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检索条件"任意字段=Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems"

共 4919 条记录，以下是81-90 订阅

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No Pie in the (Digital) Sky: Co-Imagining the Food Metaverse 23

No Pie in the (Digital) Sky: Co-Imagining the Food Metaverse

引用

chi conference on human factors in computing systems (chi)

作者： Covaci, Alexandra Alhasan, Khawla Loonker, Mayank Farrell, Bernardine Tabbaa, Luma Ppali, Sophia Ang, Chee Siang Univ Kent Canterbury Kent England Univ Bahrain Sakheer Bahrain

ISBN: (纸本)9781450394215

human behaviour and habits co-evolve with technology, and the metaverse is poised to become a key player in reshaping how we live our everyday life. Given the importance of food in our daily lives, we ask: how will our relationships with food be transformed by the metaverse, and what are the promises and pitfalls of this technology? To answer this, we propose a co-design study that reveals the important elements people value in their daily interactions with food. We then present a speculative catalogue of novel metaverse food experiences, and insights from discussing these ideas with food designers, anthropologists and metaverse experts. Our work aims to provide designers with inspirations for building a metaverse that: provides inclusive opportunities for the future of food;helps re-discover the forgotten or lost knowledge about food;facilitates the exploration, excitement and joy of eating;and reinvigorates the ways that food can soothe and heal.

关键词： metaverse food human food technology interaction speculative design co-design

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Social Dynamics of AI Support in Creative Writing 23

Social Dynamics of AI Support in Creative Writing

引用

chi conference on human factors in computing systems (chi)

作者： Gero, Katy Ilonka Long, Tao chilton, Lydia Columbia Univ New York NY 10027 USA

ISBN: (纸本)9781450394215

Recently, large language models have made huge advances in generating coherent, creative text. While much research focuses on how users can interact with language models, less work considers the social-technical gap that this technology poses. What are the social nuances that underlie receiving support from a generative AI? In this work we ask when and why a creative writer might turn to a computer versus a peer or mentor for support. We interview 20 creative writers about their writing practice and their attitudes towards both human and computer support. We discover three elements that govern a writer's interaction with support actors: 1) what writers desire help with, 2) how writers perceive potential support actors, and 3) the values writers hold. We align our results with existing frameworks of writing cognition and creativity support, uncovering the social dynamics which modulate user responses to generative technologies.

关键词： creative writing writing support tools writing assistants human-AI collaboration language models

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ChameleonControl: Teleoperating Real human Surrogates through Mixed Reality Gestural Guidance for Remote Hands-on Classrooms 23

ChameleonControl: Teleoperating Real Human Surrogates throug...

引用

chi conference on human factors in computing systems (chi)

作者： Faridan, Mehrad Kumari, Bheesha Suzuki, Ryo Univ Calgary Calgary AB Canada MaKami Coll Calgary AB Canada

ISBN: (纸本)9781450394215

We present ChameleonControl, a real-human teleoperation system for scalable remote instruction in hands-on classrooms. In contrast to existing video or AR/VR-based remote hands-on education, ChameleonControl uses a real human as a surrogate of a remote instructor. Building on existing human-based telepresence approaches, we contribute a novel method to teleoperate a human surrogate through synchronized mixed reality hand gestural navigation and verbal communication. By overlaying the remote instructor's virtual hands in the local user's MR view, the remote instructor can guide and control the local user as if they were physically present. This allows the local user/surrogate to synchronize their hand movements and gestures with the remote instructor, effectively teleoperating a real human. We deploy and evaluate our system in classrooms of physiotherapy training, as well as other application domains such as mechanical assembly, sign language and cooking lessons. The study results confirm that our approach can increase engagement and the sense of co-presence, showing potential for the future of remote hands-on classrooms.

关键词： Mixed Reality Visual Cue Remote Collaboration Telepresence Remote Guidance human Surrogates Hands-on Training

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Understanding Perception of human Augmentation: A Mixed-Method Study 23

Understanding Perception of Human Augmentation: A Mixed-Meth...

