Ling Qiu, B. Kanski, Shawna Doerksen, R. Winkels, K. Schmitz, Saeed Abdullah
Women with metastatic breast cancer (MBC) face serious physiological and psychosocial challenges. The management of this chronic, incurable condition requires long-term care coordination. Traditional clinical methods do not often provide adequate and personalized support for these individuals. In this project, we aim to use smart speakers to provide supportive care interventions to improve the quality of life for women with MBC. Specifically, we have developed Nurse AMIE (Addressing Metastatic Individuals Everyday) by leveraging the Amazon Alexa to remotely deliver validated interventions. We believe that voice interactions can significantly lower the barrier to interact with remote intervention technologies for this population. In a pilot study, we deployed Nurse AMIE for 14 days over 6 women with MBC. Based on the collected data, this paper discusses the feasibility, acceptability, and future directions of Nurse AMIE. To the best of our knowledge, this is the first study to use smart speakers to support women with MBC.
{"title":"Nurse AMIE: Using Smart Speakers to Provide Supportive Care Intervention for Women with Metastatic Breast Cancer","authors":"Ling Qiu, B. Kanski, Shawna Doerksen, R. Winkels, K. Schmitz, Saeed Abdullah","doi":"10.1145/3411763.3451827","DOIUrl":"https://doi.org/10.1145/3411763.3451827","url":null,"abstract":"Women with metastatic breast cancer (MBC) face serious physiological and psychosocial challenges. The management of this chronic, incurable condition requires long-term care coordination. Traditional clinical methods do not often provide adequate and personalized support for these individuals. In this project, we aim to use smart speakers to provide supportive care interventions to improve the quality of life for women with MBC. Specifically, we have developed Nurse AMIE (Addressing Metastatic Individuals Everyday) by leveraging the Amazon Alexa to remotely deliver validated interventions. We believe that voice interactions can significantly lower the barrier to interact with remote intervention technologies for this population. In a pilot study, we deployed Nurse AMIE for 14 days over 6 women with MBC. Based on the collected data, this paper discusses the feasibility, acceptability, and future directions of Nurse AMIE. To the best of our knowledge, this is the first study to use smart speakers to support women with MBC.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122530566","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}
We propose a novel fingering estimation method that allows a player to use any wind instrument as a music controller by attaching a single microphone and loudspeaker-embedded mouthpiece. The loudspeaker plays white noise continuously while the fingerings are estimated in real-time based on the sound pressure recorded at the end of the instrument. Our method addresses a major problem of conventional music controllers: differences in the tactile feel of keys compared to the player’s own instrument. We demonstrated that the proposed method accurately estimated fingerings on a saxophone with promising performance (a 1.05 % misclassification rate), satisfying the low-latency feedback required in the context of musical performance.
{"title":"Turning Your Wind Instrument into a Music Controller: Real-time Fingering Estimation by Classifying Reflected White Noise","authors":"Naoyuki Terashita, Kyoichi Sugahara, Yosuke Terashita","doi":"10.1145/3411763.3451719","DOIUrl":"https://doi.org/10.1145/3411763.3451719","url":null,"abstract":"We propose a novel fingering estimation method that allows a player to use any wind instrument as a music controller by attaching a single microphone and loudspeaker-embedded mouthpiece. The loudspeaker plays white noise continuously while the fingerings are estimated in real-time based on the sound pressure recorded at the end of the instrument. Our method addresses a major problem of conventional music controllers: differences in the tactile feel of keys compared to the player’s own instrument. We demonstrated that the proposed method accurately estimated fingerings on a saxophone with promising performance (a 1.05 % misclassification rate), satisfying the low-latency feedback required in the context of musical performance.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114491432","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}
Retail experiences have started adopting Augmented Reality (AR) as a tool to let customers see products in their space before committing to a purchase. Although online retailers use high resolution 3D models to create onsite imagery, limitations in the rendering capabilities of phones require them to optimize models for real-time use, diminishing the visual quality of the experience and widening the gap between what the customer thinks they are buying and what they get. We present Fused Photo, a system that leverages AR to capture the customer’s spatial context and recreate it in a remote rendering environment that then composites photorealistic images of products onto their space. Results show that Fused Photos outperform other AR visualizations in the market both in realism and ability to represent a product’s appearance, while being comparable in quality to photorealistic renders staged manually by artists.
