Explainable Artificial Intelligence (XAI) aims to provide insights into the inner workings and the outputs of AI systems. Recently, there’s been growing recognition that explainability is inherently human-centric, tied to how people perceive explanations. Despite this, there is no consensus in the research community on whether user evaluation is crucial in XAI, and if so, what exactly needs to be evaluated and how. This systematic literature review addresses this gap by providing a detailed overview of the current state of affairs in human-centered XAI evaluation. We reviewed 73 papers across various domains where XAI was evaluated with users. These studies assessed what makes an explanation “good” from a user’s perspective, i.e., what makes an explanation meaningful to a user of an AI system. We identified 30 components of meaningful explanations that were evaluated in the reviewed papers and categorized them into a taxonomy of human-centered XAI evaluation, based on: (a) the contextualized quality of the explanation, (b) the contribution of the explanation to human-AI interaction, and (c) the contribution of the explanation to human- AI performance. Our analysis also revealed a lack of standardization in the methodologies applied in XAI user studies, with only 19 of the 73 papers applying an evaluation framework used by at least one other study in the sample. These inconsistencies hinder cross-study comparisons and broader insights. Our findings contribute to understanding what makes explanations meaningful to users and how to measure this, guiding the XAI community toward a more unified approach in human-centered explainability.
MULTIFILE
This paper introduces the design principle of legibility as means to examine the epistemic and ethical conditions of sensing technologies. Emerging sensing technologies create new possibilities regarding what to measure, as well as how to analyze, interpret, and communicate said measurements. In doing so, they create ethical challenges for designers to navigate, specifically how the interpretation and communication of complex data affect moral values such as (user) autonomy. Contemporary sensing technologies require layers of mediation and exposition to render what they sense as intelligible and constructive to the end user, which is a value-laden design act. Legibility is positioned as both an evaluative lens and a design criterion, making it complimentary to existing frameworks such as value sensitive design. To concretize the notion of legibility, and understand how it could be utilized in both evaluative and anticipatory contexts, the case study of a vest embedded with sensors and an accompanying app for patients with chronic obstructive pulmonary disease is analyzed.
DOCUMENT
Technology in general, and assistive technology in particular, is considered to be a promising opportunity to address the challenges of an aging population. Nevertheless, in health care, technology is not as widely used as could be expected. In this chapter, an overview is given of theories and models that help to understand this phenomenon. First, the design of (assistive) technologies will be addressed and the importance of human-centered design in the development of new assistive devices will be discussed. Also theories and models are addressed about technology acceptance in general. Specific attention will be given to technology acceptance in healthcare professionals, and the implementation of technology within healthcare organizations. The chapter will be based on the state of the art of scientific literature and will be illustrated with examples from our research in daily practice considering the different perspectives of involved stakeholders.
LINK
The Dutch hospitality sector is the 8th largest contributor to GDP, employing over 500,000 people, yet it remains heavily reliant on manual processes and human labor for service delivery. Structural staff shortages, rising labor costs, and increasing operational demands are pushing the industry to its limits. Hotels and restaurants, the backbone of this sector, are struggling with operational inefficiencies, high staff turnover, and the growing difficulty of maintaining high service standards. An overhaul of the traditional hospitality model is necessary to unlock sustainable growth. This Embrace IT project provides a structured, collaborative approach to solving these pressing challenges. Focusing on three critical areas—housekeeping services, food services, and reception services—the project will co-create concrete, tech-driven solutions together with hospitality businesses, technology providers, and knowledge institutions. These areas represent key operational cost drivers and are vital to revenue generation, making them priorities for industry leaders. By developing technology that complements human labor, the project ensures that operational efficiency improves while leveraging worker well-being and hospitality experience. Over four years, Embrace IT will establish a sustainable innovation ecosystem within the hospitality sector. Through iterative co-creation and field testing of automation, AI, and immersive technologies, the project will equip businesses with the tools and structures to shift from short-term, reactive strategies to long-term, sustainable digital transformation. Moving beyond the current "sensing" phase, where businesses recognize technological trends but are hesitant to act, Embrace IT will deliver concrete and scalable solutions that foster industry-wide adoption. Embrace IT aligns with key sector policy documents such as the 2024 Digital Destinations strategy from the Netherlands Board of Tourism & Conventions (NBTC), ensuring direct support of the broader vision for digital transformation of Dutch hospitality. This project will increase productivity of the sector while improving working conditions and leveraging hospitality experience – to ensure lasting societal impact.