引用

chi conference on human factors in computing systems (chi)

作者： Villa, Steeven Niess, Jasmin Nakao, Takuro Lazar, Jonathan Schmidt, Albrecht Machulla, Tonja Ludwig Maximilians Univ Munchen Munich Germany Univ St Gallen St Gallen Switzerland Univ Oslo Oslo Norway Keio Univ Yokohama Kanagawa Japan Univ Maryland Baltimore MD 21201 USA TU Chemnitz Chemnitz Germany

ISBN: (纸本)9781450394215

Technologies that help users overcome their limitations and integrate with the human body are often termed "human augmentations". Such technologies are nowavailable on the consumer market, potentially supporting people in their everyday activities. To date, there is no systematic understanding of the perception of human augmentations yet. To address this gap and build an understanding of how to design positive experiences with human augmentations, we conducted a mixed-method study of the perception of augmented humans (AHs). We conducted two scenario-based studies: interviews (n = 16) and an online study (n = 506) with participants from four countries. The scenarios include one out of three augmentation categories (sensory, motor, and cognitive) and specify if the augmented person has a disability or not. Overall, results show that the type of augmentation and disability impacted user attitudes towards AHs. We derive design dimensions for creating technological augmentations for a diverse and global audience.

关键词： human augmentation augmented human social attitudes

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Expressiveness, Cost, and Collectivism: How the Design of Preference Languages Shapes Participation in Algorithmic Decision-Making 23

Expressiveness, Cost, and Collectivism: How the Design of Pr...

引用

chi conference on human factors in computing systems (chi)

作者： Robertson, Samantha Nguyen, Tonya Hu, Cathy Albiston, Catherine Nikzad, Afshin Salehi, Niloufar Univ Calif Berkeley Berkeley CA 94720 USA Univ Southern Calif Los Angeles CA USA

ISBN: (纸本)9781450394215

Emerging methods for participatory algorithm design have proposed collecting and aggregating individual stakeholders' preferences to create algorithmic systems that account for those stakeholders' values. Drawing on two years of research across two public school districts in the United States, we study how families and school districts use students' preferences for schools to meet their goals in the context of algorithmic student assignment systems. We find that the design of the preference language, i.e. the structure in which participants must express their needs and goals to the decision-maker, shapes the opportunities for meaningful participation. We define three properties of preference languages expressiveness, cost, and collectivism - and discuss how these factors shape who is able to participate, and the extent to which they are able to effectively communicate their needs to the decision maker. Reflecting on these findings, we offer implications and paths forward for researchers and practitioners who are considering applying a preference-based model for participation in algorithmic decision making.

关键词： Participatory design preference elicitation preference language algorithmic systems

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How can we can create an equitable chi

How can we can create an equitable CHI

引用

Extended Abstracts of the 2023 chi conference on human factors in computing systems, chi EA 2023

作者： Grady, Siobahn Day Bauer, Christine Wehbe, Rina Spiel, Katta Muller, Michael Harrington, Christina School of Library and Information Sciences North Carolina Central University DurhamNC United States Department of Information and Computing Sciences Utrecht University Utrecht Netherlands Computer Science Dalhousie University HalifaxNS Canada Faculty of Informatics Tu Wien Vienna Austria Human Centered Ai Ibm Research CambridgeMA United States Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9781450394222

This panel aims to generate conversation toward creating a more equitable chi. In recognizing our community's hard work thus far, this panel seeks to engage panelists and participants with thought-provoking questions to garner and promote actionable items for the community. We intend to have an open dialogue on allyship, diversity, equity, and inclusion to achieve a chi for all. © 2023 Owner/Author.

关键词： allyship diversity equality equity inclusion

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Statistics for HCI

Statistics for HCI

引用

Extended Abstracts of the 2023 chi conference on human factors in computing systems, chi EA 2023

作者： Dix, Alan Computational Foundry Swansea University Swansea United Kingdom Cardif Metropolitan University Cardif United Kingdom

ISBN: (纸本)9781450394222

Many researchers and practitioners find statistics confusing. This course aims to give attendees an understanding of the meaning of the various statistics they see in papers or need to use in their own work. The course builds on the instructor's previous tutorials and master classes including at chi 2022, and on his recently book "Statistics for HCI: Making Sense of Quantitative Data". The course will focus especially on material you will not find in a conventional textbook or statistics course including aspects of statistical 'craft' skill, and offer attendees an introduction to some of the instructor's extensive online material. © 2023 Owner/Author.