{"title":"Fused Photo: Augmented Reality Staging for Photorealistic Visualization in Online Home Retail","authors":"C. Vazquez, Nicole Tan, Shrenik Sadalgi","doi":"10.1145/3411763.3451723","DOIUrl":"https://doi.org/10.1145/3411763.3451723","url":null,"abstract":"Retail experiences have started adopting Augmented Reality (AR) as a tool to let customers see products in their space before committing to a purchase. Although online retailers use high resolution 3D models to create onsite imagery, limitations in the rendering capabilities of phones require them to optimize models for real-time use, diminishing the visual quality of the experience and widening the gap between what the customer thinks they are buying and what they get. We present Fused Photo, a system that leverages AR to capture the customer’s spatial context and recreate it in a remote rendering environment that then composites photorealistic images of products onto their space. Results show that Fused Photos outperform other AR visualizations in the market both in realism and ability to represent a product’s appearance, while being comparable in quality to photorealistic renders staged manually by artists.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114547148","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}
Jiali Zhang, He Feng, Chee Jen Ngeh, J. Raiti, Yuntao Wang, Paulo Gonçalves, Gulnara Sarymbekova, Linda Wagner, J. James, Paul B. Albee, Jayasakthi Thiagarajan
Smart Helmet is a new wearable device to monitor wildland firefighters’ real-time bio-signal data and alert potential health issues, i.e., dehydration. In this paper, we applied the human-centered design method to develop Smart Helmet for firefighters. We initially conducted multiple rounds of primary research to collect user needs and the deployment constraints by interviewing 80 firefighters. Targeted on dehydration caused by heat exhaustion and overexertion, we developed a smart helmet prototype, named FireWorks, with an array of sensors collecting the firefighter’s bio-signals, including body temperature, heart rate, and motions. When abnormal bio-signal levels are detected, the alert system will notify the firefighter and their supervisor. The notification is achieved by an on-device algorithm that predicts imminent health risks. Further, we designed a mobile application to display real-time and historical bio-signal data as well as alert users about potential dehydration issues. In the end, we ran user evaluation studies and iterated the prototype based on user feedback, and we ran the functional evaluation to make sure all the implemented functions work properly.
{"title":"Designing a Smart Helmet for Wildland Firefighters to Avoid Dehydration by Monitoring Bio-signals","authors":"Jiali Zhang, He Feng, Chee Jen Ngeh, J. Raiti, Yuntao Wang, Paulo Gonçalves, Gulnara Sarymbekova, Linda Wagner, J. James, Paul B. Albee, Jayasakthi Thiagarajan","doi":"10.1145/3411763.3451772","DOIUrl":"https://doi.org/10.1145/3411763.3451772","url":null,"abstract":"Smart Helmet is a new wearable device to monitor wildland firefighters’ real-time bio-signal data and alert potential health issues, i.e., dehydration. In this paper, we applied the human-centered design method to develop Smart Helmet for firefighters. We initially conducted multiple rounds of primary research to collect user needs and the deployment constraints by interviewing 80 firefighters. Targeted on dehydration caused by heat exhaustion and overexertion, we developed a smart helmet prototype, named FireWorks, with an array of sensors collecting the firefighter’s bio-signals, including body temperature, heart rate, and motions. When abnormal bio-signal levels are detected, the alert system will notify the firefighter and their supervisor. The notification is achieved by an on-device algorithm that predicts imminent health risks. Further, we designed a mobile application to display real-time and historical bio-signal data as well as alert users about potential dehydration issues. In the end, we ran user evaluation studies and iterated the prototype based on user feedback, and we ran the functional evaluation to make sure all the implemented functions work properly.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122103897","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}
The perceived emotional intelligence of a conversational agent (CA) can significantly impact people’s interaction with the CA. Prior research applies text-based sentiment analysis and emotional response generation to improve CAs’ emotional intelligence. However, acoustic features in speech containing rich contexts are underexploited. In this work, we designed and implemented an emotionally aware CA, called HUE (Heard yoUr Emotion) that stylized responses with emotion regulation strategies and empathetic interjections. We conducted a user study with 75 participants to evaluate their perceived emotional intelligence (PEI) of HUE by having them observe conversations between people and HUE in different emotional scenarios. Our results show that participants’ PEI was significantly higher with the acoustic features than without.
