeveloped, often falling…
Requirements engineering (RE), as a part of the project development life cycle, has increasingly been recognized as the key to ensuring on-time, on-budget, and goal-based delivery of software projects;compromising this vital phase is…
This position paper argues for a fundamental shift in how Large Language Models (LLMs) are integrated into the mental health care domain. We advocate for their role as co-creators rather than mere assistive tools. While LLMs have the…
This paper explores how generative AI can help automate and improve key steps in systems engineering. It examines AI's ability to analyze system requirements based on INCOSE's "good requirement" criteria, identifying well-formed and poorly…
Regulatory frameworks for the use of AI are emerging. However, they trail behind the fast-evolving malicious AI technologies that can quickly cause lasting societal damage. In response, we introduce a pioneering Assistive AI framework…
Context: Requirements Engineering (RE)-related activities are critical in developing quality software and one of the most human-dependent processes in software engineering (SE). Hence, identifying the impact of diverse human-related aspects…