Related papers: Visualization for Human-Centered AI Tools
Human-centered artificial intelligence (HCAI) is a design philosophy that prioritizes humans in the design, development, deployment, and use of AI systems, aiming to maximize AI's benefits while mitigating its negative impacts. Despite its…
This study is located in the Human-Centered Artificial Intelligence (HCAI) and focuses on the results of a user-centered assessment of commonly used eXplainable Artificial Intelligence (XAI) algorithms, specifically investigating how humans…
In healthcare, AI techniques are widely used for tasks like risk assessment and anomaly detection. Despite AI's potential as a valuable assistant, its role in complex medical data analysis often oversimplifies human-AI collaboration…
The development of autonomous robotic systems offers significant potential for performing complex tasks with precision and consistency. Recent advances in Artificial Intelligence (AI) have enabled more capable intelligent automation…
The growing importance of data visualization in business intelligence and data science emphasizes the need for tools that can efficiently generate meaningful visualizations from large datasets. Existing tools fall into two main categories:…
Researchers and practitioners increasingly consider a human-centered perspective in the design of machine learning-based applications, especially in the context of Explainable Artificial Intelligence (XAI). However, clear methodological…
Humans are increasingly coming into contact with artificial intelligence and machine learning systems. Human-centered artificial intelligence is a perspective on AI and ML that algorithms must be designed with awareness that they are part…
Advancements in Artificial Intelligence (AI) have significantly transformed the financial industry, enabling the development of more personalised and adaptable financial products and services. This research paper explores various instances…
While recent advances in deep learning have demonstrated its transformative potential, its adoption for real-world manufacturing applications remains limited. We present an Explanation User Interface (XUI) for a state-of-the-art deep…
Starting from the design philosophy of "user-centered design", this paper analyzes the human factors characteristics of intelligent human-computer interaction (iHCI) and proposes a concept of "user-oriented iHCI". The paper further proposes…
IUIs aim to incorporate intelligent automated capabilities in human computer interaction, where the net impact is a human-computer interaction that improves performance or usability in critical ways. It also involves designing and…
As AI systems become increasingly conversational, a gap emerges wherein explanations are studied as static artifacts, yet in practice, are experienced as dialogue. In this provocation, we argue that the conversational layer around an…
The rapid development of artificial intelligence (AI) has significantly transformed human-computer interactions, making it essential to establish robust design standards to ensure effective, ethical, and human-centered AI (HCAI) solutions.…
Despite its technological breakthroughs, eXplainable Artificial Intelligence (XAI) research has limited success in producing the {\em effective explanations} needed by users. In order to improve XAI systems' usability, practical…
Explainable AI (XAI) is widely viewed as a sine qua non for ever-expanding AI research. A better understanding of the needs of XAI users, as well as human-centered evaluations of explainable models are both a necessity and a challenge. In…
While research on explainable AI (XAI) is booming and explanation techniques have proven promising in many application domains, standardised human-centred evaluation procedures are still missing. In addition, current evaluation procedures…
As AI becomes more common in everyday living, there is an increasing demand for intelligent systems that are both performant and understandable. Explainable AI (XAI) systems aim to provide comprehensible explanations of decisions and…
Human-Center eXplainable AI (HCXAI) literature identifies the need to address user needs. This paper examines how existing XAI research involves human users in designing and developing XAI systems and identifies limitations in current…
The integration of Artificial Intelligence (AI) in modern society is transforming how individuals perform tasks. In high-risk domains, ensuring human control over AI systems remains a key design challenge. This article presents a novel…
As artificial intelligence (AI) becomes more integrated into educational environments, how can we ensure that these systems are both understandable and trustworthy? The growing demand for explainability in AI systems is a critical area of…