huashen218/convxai-cia-dataset huggingface dataset:
Title: Exploring the Design Space of User-System Communication for Smart-home Routine Assistants
Authors: family: Chiang
given: Yi-Shyuan; family: Chang
given: Ruei-Che; family: Chuang
given: Yi-Lin; family: Chou
given: Shih-Ya; family: Lee
given: Hao-Ping; family: Lin
given: I-Ju; family: Jiang Chen
given: Jian-Hua; family: Chang
given: Yung-Ju
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: AI-enabled smart-home agents that automate household routines are increasingly viable, but the design space of how and what such systems should communicate with their users remains underexplored. Through a user-enactment study, we identified various interpretations of and feelings toward such a system's confidence in its automated acts. That confidence and their own mental models influenced what and how the participants wanted the system to communicate, as well as how they would assess, diagnose, and subsequently improve it. Automated acts resulted from false predictions were not generally considered improper, provided that they were perceived as reasonable or potentially useful. The participants' improvement strategies were of four general types, all of which will be discussed. Factors affecting their preferred levels of involvement in automated acts and their interest in system confidence were also identified. We conclude by making practical design recommendations for the user-system communication design spaces of smart-home routine assistants.
Title: A Literature Review of Quantitative Persona Creation
Authors: family: Salminen
given: Joni; family: Guan
given: Kathleen; family: Jung
given: Soon-Gyo; family: Chowdhury
given: Shammur A.; family: Jansen
given: Bernard J.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Quantitative persona creation (QPC) has tremendous potential, as HCI researchers and practitioners can leverage user data from online analytics and digital media platforms to better understand their users and customers. However, there is a lack of a systematic overview of the QPC methods and progress made, with no standard methodology or known best practices. To address this gap, we review 49 QPC research articles from 2005 to 2019. Results indicate three stages of QPC research: Emergence, Diversification, and Sophistication. Sharing resources, such as datasets, code, and algorithms, is crucial to achieving the next stage (Maturity). For practitioners, we provide guiding questions for assessing QPC readiness in organizations.
Title: Digital Ventriloquism: Giving Voice to Everyday Objects
Authors: family: Iravantchi
given: Yasha; family: Goel
given: Mayank; family: Harrison
given: Chris
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Smart speakers with voice agents are becoming increasingly common. However, the agent's voice always emanates from the device, even when that information is contextually and spatially relevant elsewhere. Digital Ventriloquism allows smart speakers to render sound onto everyday objects, such that it appears they are speaking and are interactive. This can be achieved without any modification of objects or the environment. For this, we used a highly directional pan-tilt ultrasonic array. By modulating a 40 kHz ultrasonic signal, we can emit sound that is inaudible "in flight" and demodulates to audible frequencies when impacting a surface through acoustic parametric interaction. This makes it appear as though the sound originates from an object and not the speaker. We ran a study in which we projected speech onto five objects in three environments, and found that participants were able to correctly identify the source object 92% of the time and correctly repeat the spoken message 100% of the time, demonstrating our digital ventriloquy is both directional and intelligible.
Title: Affective State Prediction Based on Semi-Supervised Learning from Smartphone Touch Data
Authors: family: Wampfler
given: Rafael; family: Klingler
given: Severin; family: Solenthaler
given: Barbara; family: Schinazi
given: Victor R.; family: Gross
given: Markus
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Gaining awareness of the user's affective states enables smartphones to support enriched interactions that are sensitive to the user's context. To accomplish this on smartphones, we propose a system that analyzes the user's text typing behavior using a semi-supervised deep learning pipeline for predicting affective states measured by valence, arousal, and dominance. Using a data collection study with 70 participants on text conversations designed to trigger different affective responses, we developed a variational auto-encoder to learn efficient feature embeddings of two-dimensional heat maps generated from touch data while participants engaged in these conversations. Using the learned embedding in a cross-validated analysis, our system predicted three levels (low, medium, high) of valence (AUC up to 0.84), arousal (AUC up to 0.82), and dominance (AUC up to 0.82). These results demonstrate the feasibility of our approach to accurately predict affective states based only on touch data.
