International Journal of Human-Computer Studies最新文献_第7页

Oh no! She is Flying! Interaction Analysis of Therapist-Robot Collaboration in Gait Rehabilitation 噢,不!她在飞！步态康复中治疗师-机器人协作的交互分析

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-27 DOI: 10.1016/j.ijhcs.2025.103620

Jose Pablo De la Rosa Gutierrez , Thiago Rocha Silva , Anders Stengaard Sørensen , Gitte Rasmussen

Strokes are a leading cause of disability, with many survivors experiencing significant mobility impairments. While robot-assisted rehabilitation offers a promising solution, its adoption seems challenged by high upfront costs, low flexibility and complex configuration workflows. To address these challenges, this study conducts an interaction analysis to identify key requirements for empowering therapists to self-configure and adapt a flexible, cost-effective robot during gait rehabilitation tasks. Our analysis is based on 20 training sequences from a 60-hour video dataset collected across three experimental setups, involving young adults with motor impairments training with the assistance of the robot. Drawing methods from Ethnomethodology and Conversation Analysis (EMCA), we examined the sequential organization of actions between technology, therapist and participant, identifying three main stages: setup, training, and completion. During setup, coordinated actions prepare the participant and the robot for the main training task; during training, participant and robot engage in movement while the therapist iterates adjustments; and in completion, coordinated actions prepare the participant for transitioning back to their conventional support system. Our analysis highlights some requirements and strategies for developing End-User Development (EUD) environments for robot-assisted physiotherapy, emphasizing user-driven workflows, multimodal transitions between robot’s assistance modes, and real-time robotic feedback that maintains coherence with therapists’ practices.

中风是致残的主要原因，许多幸存者经历了严重的行动障碍。虽然机器人辅助康复提供了一个很有前途的解决方案，但它的采用似乎面临着前期成本高、灵活性低和配置工作流程复杂的挑战。为了解决这些挑战，本研究进行了交互分析，以确定使治疗师能够在步态康复任务中自我配置和适应灵活、经济高效的机器人的关键要求。我们的分析基于从三个实验设置中收集的60小时视频数据集中的20个训练序列，涉及运动障碍的年轻人在机器人的帮助下进行训练。借鉴民族方法学和对话分析（EMCA）的方法，我们检查了技术、治疗师和参与者之间的行动顺序组织，确定了三个主要阶段：设置、培训和完成。在设置过程中，协调动作为参与者和机器人的主要训练任务做好准备；在训练期间，参与者和机器人进行运动，而治疗师反复调整；最后，协调一致的行动使参与者准备好过渡回他们传统的支持系统。我们的分析强调了开发机器人辅助物理治疗的终端用户开发（EUD）环境的一些要求和策略，强调用户驱动的工作流程，机器人辅助模式之间的多模式转换，以及与治疗师实践保持一致的实时机器人反馈。

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引用次数: 0

Mimicking fruit textures with low-cost stylus interfaces for accessible sensory interaction 用低成本的触控笔界面模拟水果纹理，实现感官互动

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-27 DOI: 10.1016/j.ijhcs.2025.103659

Christian Gonzalez , Luis M. Zamudio , Jesus Favela , Monica Tentori

Replicating real-world textures using haptic technology poses significant challenges, particularly in accurately capturing complex tactile qualities such as smoothness, roughness, and sharpness through vibration-based information. This research investigates how vibration parameters, intensity, duration, and off-time, can be manipulated to simulate textures inspired by fruit skins, including smooth-apple, rough-melon, bumpy-corn, sharp-pineapple, and adhesive-banana. Using a user-centered design methodology, we developed five vibrotactile patterns and implemented them within the Cactus Mobile Haptic Interface. The patterns were delivered via two interaction devices, a thimble and a stylus pen, designed to enable touch-based activities and tactile experiences. An empirical study with 36 participants evaluated those devices within three tasks: Tolerance to 10-second exposures, change perception, and the ability to associate patterns with real-world textures. Results showed that most patterns were accurately classified (76% with the thimble and 78% the stylus), although the adhesive texture proved more difficult to identify. Rough and sharp textures received slightly lower comfort ratings. While there were notable confusions between similar patterns, such as the sharp–bumpy pair, the type of interaction device did not significantly affect classification accuracy. These findings highlight the potential of low-cost haptic interfaces to mimic sensations from natural, realistic textures and emphasize the importance of refining vibration design for improved perceptual clarity. This work contributes to the development of accessible, portable, and customizable haptic systems designed for sensory interaction in therapeutic, educational, and interactive environments. Future research will focus on refining ambiguous patterns and exploring sensory integration to expand the system’s usability in tactile therapy.

