Related papers: Developing and Operating Artificial Intelligence M…
This study explores the benefits and challenges of integrating Artificial Intelligence with Agile software development methodologies, focusing on improving continuous integration and delivery. A systematic literature review and longitudinal…
As artificial intelligence (AI) becomes increasingly embedded in daily life, designing intuitive, trustworthy, and emotionally resonant AI-human interfaces has emerged as a critical challenge. This editorial introduces a Special Issue that…
As AI becomes embedded in customer-facing systems, ethical scrutiny has largely focused on models, data, and governance. Far less attention has been paid to how AI is experienced through user-facing design. This commentary argues that many…
Responsible Artificial Intelligence (RAI) addresses the ethical and regulatory challenges of deploying AI systems in high-risk scenarios. This paper proposes a comprehensive framework for the design of an RAI system (RAIS) that integrates…
Human-technology interaction deals with trust as an inevitable requirement for user acceptance. As the applications of artificial intelligence (AI) and robotics emerge and with their ever-growing socio-economic influence in various fields…
My research centers on the development of context-adaptive AI systems to improve end-user adoption through the integration of technical methods. I deploy these AI systems across various interaction modalities, including user interfaces and…
Human computation is an approach to solving problems that prove difficult using AI only, and involves the cooperation of many humans. Because human computation requires close engagement with both "human populations as users" and "human…
In this paper we present an analysis of technological and psychological factors of applying artificial intelligence (AI) at the work place. We do so for a number of twelve application cases in the context of a project where AI is integrated…
AI and its relevant technologies, including machine learning, deep learning, chatbots, virtual assistants, and others, are currently undergoing a profound transformation of development and organizational processes within companies.…
AI is increasingly being offered 'as a service' (AIaaS). This entails service providers offering customers access to pre-built AI models and services, for tasks such as object recognition, text translation, text-to-voice conversion, and…
In the future, most companies will be confronted with the topic of Artificial Intelligence (AI) and will have to decide on their strategy in this regards. Currently, a lot of companies are thinking about whether and how AI and the usage of…
Automated control monitors could play an important role in overseeing highly capable AI agents that we do not fully trust. Prior work has explored control monitoring in simplified settings, but scaling monitoring to real-world deployments…
Assuring safety of artificial intelligence (AI) applied to safety-critical systems is of paramount importance. Especially since research in the field of automated driving shows that AI is able to outperform classical approaches, to handle…
Operationalizing the EU AI Act requires clear technical documentation to ensure AI systems are transparent, traceable, and accountable. Existing documentation templates for AI systems do not fully cover the entire AI lifecycle while meeting…
With recent advancements in AI and computation tools, intelligent paradigms emerged to empower different fields such as healthcare robots with new capabilities. Advanced AI robotic algorithms (e.g., reinforcement learning) can be trained…
AI-based systems leverage recent advances in the field of AI/ML by combining traditional software systems with AI components. Applications are increasingly being developed in this way. Software engineers can usually rely on a plethora of…
According to several empirical investigations, despite enhancing human capabilities, human-AI cooperation frequently falls short of expectations and fails to reach true synergy. We propose a task-driven framework that reverses prevalent…
We present an overview of the literature on trust in AI and AI trustworthiness and argue for the need to distinguish these concepts more clearly and to gather more empirically evidence on what contributes to people s trusting behaviours. We…
As artificial intelligence systems grow more capable and autonomous, frontier AI development poses potential systemic risks that could affect society at a massive scale. Current practices at many AI labs developing these systems lack…
Autonomous driving systems (ADSs) promise improved transportation efficiency and safety, yet ensuring their reliability in complex real-world environments remains a critical challenge. Effective testing is essential to validate ADS…