Title: Glissade: Generating Balance Shifting Feedback to Facilitate Auxiliary Digital Pen Input
Authors: family: Huang
given: Kai-Chieh; family: Sun
given: Chen-Kuo; family: Huang
given: Da-Yuan; family: Chen
given: Yu-Chun; family: Chang
given: Ruei-Che; family: Hsu
given: Shuo-wen; family: Yang
given: Chih-Yun; family: Chen
given: Bing-Yu
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: This paper introduces Glissade, a digital pen that generates balance shifting feedback by changing the weight distribution of the pen. A pulley system shifts a brass mass inside the pen to change the pen's center of mass and moment of inertia. When the mass is stationary, the pen delivers a constant yet natural sensation of weight, which can be used to convey a status. The pen can also generate a variety of haptic clues by actuating the mass according to the tilt or rotation of the pen, two commonly-used auxiliary pen input channels. Glissade demonstrates new possibilities that balance shifting feedback can bring to digital pen interactions. We validated the usability of this feedback by determining the recognizability of six balance patterns – a mix of static and dynamic patterns chosen based on our design considerations – in two controlled experiments. The results show that, on average, the participants could distinguish between the patterns with a 94.25% accuracy. At the end, we demonstrate a set of novel interactions enabled by Glissade and discuss the directions for future research.
Title: Ambiguity-aware AI Assistants for Medical Data Analysis
Authors: family: Schaekermann
given: Mike; family: Beaton
given: Graeme; family: Sanoubari
given: Elaheh; family: Lim
given: Andrew; family: Larson
given: Kate; family: Law
given: Edith
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Artificial intelligence (AI) assistants for clinical decision making show increasing promise in medicine. However, medical assessments can be contentious, leading to expert disagreement. This raises the question of how AI assistants should be designed to handle the classification of ambiguous cases. Our study compared two AI assistants that provide classification labels for medical time series data along with quantitative uncertainty estimates: conventional vs. ambiguity-aware. We simulated our ambiguity-aware AI based on real-world expert discussions to highlight cases likely to lead to expert disagreement, and to present arguments for conflicting classification choices. Our results demonstrate that ambiguity-aware AI can alter expert workflows by significantly increasing the proportion of contentious cases reviewed. We also found that the relevance of AI-provided arguments (selected from guidelines either randomly or by experts) affected experts' accuracy at revising AI-suggested labels. Our work contributes a novel perspective on the design of AI for contentious clinical assessments.
Title: Becoming a Robot - Overcoming Anthropomorphism with Techno-Mimesis
Authors: family: Dörrenbächer
given: Judith; family: Löffler
given: Diana; family: Hassenzahl
given: Marc
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Employing anthropomorphism in physical appearance and behavior is the most widespread strategy for designing social robots. In the present paper, we argue that imitating humans impedes the full exploration of robots' social abilities. In fact, their very 'thingness' (e.g., sensors, rationality) is able to create 'superpowers' that go beyond human abilities, such as endless patience. To better identify these special abilities, we develop a performative method called 'Techno-Mimesis' and explore it in a series of workshops with robot designers. Specifically, we create 'prostheses' to allow designers to transform themselves into their future robot to experience use cases from the robot's perspective, e.g., 'seeing' with a distance sensor rather than with eyes. This imperfect imitation helps designers to experience being human and being robot at the same time, making differences apparent and facilitating the discovery of a number of potential physical, cognitive, and communicational robotic superpowers.
Title: Understanding what you feel: A Mobile Audio-Tactile System for Graphics Used at Schools with Students with Visual Impairment
Authors: family: Melfi
given: Giuseppe; family: Müller
given: Karin; family: Schwarz
given: Thorsten; family: Jaworek
given: Gerhard; family: Stiefelhagen
given: Rainer
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: A lot of information is nowadays presented graphically. However, students with blindness do not have access to visual information. Providing an alternative text is not always the appropriate solution as exploring graphics to discover information independently is a fundamental part of the learning process. In this work, we introduce a mobile audio-tactile learning environment, which facilitates the incorporation of real educational material. We evaluate our system by comparing three methods of interaction with tactile graphics: A tactile graphic augmented by (1) a document with key index information in Braille, (2) a digital document with key index information and (3) the TPad system, an audio-tactile solution meeting the specific needs within the school context. Our study shows that the TPad system is suitable for educational environments. Moreover, compared to the other methods TPad is faster to explore tactile graphics and it suggests a promising effect on the memorization of information.
Title: Digital-Enabled Last Mile: A Study of Passenger Trips in Rural, Low-density Populated Areas
Authors: family: Kjærup
given: Maria; family: Skov
given: Mikael B.; family: Agerholm
given: Niels
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Public transportation in rural areas is difficult due to low numbers of passengers and diverse needs, also reflected in the last mile problem that points to the distance to access transportation hubs in order to connect with core networks of transportation. In this paper, we study public transportation in rural areas using a digital-enabled, demand-responsive service called Plustur. This service was recently introduced as an effort to increase mobility in underserved rural areas by creating routes ad-hoc to answer to the last mile(s). We study how passengers and drivers understand Plustur, as well as experience the role of passenger. Our findings show that Plustur is viewed as a benefit for autonomy of mobility in rural areas, however is lacking in addressing integration of modes of mobilities, flexibility and spontaneous trips. We contribute with design implications for digital multimodal mobility services.