关键词： human computer interaction

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A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on human Preferences in Multi-armed Bandits 23

A Field Test of Bandit Algorithms for Recommendations: Under...

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chi conference on human factors in computing systems (chi)

作者： Liu Leqi Zhou, Giulio Kilinc-Karzan, Fatma Lipton, Zachary C. Montgomery, Alan L. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450394215

Personalized recommender systems suffuse modern life, shaping what media we read and what products we consume. Algorithms powering such systems tend to consist of supervised-learning-based heuristics, such as latent factor models with a variety of heuristically chosen prediction targets. Meanwhile, theoretical treatments of recommendation frequently address the decision-theoretic nature of the problem, including the need to balance exploration and exploitation, via the multi-armed bandits (MABs) framework. However, MAB-based approaches rely heavily on assumptions about human preferences. These preference assumptions are seldom tested using human subject studies, partly due to the lack of publicly available toolkits to conduct such studies. In this work, we conduct a study with crowdworkers in a comics recommendation MABs setting. Each arm represents a comic category, and users provide feedback after each recommendation. We check the validity of core MABs assumptions-that human preferences (reward distributions) are fixed over time-and find that they do not hold. This finding suggests that any MAB algorithm used for recommender systems should account for human preference dynamics. While answering these questions, we provide a flexible experimental framework for understanding human preference dynamics and testing MABs algorithms with human users. The code for our experimental framework and the collected data can be found at https://***/HumainLab/human-bandit-evaluation.

关键词： preference dynamics recommender systems multi-armed bandits

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The Metacognitive Demands and Opportunities of Generative AI 24

The Metacognitive Demands and Opportunities of Generative AI

引用

ACM chi conference on human factors in computing Sytems (chi)

作者： Tankelevitch, Lev Kewenig, Viktor Simkute, Auste Elizabeth, Ava Sarkar, Advait Sellen, Abigail Rintel, Sean Microsoft Res Cambridge England UCL London England Univ Edinburgh Edinburgh Midlothian Scotland Microsoft Redmond WA USA

ISBN: (纸本)9798400703300

Generative AI (GenAI) systems offer unprecedented opportunities for transforming professional and personal work, yet present challenges around prompting, evaluating and relying on outputs, and optimizing workflows. We argue that metacognition-the psychological ability to monitor and control one's thoughts and behavior-offers a valuable lens to understand and design for these usability challenges. Drawing on research in psychology and cognitive science, and recent GenAI user studies, we illustrate how GenAI systems impose metacognitive demands on users, requiring a high degree of metacognitive monitoring and control. We propose these demands could be addressed by integrating metacognitive support strategies into GenAI systems, and by designing GenAI systems to reduce their metacognitive demand by targeting explainability and customizability. Metacognition offers a coherent framework for understanding the usability challenges posed by GenAI, and provides novel research and design directions to advance human-AI interaction.

关键词： Generative AI Metacognition human-AI interaction User Experience Design System Usability

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Interaction of Thoughts: Towards Mediating Task Assignment in human-AI Cooperation with a Capability-Aware Shared Mental Model 23

Interaction of Thoughts: Towards Mediating Task Assignment i...

引用

chi conference on human factors in computing systems (chi)

作者： He, Ziyao Song, Yunpeng Zhou, Shurui Cai, Zhongmin Xi An Jiao Tong Univ MOE KLINNS Lab Xian Shaanxi Peoples R China Univ Toronto Toronto ON Canada

ISBN: (纸本)9781450394215

The existing work on task assignment of human-AI cooperation did not consider the differences between individual team members regarding their capabilities, leading to sub-optimal task completion results. In this work, we propose a capability-aware shared mental model (CASMM) with the components of task grouping and negotiation, which utilize tuples to break down tasks into sets of scenarios relating to difficulties and then dynamically merge the task grouping ideas raised by human and AI through negotiation. We implement a prototype system and a 3-phase user study for the proof of concept via an image labeling task. The result shows building CASMM boosts the accuracy and time efficiency significantly through forming the task assignment close to real capabilities within few iterations. It helps users better understand the capability of AI and themselves. Our method has the potential to generalize to other scenarios such as medical diagnoses and automatic driving in facilitating better human-AI cooperation.

关键词： shared mental model human-AI cooperation task assignment

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