使用触觉技术复制真实世界的纹理提出了重大挑战，特别是通过基于振动的信息准确捕获复杂的触觉质量，如平滑度，粗糙度和锐度。这项研究探讨了振动参数、强度、持续时间和关闭时间如何被操纵来模拟水果表皮的纹理，包括光滑的苹果、粗糙的甜瓜、凹凸的玉米、尖锐的菠萝和粘连的香蕉。使用以用户为中心的设计方法，我们开发了五种振动触觉模式，并在Cactus移动触觉界面中实现了它们。图案通过两个交互设备，一个顶针和一个触控笔传递，旨在实现基于触摸的活动和触觉体验。一项有36名参与者的实证研究在三个任务中评估了这些设备：对10秒曝光的耐受性，改变感知，以及将图案与现实世界纹理联系起来的能力。结果显示，大多数图案被准确地分类（76%的顶针和78%的触针），尽管粘接剂纹理证明更难识别。粗糙和尖锐纹理的舒适度评分略低。虽然相似模式之间存在明显的混淆，例如尖锐-凹凸对，但交互装置的类型对分类准确性没有显著影响。这些发现强调了低成本触觉界面模仿自然、真实纹理的潜力，并强调了改进振动设计以提高感知清晰度的重要性。这项工作有助于开发可访问、便携式和可定制的触觉系统，用于治疗、教育和互动环境中的感觉交互。未来的研究将集中在细化模糊模式和探索感觉整合，以扩大系统在触觉治疗中的可用性。

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引用次数: 0

How do young users perceive and respond to AI-generated short-form videos? An exploration of Generation Z’s perceptions, emotional responses, and trust in AI-created video on social media platforms 年轻用户如何看待和回应人工智能生成的短视频？探索Z世代对社交媒体平台上人工智能制作的视频的看法、情绪反应和信任

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-24 DOI: 10.1016/j.ijhcs.2025.103660

Hoai Lan Duong, Thi Kim Oanh Vo

As artificial intelligence (AI) becomes more prominent in shaping media experiences, short form video platforms such as TikTok, Instagram Reels, and YouTube Shorts have emerged as dynamic environments for complex interaction between humans and AI. While most research in human computer interaction has focused on AI in practical or task based roles, there is still limited understanding of how young people perceive and respond to AI-generated short-form videos in everyday digital contexts. This study helps fill that gap by focusing on Generation Z, the most active and influential demographic on social media, and the first to encounter generative AI as an integrated part of everyday digital life. Drawing on the Stimulus Organism Response model and Uncanny Valley Theory, and based on in-depth interviews, this study explores (1) how Gen Z perceives the human likeness and emotional authenticity of AI generated short form videos, and (2) what interactional and design features shape their trust and engagement. The findings reveal a mix of admiration and unease. Key design elements such as visuals, voice, storytelling, and transparency about authorship play a critical role in how young users assess authenticity and build trust. The study expands the scope of Human-Computer Interaction by treating AI as a social and creative presence. It introduces the Perceptual Response Zone to explain how emotional realism shapes user trust and proposes a new framework for understanding how design stimuli influence engagement behaviors. These insights offer practical guidance for creating emotionally resonant AI content for youth audiences.

随着人工智能（AI）在塑造媒体体验方面的作用越来越突出，TikTok、Instagram Reels、YouTube Shorts等短视频平台已经成为人类与人工智能复杂互动的动态环境。虽然大多数人机交互研究都集中在人工智能在实际或基于任务的角色上，但对于年轻人如何在日常数字环境中感知和回应人工智能生成的短视频，人们的理解仍然有限。这项研究通过关注Z世代来填补这一空白。Z世代是社交媒体上最活跃、最具影响力的人群，也是第一批将生成式人工智能作为日常数字生活不可或缺的一部分的人。本研究借鉴刺激有机体反应模型和恐怖谷理论，基于深度访谈，探讨(1)Z世代如何感知人工智能生成的短视频的人类相似性和情感真实性；(2)哪些交互和设计特征塑造了他们的信任和参与度。调查结果显示，人们既有钦佩，也有不安。关键的设计元素，如视觉、声音、故事和作者的透明度，在年轻用户如何评估真实性和建立信任方面发挥着关键作用。该研究将人工智能视为一种社交和创造性的存在，扩大了人机交互的范围。它引入了感知反应区来解释情感现实主义如何塑造用户信任，并提出了一个新的框架来理解设计刺激如何影响参与行为。这些见解为为年轻观众创造情感共鸣的人工智能内容提供了实用指导。