Title: Integrating the Digital and the Traditional to Deliver Therapy for Depression: Lessons from a Pragmatic Study
Authors: family: Stawarz
given: Katarzyna; family: Preist
given: Chris; family: Tallon
given: Deborah; family: Thomas
given: Laura; family: Turner
given: Katrina; family: Wiles
given: Nicola; family: Kessler
given: David; family: Shafran
given: Roz; family: Coyle
given: David
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Traditional approaches to psychotherapy emphasise face-to-face contact between patients and therapists. In contrast, current computerised approaches tend to minimise this contact. This can limit the range of mental health difficulties for which computerised approaches are effective. Here, we explore an alternative approach that integrates face-to-face contact, electronic contact, online collaboration, and support for between-session activities. Our discussion is grounded in the design of a platform to deliver psychotherapy for depression. We report findings of an 11-month pragmatic study in which 17 patients received treatment for depression via the platform. Results show how design decisions had a significant impact on the dynamics of therapeutic sessions and the establishment of patient-therapist relationships. For example, the use of instant messaging for synchronous, in-session contact slowed communication, but also provided a valuable space for reflection and helped to maintain session focus. We discuss the impact of flexibility and the potential of integrated approaches to both enhance and reduce patient engagement.
Title: "It's a scavenger hunt": Usability of Websites' Opt-Out and Data Deletion Choices
Authors: family: Habib
given: Hana; family: Pearman
given: Sarah; family: Wang
given: Jiamin; family: Zou
given: Yixin; family: Acquisti
given: Alessandro; family: Cranor
given: Lorrie Faith; family: Sadeh
given: Norman; family: Schaub
given: Florian
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: We conducted an in-lab user study with 24 participants to explore the usefulness and usability of privacy choices offered by websites. Participants were asked to find and use choices related to email marketing, targeted advertising, or data deletion on a set of nine websites that differed in terms of where and how these choices were presented. They struggled with several aspects of the interaction, such as selecting the correct page from a site's navigation menu and understanding what information to include in written opt-out requests. Participants found mechanisms located in account settings pages easier to use than options contained in privacy policies, but many still consulted help pages or sent email to request assistance. Our findings indicate that, despite their prevalence, privacy choices like those examined in this study are difficult for consumers to exercise in practice. We provide design and policy recommendations for making these website opt-out and deletion choices more useful and usable for consumers.
Title: TangibleCircuits: An Interactive 3D Printed Circuit Education Tool for People with Visual Impairments
Authors: family: Davis
given: Josh Urban; family: Wu
given: Te-Yen; family: Shi
given: Bo; family: Lu
given: Hanyi; family: Panotopoulou
given: Athina; family: Whiting
given: Emily; family: Yang
given: Xing-Dong
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: We present a novel haptic and audio feedback device that allows blind and visually impaired (BVI) users to understand circuit diagrams. TangibleCircuits allows users to interact with a 3D printed tangible model of a circuit which provides audio tutorial directions while being touched. Our system comprises an automated parsing algorithm which extracts 3D printable models as well as an audio interfaces from a Fritzing diagram. To better understand the requirements of designing technology to assist BVI users in learning hardware computing, we conducted a series of formative inquiries into the accessibility limitations of current circuit tutorial technologies. In addition, we derived insights and design considerations gleaned from conducting a formal comparative user study to understand the effectiveness of TangibleCircuits as a tutorial system. We found that BVI users were better able to understand the geometric, spatial and structural circuit information using TangibleCircuits, as well as enjoyed learning with our tool.
Title: Music Creation by Example
Authors: family: Frid
given: Emma; family: Gomes
given: Celso; family: Jin
given: Zeyu
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Short online videos have become the dominating media on social platforms. However, finding suitable music to accompany videos can be a challenging task to some video creators, due to copyright constraints, limitations in search engines, and required audio-editing expertise. One possible solution to these problems is to use AI music generation. In this paper we present a user interface (UI) paradigm that allows users to input a song to an AI engine and then interactively regenerate and mix AI-generated music. To arrive at this design, we conducted user studies with a total of 104 video creators at several stages of our design and development process. User studies supported the effectiveness of our approach and provided valuable insights about human-AI interaction as well as the design and evaluation of mixed-initiative interfaces in creative practice.