{"title":"Enhancing the Perceived Emotional Intelligence of Conversational Agents through Acoustic Cues","authors":"Jiaxiong Hu, Yun Huang, Xiaozhu Hu, Ying-Qing Xu","doi":"10.1145/3411763.3451660","DOIUrl":"https://doi.org/10.1145/3411763.3451660","url":null,"abstract":"The perceived emotional intelligence of a conversational agent (CA) can significantly impact people’s interaction with the CA. Prior research applies text-based sentiment analysis and emotional response generation to improve CAs’ emotional intelligence. However, acoustic features in speech containing rich contexts are underexploited. In this work, we designed and implemented an emotionally aware CA, called HUE (Heard yoUr Emotion) that stylized responses with emotion regulation strategies and empathetic interjections. We conducted a user study with 75 participants to evaluate their perceived emotional intelligence (PEI) of HUE by having them observe conversations between people and HUE in different emotional scenarios. Our results show that participants’ PEI was significantly higher with the acoustic features than without.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129596142","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}
Vaishnavi Mande, Abraham Glasser, Becca Dingman, Matt Huenerfauth
Personal-assistant devices like Amazon Alexa and Google Assistant are increasingly popular among consumers. Users activate these systems through some type of wake-up approach, e.g. using a wake-word “Alexa” or “Ok, Google.” Voice-based interaction poses accessibility barriers for Deaf and Hard of Hearing (DHH) users, and technologies for sign-language recognition are improving. We therefore explore wake-up interactions for DHH users for potential personal assistant devices that understand sign language commands. Interviews with DHH users (N=21) motivated the design of six wake-up approaches, and we produced video prototypes demonstrating each using a Wizard-of-Oz approach. These prototypes were evaluated in a follow-up study in which DHH users (N=12) identified factors that influenced their preference among approaches. This study contributes empirical knowledge about DHH ASL signers’ preferences and concerns with wake-up interaction, thereby providing guidance for future designers of these systems.
{"title":"Deaf Users’ Preferences Among Wake-Up Approaches during Sign-Language Interaction with Personal Assistant Devices","authors":"Vaishnavi Mande, Abraham Glasser, Becca Dingman, Matt Huenerfauth","doi":"10.1145/3411763.3451592","DOIUrl":"https://doi.org/10.1145/3411763.3451592","url":null,"abstract":"Personal-assistant devices like Amazon Alexa and Google Assistant are increasingly popular among consumers. Users activate these systems through some type of wake-up approach, e.g. using a wake-word “Alexa” or “Ok, Google.” Voice-based interaction poses accessibility barriers for Deaf and Hard of Hearing (DHH) users, and technologies for sign-language recognition are improving. We therefore explore wake-up interactions for DHH users for potential personal assistant devices that understand sign language commands. Interviews with DHH users (N=21) motivated the design of six wake-up approaches, and we produced video prototypes demonstrating each using a Wizard-of-Oz approach. These prototypes were evaluated in a follow-up study in which DHH users (N=12) identified factors that influenced their preference among approaches. This study contributes empirical knowledge about DHH ASL signers’ preferences and concerns with wake-up interaction, thereby providing guidance for future designers of these systems.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129048651","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}
M. A. Devito, Caitlin Lustig, Ellen Simpson, K. Allison, Tya S. Chuanromanee, Katta Spiel, Amy J. Ko, J. Rode, Brianna Dym, Michael J. Muller, M. Scheuerman, A. Walker, Jed R. Brubaker, Alex A. Ahmed
As Queer Human-Computer Interaction (HCI) becomes an established part of the larger field, both in terms of research on and with queer populations and in terms of employing queering theories and methods, the role of queer researchers has become a timely topic of discussion. However, these discussions have largely centered around member-researcher status and positionality when working with queer populations. Based on insights gathered at multiple ACM events over the past two years, we identified two pressing issues: (1) we need to better support queer people doing HCI research not specific to queer populations, and (2) we need to identify how to best support member-researchers in leading Queer HCI while including collaborators beyond the queer community. This Special Interest Group (SIG) aims to directly address these challenges by convening a broad community of queer researchers and allies, working not only on explicitly-queer topics but across a broad range of HCI topics.