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引用次数: 0

Older adults co-creating and experiencing VR garden tours: Developing a participatory VR storytelling framework 老年人共同创造和体验VR花园之旅：开发参与式VR叙事框架

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-17 DOI: 10.1016/j.ijhcs.2025.103656

Wei Zhao , Ryan M. Kelly , Melissa J. Rogerson , Jenny Waycott

Virtual reality (VR) technology is being used in diverse ways to enable older adults to reminisce and connect. An underexplored area is the use of VR for creating and sharing personally meaningful stories. This paper examines the use of VR technology to help nine older adults share and experience others’ stories about their gardens. Through a co-design approach involving home visits, interviews, and a workshop, we examined older gardeners’ perceptions and experiences of co-creating, sharing, and viewing narrated 3D garden tours captured with a VR camera. Our findings demonstrate that participants showcased the meaning, creativity, and expertise associated with their gardens and gardening practices through the VR garden tours. Viewing the garden tours created by others fostered a sense of connection among participants through shared passions and interests. Participants valued the authenticity and individuality of the tours, perceiving them as avenues for learning, inspiration, and motivation. Viewers experienced a strong sense of presence in the garden tours, particularly due to the spatial immersion, holistic perspectives, the first-person view, and the ability to exert control in the VR system. The study reveals opportunities to enhance the VR garden tour experience, including increasing sociality, improving usability and guidance, and building communities around the tours. Drawing from these insights, we develop a framework to guide future practices of conducting participatory VR storytelling with older adults. The framework outlines three critical roles involved in the process: Storyteller, Facilitator, and Audience. It also discusses five key elements that need to be considered: Intention, Narrative, Medium, Context, and Engagement.

虚拟现实（VR）技术正以多种方式被用于老年人的回忆和联系。一个未被充分开发的领域是使用VR来创造和分享个人有意义的故事。本文研究了使用VR技术来帮助九位老年人分享和体验他人关于他们花园的故事。通过包括家访、访谈和研讨会在内的共同设计方法，我们研究了老年园丁对共同创造、分享和观看用VR相机拍摄的3D花园之旅的看法和经验。我们的研究结果表明，参与者通过VR花园之旅展示了与他们的花园和园艺实践相关的意义、创造力和专业知识。观看由其他人创建的花园之旅，通过分享激情和兴趣，培养了参与者之间的联系感。参与者重视旅游的真实性和个性，将其视为学习、灵感和动力的途径。观众在花园之旅中体验到强烈的存在感，特别是由于空间沉浸，整体视角，第一人称视角以及VR系统中施加控制的能力。该研究揭示了增强VR花园旅游体验的机会，包括增加社交性，改善可用性和指导，以及围绕旅游建立社区。根据这些见解，我们开发了一个框架，以指导未来与老年人进行参与式VR讲故事的实践。该框架概述了过程中涉及的三个关键角色：说书人、推动者和听众。它还讨论了需要考虑的5个关键元素：意图、叙述、媒介、背景和粘性。

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引用次数: 0

Generative AI personas considered harmful? Putting forth twenty challenges of algorithmic user representation in human-computer interaction 生成人工智能角色被认为是有害的？提出了人机交互中算法用户表示的二十个挑战

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-17 DOI: 10.1016/j.ijhcs.2025.103657

Danial Amin , Joni Salminen , Bernard J. Jansen , Joongi Shin , Dae Hyun Kim

Generative AI personas (GenAIPs) promise user-centred design efficiency, but their impact on different persona challenges remains unexplored. Inspired by Dijkstra’s classic essay on harmful programming constructs, we analyze twenty challenges in persona development using Human-Centered AI principles. Through literature review and expert survey (n = 17), we find that GenAIPs transform rather than eliminate traditional persona challenges. Experts rated all challenges as problematic for GenAIPs (M > 4.0), with the highest concerns for hallucinations (M = 5.94), over-sanitization (M = 5.82), and lack of standardization (M = 5.59). 12 out of 20 challenges are considered more problematic for GenAIPs than conventional personas, particularly bias amplification, validation challenges, and accessibility without expertise. We provide HCAI-grounded guidelines demonstrating that effective GenAIP implementation requires human-AI collaboration rather than automation and prioritizing user welfare over technical efficiency.

