Proceedings of the 24th International Conference on Intelligent User Interfaces最新文献_第7页

Analyzing user's task-driven interaction in mixed reality 分析混合现实中用户的任务驱动交互

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302286

S. Kleanthous, Elena Matsi

引用次数: 0

Explainability scenarios: towards scenario-based XAI design 可解释性场景:面向基于场景的XAI设计

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302317

Christine T. Wolf

引用次数: 86

Background perception and comprehension of symbols conveyed through vibrotactile wearable displays 振动触觉可穿戴显示器传达符号的背景感知与理解

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302282

Granit Luzhnica, Eduardo Veas

{"title":"Background perception and comprehension of symbols conveyed through vibrotactile wearable displays","authors":"Granit Luzhnica, Eduardo Veas","doi":"10.1145/3301275.3302282","DOIUrl":"https://doi.org/10.1145/3301275.3302282","url":null,"abstract":"Previous research has demonstrated the feasibility of conveying vibrotactile encoded information efficiently using wearable devices. Users can understand vibrotactile encoded symbols and complex messages combining such symbols. Such wearable devices can find applicability in many multitasking use cases. Nevertheless, for multitasking, it would be necessary for the perception and comprehension of vibrotactile information to be less attention demanding and not interfere with other parallel tasks. We present a user study which investigates whether high speed vibrotactile encoded messages can be perceived in the background while performing other concurrent attention-demanding primary tasks. The vibrotactile messages used in the study were limited to symbols representing letters of English Alphabet. We observed that users could very accurately comprehend vibrotactile such encoded messages in the background and other parallel tasks did not affect users performance. Additionally, the comprehension of such messages did also not affect the performance of the concurrent primary task as well. Our results promote the use of vibrotactile information transmission to facilitate multitasking.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129034508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

When people and algorithms meet: user-reported problems in intelligent everyday applications 当人和算法相遇:智能日常应用中用户报告的问题

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302262

Malin Eiband, S. Völkel, Daniel Buschek, Sophia Cook, H. Hussmann

引用次数: 45

Walking with adaptive augmented reality workspaces: design and usage patterns 适应增强现实工作空间:设计和使用模式

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-03-17 DOI: 10.1145/3301275.3302278

W. Lages, D. Bowman

引用次数: 36

SAM: a modular framework for self-adapting web menus SAM:用于自适应web菜单的模块化框架

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-01-24 DOI: 10.1145/3301275.3302314

Camille Gobert, Kashyap Todi, G. Bailly, Antti Oulasvirta

引用次数: 11

Explaining models: an empirical study of how explanations impact fairness judgment 解释模型:解释如何影响公平判断的实证研究

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-01-23 DOI: 10.1145/3301275.3302310

Jonathan Dodge, Q. Vera Liao, Yunfeng Zhang, Rachel K. E. Bellamy, Casey Dugan

{"title":"Explaining models: an empirical study of how explanations impact fairness judgment","authors":"Jonathan Dodge, Q. Vera Liao, Yunfeng Zhang, Rachel K. E. Bellamy, Casey Dugan","doi":"10.1145/3301275.3302310","DOIUrl":"https://doi.org/10.1145/3301275.3302310","url":null,"abstract":"Ensuring fairness of machine learning systems is a human-in-the-loop process. It relies on developers, users, and the general public to identify fairness problems and make improvements. To facilitate the process we need effective, unbiased, and user-friendly explanations that people can confidently rely on. Towards that end, we conducted an empirical study with four types of programmatically generated explanations to understand how they impact people's fairness judgments of ML systems. With an experiment involving more than 160 Mechanical Turk workers, we show that: 1) Certain explanations are considered inherently less fair, while others can enhance people's confidence in the fairness of the algorithm; 2) Different fairness problems-such as model-wide fairness issues versus case-specific fairness discrepancies-may be more effectively exposed through different styles of explanation; 3) Individual differences, including prior positions and judgment criteria of algorithmic fairness, impact how people react to different styles of explanation. We conclude with a discussion on providing personalized and adaptive explanations to support fairness judgments of ML systems.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122066089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27