{"title":"Queer in HCI: Strengthening the Community of LGBTQIA+ Researchers and Research","authors":"M. A. Devito, Caitlin Lustig, Ellen Simpson, K. Allison, Tya S. Chuanromanee, Katta Spiel, Amy J. Ko, J. Rode, Brianna Dym, Michael J. Muller, M. Scheuerman, A. Walker, Jed R. Brubaker, Alex A. Ahmed","doi":"10.1145/3411763.3450403","DOIUrl":"https://doi.org/10.1145/3411763.3450403","url":null,"abstract":"As Queer Human-Computer Interaction (HCI) becomes an established part of the larger field, both in terms of research on and with queer populations and in terms of employing queering theories and methods, the role of queer researchers has become a timely topic of discussion. However, these discussions have largely centered around member-researcher status and positionality when working with queer populations. Based on insights gathered at multiple ACM events over the past two years, we identified two pressing issues: (1) we need to better support queer people doing HCI research not specific to queer populations, and (2) we need to identify how to best support member-researchers in leading Queer HCI while including collaborators beyond the queer community. This Special Interest Group (SIG) aims to directly address these challenges by convening a broad community of queer researchers and allies, working not only on explicitly-queer topics but across a broad range of HCI topics.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129367299","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}
Recent advancements in artificial intelligence (AI) create new opportunities for implementing a wide range of intelligent user interfaces. Speech-based interfaces, chatbots, visual recognition of users and objects, recommender systems, and adaptive user interfaces are examples that have majored over the last 10 years due to new approaches in machine learning (ML). Modern ML-techniques outperform in many domains of previous approaches and enable new applications. Today, it is possible to run models efficiently on various devices, including PCs, smartphones, and embedded systems. Leveraging the potential of artificial intelligence and combining them with human-computer interaction approaches allows developing intelligent user interfaces supporting users better than ever before. This course introduces participants to terms and concepts relevant in AI and ML. Using examples and application scenarios, we practically show how intelligent user interfaces can be designed and implemented. In particular, we look at how to create optimized keyboards, use natural language processing for text and speech-based interaction, and how to implement a recommender system for movies. Thus, this course aims to introduce participants to a set of machine learning tools that will enable them to build their own intelligent user interfaces. This course will include video based lectures to introduce concepts and algorithms supported by practical and interactive exercises using python notebooks.