生成式人工智能人物角色（GenAIPs）承诺以用户为中心的设计效率，但它们对不同人物角色挑战的影响仍未被探索。受Dijkstra关于有害编程结构的经典文章的启发，我们使用以人为中心的AI原则分析了人物角色开发中的20个挑战。通过文献回顾和专家调查（n = 17），我们发现GenAIPs改变了而不是消除了传统的角色挑战。专家们对GenAIPs的所有挑战进行了评分（M > 4.0），其中幻觉（M = 5.94）、过度消毒（M = 5.82）、缺乏标准化（M = 5.59）是最令人担忧的问题。对于genaip来说，20个挑战中有12个被认为比传统人物角色更有问题，特别是偏见放大、验证挑战和没有专业知识的可访问性。我们提供了基于人工智能的指导方针，表明有效的GenAIP实施需要人类与人工智能的协作，而不是自动化，并优先考虑用户福利而不是技术效率。

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引用次数: 0

Augmented reality robot manipulation with physical mock-up and improved spatial cognition 增强现实机器人操作与物理模型和改进的空间认知

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-17 DOI: 10.1016/j.ijhcs.2025.103658

Fang Xu , Hengxu You , Tianyu Zhou , Jing Du

Robotic teleoperation is essential for executing tasks in remote, hazardous, or inaccessible environments such as disaster response, hazardous materials handling, and search and rescue missions. In these complex scenarios, limited robot autonomy often requires direct human control to ensure adaptability and situational responsiveness. Traditional teleoperation systems using virtual reality (VR) head-mounted displays aim to improve spatial awareness, but they suffer from limited depth perception and lack of proprioceptive feedback. Recent advances in augmented reality (AR), particularly optical see-through (OST) head mounted displays, offer a more intuitive solution by overlaying digital information directly onto the real world. This approach improves egocentric spatial cognition and motor coordination by aligning virtual cues with physical actions, which reduces cognitive load and increases precision. This study evaluates an AR-based teleoperation system that combines a HoloLens2 OST-based AR display, adaptive hand-motion controls, Unity-based visualization, and a Franka Emika 7-DOF robotic arm. In a user study with 30 participants, the AR-enhanced interface demonstrated significantly higher spatial awareness and task execution efficiency than conventional setups. These results provide empirical support for deploying AR in high-stakes teleoperation tasks where accuracy and situational awareness are critical.

机器人远程操作对于在远程、危险或难以进入的环境中执行任务至关重要，例如灾难响应、危险材料处理和搜索和救援任务。在这些复杂的场景中，有限的机器人自主性通常需要人类直接控制，以确保适应性和情境响应能力。使用虚拟现实（VR）头戴式显示器的传统远程操作系统旨在提高空间意识，但它们存在深度感知有限和缺乏本体感觉反馈的问题。增强现实（AR）的最新进展，特别是光学透明（OST）头戴式显示器，通过将数字信息直接覆盖到现实世界中，提供了更直观的解决方案。该方法通过将虚拟线索与物理动作相匹配，提高了自我中心空间认知和运动协调能力，减少了认知负荷，提高了精度。本研究评估了一种基于AR的远程操作系统，该系统结合了基于HoloLens2的AR显示、自适应手部运动控制、基于unity的可视化和Franka Emika 7自由度机械臂。在一项有30名参与者的用户研究中，ar增强界面比传统设置显示出更高的空间意识和任务执行效率。这些结果为在准确性和态势感知至关重要的高风险远程操作任务中部署AR提供了经验支持。

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引用次数: 0

StoryPoint: GenAI-supported domain-specific data story authoring for enterprises StoryPoint：为企业编写genai支持的特定领域的数据故事

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-15 DOI: 10.1016/j.ijhcs.2025.103655

Jonas Gunklach, Elias Mueller, Merlin Knaeble, Alexander Maedche

In today’s data-driven world, enterprises face the dual challenge of deriving value from vast datasets and effectively communicating insights. While data storytelling is integral for conveying insights, existing authoring tools often fail to fully leverage domain expertise or support the entire storytelling process. This paper introduces StoryPoint, an open-source data story authoring tool that combines domain expertise with Generative AI to dynamically enhance data story creation. We found that enabling domain experts to intuitively visualize data via natural language inputs, supported by automatically generated charts and narratives, helps narrow the gap between visualization and interpretation. To design StoryPoint, we followed a literature-grounded and user-centered design approach. A formative evaluation with eight domain experts reveals StoryPoint’s efficacy in rapid data story prototyping. A summative evaluation, including (i) a small-scale experiment comparing StoryPoint with a benchmark, (ii) a large-scale online experiment with 104 crowdworkers, and (iii) three real-world industry cases, underscores its utility. Our findings highlight that StoryPoint reduces data story creation time by more than 50% compared to the benchmark, receives significantly higher usability ratings, and supports the creation of data stories rating higher in readability, fluency, clarity, and trustworthiness.