Automated rationale generation: a technique for explainable AI and its effects on human perceptions 自动原理生成:一种可解释的人工智能及其对人类感知的影响的技术

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2019-01-11 DOI: 10.1145/3301275.3302316

Upol Ehsan, Pradyumna Tambwekar, Larry Chan, Brent Harrison, Mark O. Riedl

{"title":"Automated rationale generation: a technique for explainable AI and its effects on human perceptions","authors":"Upol Ehsan, Pradyumna Tambwekar, Larry Chan, Brent Harrison, Mark O. Riedl","doi":"10.1145/3301275.3302316","DOIUrl":"https://doi.org/10.1145/3301275.3302316","url":null,"abstract":"Automated rationale generation is an approach for real-time explanation generation whereby a computational model learns to translate an autonomous agent's internal state and action data representations into natural language. Training on human explanation data can enable agents to learn to generate human-like explanations for their behavior. In this paper, using the context of an agent that plays Frogger, we describe (a) how to collect a corpus of explanations, (b) how to train a neural rationale generator to produce different styles of rationales, and (c) how people perceive these rationales. We conducted two user studies. The first study establishes the plausibility of each type of generated rationale and situates their user perceptions along the dimensions of confidence, humanlike-ness, adequate justification, and understandability. The second study further explores user preferences between the generated rationales with regard to confidence in the autonomous agent, communicating failure and unexpected behavior. Overall, we find alignment between the intended differences in features of the generated rationales and the perceived differences by users. Moreover, context permitting, participants preferred detailed rationales to form a stable mental model of the agent's behavior.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131183870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 178

Smell Pittsburgh: community-empowered mobile smell reporting system 气味匹兹堡:社区授权的移动气味报告系统

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2018-10-25 DOI: 10.1145/3301275.3302293

Yen-Chia Hsu, Jennifer L. Cross, P. Dille, Michael Tasota, Beatrice Dias, Randy Sargent, Ting-Hao 'Kenneth' Huang, I. Nourbakhsh

{"title":"Smell Pittsburgh: community-empowered mobile smell reporting system","authors":"Yen-Chia Hsu, Jennifer L. Cross, P. Dille, Michael Tasota, Beatrice Dias, Randy Sargent, Ting-Hao 'Kenneth' Huang, I. Nourbakhsh","doi":"10.1145/3301275.3302293","DOIUrl":"https://doi.org/10.1145/3301275.3302293","url":null,"abstract":"Urban air pollution has been linked to various human health considerations, including cardiopulmonary diseases. Communities who suffer from poor air quality often rely on experts to identify pollution sources due to the lack of accessible tools. Taking this into account, we developed Smell Pittsburgh, a system that enables community members to report odors and track where these odors are frequently concentrated. All smell report data are publicly accessible online. These reports are also sent to the local health department and visualized on a map along with air quality data from monitoring stations. This visualization provides a comprehensive overview of the local pollution landscape. Additionally, with these reports and air quality data, we developed a model to predict upcoming smell events and send push notifications to inform communities. Our evaluation of this system demonstrates that engaging residents in documenting their experiences with pollution odors can help identify local air pollution patterns, and can empower communities to advocate for better air quality.","PeriodicalId":153096,"journal":{"name":"Proceedings of the 24th International Conference on Intelligent User Interfaces","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134159871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

What can AI do for me?: evaluating machine learning interpretations in cooperative play 人工智能能为我做什么?:评估机器学习在合作游戏中的解释

Proceedings of the 24th International Conference on Intelligent User Interfaces Pub Date : 2018-10-23 DOI: 10.1145/3301275.3302265

Shi Feng, Jordan L. Boyd-Graber

引用次数: 106