Title: Infrastructural Speculations: Tactics for Designing and Interrogating Lifeworlds
Authors: family: Wong
given: Richmond Y.; family: Khovanskaya
given: Vera; family: Fox
given: Sarah E.; family: Merrill
given: Nick; family: Sengers
given: Phoebe
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: This paper introduces "infrastructural speculations," an orientation toward speculative design that considers the complex and long-lived relationships of technologies with broader systems, beyond moments of immediate invention and design. As modes of speculation are increasingly used to interrogate questions of broad societal concern, it is pertinent to develop an orientation that foregrounds the "lifeworld" of artifacts-the social, perceptual, and political environment in which they exist. While speculative designs often imply a lifeworld, infrastructural speculations place lifeworlds at the center of design concern, calling attention to the cultural, regulatory, environmental, and repair conditions that enable and surround particular future visions. By articulating connections and affinities between speculative design and infrastructure studies research, we contribute a set of design tactics for producing infrastructural speculations. These tactics help design researchers interrogate the complex and ongoing entanglements among technologies, institutions, practices, and systems of power when gauging the stakes of alternate lifeworlds.
Title: The Effectiveness of Visual and Audio Wayfinding Guidance on Smartglasses for People with Low Vision
Authors: family: Zhao
given: Yuhang; family: Kupferstein
given: Elizabeth; family: Rojnirun
given: Hathaitorn; family: Findlater
given: Leah; family: Azenkot
given: Shiri
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Wayfinding is a critical but challenging task for people who have low vision, a visual impairment that falls short of blindness. Prior wayfinding systems for people with visual impairments focused on blind people, providing only audio and tactile feedback. Since people with low vision use their remaining vision, we sought to determine how audio feedback compares to visual feedback in a wayfinding task. We developed visual and audio wayfinding guidance on smartglasses based on de facto standard approaches for blind and sighted people and conducted a study with 16 low vision participants. We found that participants made fewer mistakes and experienced lower cognitive load with visual feedback. Moreover, participants with a full field of view completed the wayfinding tasks faster when using visual feedback. However, many participants preferred audio feedback because of its shorter learning curve. We propose design guidelines for wayfinding systems for low vision.
Title: Exploring the Potential of an Intelligent Tutoring System for Sketching Fundamentals
Authors: family: Williford
given: Blake; family: Runyon
given: Matthew; family: Li
given: Wayne; family: Linsey
given: Julie; family: Hammond
given: Tracy
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Sketching is a practical and useful skill that can benefit communication and problem solving. However, it remains a difficult skill to learn because of low confidence and motivation among students and limited availability for instruction and personalized feedback among teachers. There is an need to improve the educational experience for both groups, and we hypothesized that integrating technology could provide a variety of benefits. We designed and developed an intelligent tutoring system for sketching fundamentals called Sketchtivity, and deployed it in to six existing courses at the high school and university level during the 2017-2018 school year. 268 students used the tool and produced more than 116,000 sketches of basic primitives. We conducted semi-structured interviews with the six teachers who implemented the software, as well as nine students from a course where the tool was used extensively. Using grounded theory, we found ten categories which unveiled the benefits and limitations of integrating an intelligent tutoring system for sketching fundamentals in to existing pedagogy.
Title: Reinforcement Learning for the Adaptive Scheduling of Educational Activities
Authors: family: Bassen
given: Jonathan; family: Balaji
given: Bharathan; family: Schaarschmidt
given: Michael; family: Thille
given: Candace; family: Painter
given: Jay; family: Zimmaro
given: Dawn; family: Games
given: Alex; family: Fast
given: Ethan; family: Mitchell
given: John C.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Adaptive instruction for online education can increase learning gains and decrease the work required of learners, instructors, and course designers. Reinforcement Learning (RL) is a promising tool for developing instructional policies, as RL models can learn complex relationships between course activities, learner actions, and educational outcomes. This paper demonstrates the first RL model to schedule educational activities in real time for a large online course through active learning. Our model learns to assign a sequence of course activities while maximizing learning gains and minimizing the number of items assigned. Using a controlled experiment with over 1,000 learners, we investigate how this scheduling policy affects learning gains, dropout rates, and qualitative learner feedback. We show that our model produces better learning gains using fewer educational activities than a linear assignment condition, and produces similar learning gains to a self-directed condition using fewer educational activities and with lower dropout rates.