在当今数据驱动的世界中，企业面临着从海量数据集中获取价值和有效沟通见解的双重挑战。虽然数据叙述对于传达见解来说是不可或缺的，但现有的创作工具往往不能充分利用领域专业知识或支持整个叙述过程。本文介绍了StoryPoint，这是一个开源的数据故事创作工具，它将领域专业知识与生成式人工智能相结合，以动态增强数据故事的创建。我们发现，在自动生成的图表和叙述的支持下，使领域专家能够通过自然语言输入直观地可视化数据，有助于缩小可视化和解释之间的差距。为了设计StoryPoint，我们遵循了基于文献和以用户为中心的设计方法。由8位领域专家组成的形成性评估揭示了StoryPoint在快速数据故事原型中的功效。总结性评估，包括(i)将StoryPoint与基准进行比较的小规模实验，（ii）与104名众包工作者进行的大规模在线实验，以及（iii）三个现实世界的行业案例，强调了它的实用性。我们的研究结果强调，与基准相比，StoryPoint将数据故事的创建时间减少了50%以上，获得了显著更高的可用性评级，并支持创建可读性、流畅性、清晰度和可信度更高的数据故事。

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引用次数: 0

Intelligent support for digital wellbeing: A design framework through a systematic literature review 数字健康的智能支持：通过系统文献综述的设计框架

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-08 DOI: 10.1016/j.ijhcs.2025.103653

Luca Scibetta , Massimiliano Pellegrino , Alberto Monge Roffarello, Luigi De Russis

Recent advancements in AI, particularly Generative AI (GenAI) and Large Language Models (LLMs), have facilitated the integration of AI techniques into digital wellbeing applications, i.e., digital tools that aim at helping people’s wellbeing as a sum of mental and emotional wellness. These AI-powered systems hold the potential to foster healthier habits by collecting and analyzing user behavioral data to provide personalized and dynamic solutions tailored to each user’s needs and lifestyle, therefore improving the efficacy with respect to traditional non-AI interventions. Yet, their development presents significant challenges, including ethical concerns, privacy risks, and the potential for over-reliance on automated interventions. In this paper, we conduct a systematic literature review to examine the key characteristics, challenges, and opportunities in the existing research about AI-powered digital wellbeing tools. Based on our findings, we propose a design framework that outlines 6 critical dimensions and 23 sub-dimensions, spacing from user data and privacy to intervention strategies and personalization, offering practical guidance for researchers and practitioners developing AI-powered digital wellbeing applications. The framework emphasizes the importance of developing tailored and adaptive user-centered interventions adhering to scientific principles, psychological models and responsible data collection. We discuss the applicability and utility of our framework in evaluating and guiding the integration of AI in digital wellbeing applications.

人工智能的最新进展，特别是生成式人工智能（GenAI）和大型语言模型（llm），促进了人工智能技术与数字健康应用的整合，即旨在帮助人们获得精神和情感健康的数字工具。这些人工智能驱动的系统有可能通过收集和分析用户行为数据来培养更健康的习惯，为每个用户的需求和生活方式量身定制个性化和动态的解决方案，从而提高传统非人工智能干预措施的功效。然而，它们的发展面临着重大挑战，包括伦理问题、隐私风险以及过度依赖自动化干预的可能性。在本文中，我们进行了系统的文献综述，以研究人工智能驱动的数字健康工具的现有研究中的关键特征、挑战和机遇。基于我们的研究结果，我们提出了一个设计框架，概述了6个关键维度和23个子维度，从用户数据和隐私到干预策略和个性化，为研究人员和从业者开发人工智能驱动的数字健康应用程序提供了实用指导。该框架强调，必须根据科学原则、心理模型和负责任的数据收集，制定有针对性和适应性的以用户为中心的干预措施。我们讨论了我们的框架在评估和指导人工智能在数字健康应用中的集成方面的适用性和实用性。

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引用次数: 0

“I’ve never seen a glass ceiling better represented”: Bias and gendering in LLM-generated synthetic personas from a participatory design perspective “我从未见过比这更好的玻璃天花板”：从参与式设计的角度来看，法学硕士生成的合成角色中的偏见和性别