{"title":"Introduction to Intelligent User Interfaces","authors":"A. Schmidt, Sven Mayer, D. Buschek","doi":"10.1145/3411763.3445021","DOIUrl":"https://doi.org/10.1145/3411763.3445021","url":null,"abstract":"Recent advancements in artificial intelligence (AI) create new opportunities for implementing a wide range of intelligent user interfaces. Speech-based interfaces, chatbots, visual recognition of users and objects, recommender systems, and adaptive user interfaces are examples that have majored over the last 10 years due to new approaches in machine learning (ML). Modern ML-techniques outperform in many domains of previous approaches and enable new applications. Today, it is possible to run models efficiently on various devices, including PCs, smartphones, and embedded systems. Leveraging the potential of artificial intelligence and combining them with human-computer interaction approaches allows developing intelligent user interfaces supporting users better than ever before. This course introduces participants to terms and concepts relevant in AI and ML. Using examples and application scenarios, we practically show how intelligent user interfaces can be designed and implemented. In particular, we look at how to create optimized keyboards, use natural language processing for text and speech-based interaction, and how to implement a recommender system for movies. Thus, this course aims to introduce participants to a set of machine learning tools that will enable them to build their own intelligent user interfaces. This course will include video based lectures to introduce concepts and algorithms supported by practical and interactive exercises using python notebooks.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129667769","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}
Code puzzles are an increasingly popular approach to introducing programming to young learners. Today, code puzzles are predominantly introduced through static puzzle sequences with increasing difficulty. However, adaptive systems in other domains have improved learning efficiency. This paper takes a step towards developing adaptive code puzzle systems based on controlling learners’ cognitive load. We conducted a study comparing static code puzzle pathways and adaptive pathways that predict cognitive load on future puzzles. While the trialled adaptive recommendation policy did not result in better learning, our findings point us towards a different policy which may have a greater effect on learner experience. In addition, we identify predictors of student dropout, and use our experimental data to quantify learners’ puzzle-solving experiences into 7 principal component properties and use these factors to suggest approaches for future adaptive systems.
{"title":"Quantifying Novice Behavior, Experience, and Mental Effort in Code Puzzle Pathways","authors":"John Allen, Caitlin L. Kelleher","doi":"10.1145/3411763.3451752","DOIUrl":"https://doi.org/10.1145/3411763.3451752","url":null,"abstract":"Code puzzles are an increasingly popular approach to introducing programming to young learners. Today, code puzzles are predominantly introduced through static puzzle sequences with increasing difficulty. However, adaptive systems in other domains have improved learning efficiency. This paper takes a step towards developing adaptive code puzzle systems based on controlling learners’ cognitive load. We conducted a study comparing static code puzzle pathways and adaptive pathways that predict cognitive load on future puzzles. While the trialled adaptive recommendation policy did not result in better learning, our findings point us towards a different policy which may have a greater effect on learner experience. In addition, we identify predictors of student dropout, and use our experimental data to quantify learners’ puzzle-solving experiences into 7 principal component properties and use these factors to suggest approaches for future adaptive systems.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116271111","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}
Sandy J. J. Gould, L. Chuang, I. Iacovides, Diego Garaialde, Marta E. Cecchinato, Benjamin R. Cowan, A. Cox
A lot of academic and industrial HCI work has focused on making interactions easier and less effortful. As the potential risks of optimising for effortlessness have crystallised in systems designed to take advantage of the way human attention and cognition works, academic researchers and industrial practitioners have wondered whether increasing the ‘friction’ in interactions, making them more effortful might make sense in some contexts. The goal of this special interest group is to provide a forum for researchers and practitioners to discuss and advance the theoretical underpinnings of designed friction, the relation of friction to other design paradigms, and to identify the domains and interaction flows that frictions might best suit. During the SIG, attendees will attempt to prioritise a set of research questions about frictions in HCI.
{"title":"A Special Interest Group on Designed and Engineered Friction in Interaction","authors":"Sandy J. J. Gould, L. Chuang, I. Iacovides, Diego Garaialde, Marta E. Cecchinato, Benjamin R. Cowan, A. Cox","doi":"10.1145/3411763.3450404","DOIUrl":"https://doi.org/10.1145/3411763.3450404","url":null,"abstract":"A lot of academic and industrial HCI work has focused on making interactions easier and less effortful. As the potential risks of optimising for effortlessness have crystallised in systems designed to take advantage of the way human attention and cognition works, academic researchers and industrial practitioners have wondered whether increasing the ‘friction’ in interactions, making them more effortful might make sense in some contexts. The goal of this special interest group is to provide a forum for researchers and practitioners to discuss and advance the theoretical underpinnings of designed friction, the relation of friction to other design paradigms, and to identify the domains and interaction flows that frictions might best suit. During the SIG, attendees will attempt to prioritise a set of research questions about frictions in HCI.","PeriodicalId":265192,"journal":{"name":"Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124482728","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}
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