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-08 DOI: 10.1016/j.ijhcs.2025.103651

Helena A. Haxvig , Vincenzo D’Andrea , Maurizio Teli

This study examines synthetic personas generated by Large Language Models (LLMs) and their implications, focusing on how these personas encode and perform gendering. Traditional personas carry implicit power and agency, making their accuracy and inclusivity essential. However, delegating persona creation to generative AI raises concerns about bias, representation, and ethical design. Poorly designed personas risk reinforcing stereotypes, marginalizing certain groups, and embedding biases into the design process. Using a mixed-method approach – combining direct inquiries with four LLMs and participatory workshops – we analyze gender bias in synthetic personas. Drawing from feminist theory, Human–Computer Interaction (HCI), and Participatory Design (PD), both societal, normative, and representational biases were identified. As a result of this, we argue that synthetic personas should not be used as direct stand-ins for real users but instead reframed as objects of critical inquiry. They can serve as provocations—tools that challenge assumptions and expose biases in LLM-generated outputs. Furthermore, this study underscores the need to move beyond exclusively expert-driven evaluations by incorporating user perspectives directly. By doing so, the evaluation process becomes richer, more representative, and better equipped to identify biases that might otherwise be overlooked.

本研究考察了由大型语言模型（llm）生成的合成人物角色及其含义，重点关注这些人物角色是如何编码和执行性别划分的。传统人物角色具有隐含的权力和能动性，因此其准确性和包容性至关重要。然而，将角色创建委托给生成人工智能会引发对偏见、代表性和道德设计的担忧。设计不佳的角色可能会强化刻板印象，边缘化某些群体，并在设计过程中嵌入偏见。使用混合方法方法-结合直接询问与四个法学硕士和参与式研讨会-我们分析了合成人物角色中的性别偏见。从女权主义理论、人机交互（HCI）和参与式设计（PD）中，我们发现了社会、规范和代表性的偏见。因此，我们认为合成人物角色不应该被用作真实用户的直接替身，而应该被重新定义为批判性探究的对象。它们可以作为挑战假设和暴露法学硕士产生的产出中的偏见的挑衅工具。此外，这项研究强调有必要超越完全由专家推动的评价，直接纳入用户的观点。通过这样做，评估过程变得更丰富，更具代表性，并更好地识别可能被忽视的偏见。

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引用次数: 0

How animal-persona chatbots enhance empathy and positive attitudes toward animals 动物角色聊天机器人如何增强对动物的同理心和积极态度

IF 5.1 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

International Journal of Human-Computer Studies

Pub Date : 2025-10-06 DOI: 10.1016/j.ijhcs.2025.103647

Jingshu Li , Aaditya Patwari , Yi-Chieh Lee

Rises in the number of animal abuse cases are reported around the world. While chatbots have been effective in influencing their users’ perceptions and behaviors, little if any research has hitherto explored the design of chatbots that embody animal personas for the purpose of eliciting empathy toward animals. We therefore conducted a 2 × 2 × 2 experiment factorial experiment based on the presence or absence of verbal, nonverbal, and identity cues to investigate how specific design cues in such chatbots can shape their users’ perceptions of both the chatbots’ identities and the type of animal they represent. Our findings indicate that such chatbots can significantly increase empathy, improve attitudes, and promote prosocial behavioral intentions toward animals, particularly when they incorporate emotional verbal expressions and authentic details of such animals’ lives. These results expand our understanding of chatbots with non-human identities and highlight their potential for use in conservation initiatives, suggesting a promising avenue whereby technology could foster a more informed and empathetic society.

据报道，世界各地虐待动物的案件数量不断上升。虽然聊天机器人在影响用户的感知和行为方面很有效，但迄今为止，很少有研究探讨了如何设计具有动物角色的聊天机器人，从而引发人们对动物的同情。因此，我们进行了一项基于语言、非语言和身份线索存在与否的2 × 2实验阶乘实验，以调查此类聊天机器人中的特定设计线索如何影响用户对聊天机器人身份和它们所代表的动物类型的感知。我们的研究结果表明，这种聊天机器人可以显著增加同理心，改善态度，并促进对动物的亲社会行为意图，特别是当它们结合了情感语言表达和这些动物生活的真实细节时。这些结果扩大了我们对具有非人类身份的聊天机器人的理解，并突出了它们在保护倡议中使用的潜力，表明了一条有希望的途径，即技术可以促进一个更知情、更有同情心的社会。

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