huashen218/convxai-cia-dataset huggingface dataset:
Title: Adhering, Steering, and Queering: Treatment of Gender in Natural Language Generation
Authors: family: Strengers
given: Yolande; family: Qu
given: Lizhen; family: Xu
given: Qiongkai; family: Knibbe
given: Jarrod
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Natural Language Generation (NLG) supports the creation of personalized, contextualized, and targeted content. However, the algorithms underpinning NLG have come under scrutiny for reinforcing gender, racial, and other problematic biases. Recent research in NLG seeks to remove these biases through principles of fairness and privacy. Drawing on gender and queer theories from sociology and Science and Technology studies, we consider how NLG can contribute towards the advancement of gender equity in society. We propose a conceptual framework and technical parameters for aligning NLG with feminist HCI qualities. We present three approaches: (1) adhering to current approaches of removing sensitive gender attributes, (2) steering gender differences away from the norm, and (3) queering gender by troubling stereotypes. We discuss the advantages and limitations of these approaches across three hypothetical scenarios; newspaper headlines, job advertisements, and chatbots. We conclude by discussing considerations for implementing this framework and related ethical and equity agendas.
Title: Mental Models of AI Agents in a Cooperative Game Setting
Authors: family: Gero
given: Katy Ilonka; family: Ashktorab
given: Zahra; family: Dugan
given: Casey; family: Pan
given: Qian; family: Johnson
given: James; family: Geyer
given: Werner; family: Ruiz
given: Maria; family: Miller
given: Sarah; family: Millen
given: David R.; family: Campbell
given: Murray; family: Kumaravel
given: Sadhana; family: Zhang
given: Wei
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: As more and more forms of AI become prevalent, it becomes increasingly important to understand how people develop mental models of these systems. In this work we study people's mental models of AI in a cooperative word guessing game. We run think-aloud studies in which people play the game with an AI agent; through thematic analysis we identify features of the mental models developed by participants. In a large-scale study we have participants play the game with the AI agent online and use a post-game survey to probe their mental model. We find that those who win more often have better estimates of the AI agent's abilities. We present three components for modeling AI systems, propose that understanding the underlying technology is insufficient for developing appropriate conceptual models (analysis of behavior is also necessary), and suggest future work for studying the revision of mental models over time.
Title: TAGSwipe: Touch Assisted Gaze Swipe for Text Entry
Authors: family: Kumar
given: Chandan; family: Hedeshy
given: Ramin; family: MacKenzie
given: I. Scott; family: Staab
given: Steffen
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: The conventional dwell-based methods for text entry by gaze are typically slow and uncomfortable. A swipe-based method that maps gaze path into words offers an alternative. However, it requires the user to explicitly indicate the beginning and ending of a word, which is typically achieved by tedious gaze-only selection. This paper introduces TAGSwipe, a bi-modal method that combines the simplicity of touch with the speed of gaze for swiping through a word. The result is an efficient and comfortable dwell-free text entry method. In the lab study TAGSwipe achieved an average text entry rate of 15.46 wpm and significantly outperformed conventional swipe-based and dwell-based methods in efficacy and user satisfaction.
Title: Studying the Effects of Cognitive Biases in Evaluation of Conversational Agents
Authors: family: Santhanam
given: Sashank; family: Karduni
given: Alireza; family: Shaikh
given: Samira
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Humans quite frequently interact with conversational agents. The rapid advancement in generative language modeling through neural networks has helped advance the creation of intelligent conversational agents. Researchers typically evaluate the output of their models through crowdsourced judgments, but there are no established best practices for conducting such studies. Moreover, it is unclear if cognitive biases in decision-making are affecting crowdsourced workers' judgments when they undertake these tasks. To investigate, we conducted a between-subjects study with 77 crowdsourced workers to understand the role of cognitive biases, specifically anchoring bias, when humans are asked to evaluate the output of conversational agents. Our results provide insight into how best to evaluate conversational agents. We find increased consistency in ratings across two experimental conditions may be a result of anchoring bias. We also determine that external factors such as time and prior experience in similar tasks have effects on inter-rater consistency.
Title: Personal Space in Play: Physical and Digital Boundaries in Large-Display Cooperative and Competitive Games
Authors: family: Wehbe
given: Rina R.; family: Dickson
given: Terence; family: Kuzminykh
given: Anastasia; family: Nacke
given: Lennart E.; family: Lank
given: Edward
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: As multi-touch displays grow in size and shrink in price, they are more commonly used as gaming devices. When co-located users play games on a single, large display, establishing and maintaining their physical and digital territories poses a social challenge to their interaction. To gain insight into the mechanisms of establishing and maintaining users' physical and digital territories, we analyze territorial interactions in cooperative and competitive multiplayer gameplay. Participants reported weighing each game interaction based on perceived intent to determine how socially acceptable they deemed each behaviour. In light of our observations, we contribute and discuss implications for the design of multi-user, large display, co-located, touchscreen games that consider display properties, digital and physical space, permeability of boundaries, and asymmetry of play to create interactions between players.
Title: "Hi! I am the Crowd Tasker" Crowdsourcing through Digital Voice Assistants
Authors: family: Hettiachchi
given: Danula; family: Sarsenbayeva
given: Zhanna; family: Allison
given: Fraser; family: van Berkel
given: Niels; family: Dingler
given: Tilman; family: Marini
given: Gabriele; family: Kostakos
given: Vassilis; family: Goncalves
given: Jorge
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Inspired by the increasing prevalence of digital voice assistants, we demonstrate the feasibility of using voice interfaces to deploy and complete crowd tasks. We have developed Crowd Tasker, a novel system that delivers crowd tasks through a digital voice assistant. In a lab study, we validate our proof-of-concept and show that crowd task performance through a voice assistant is comparable to that of a web interface for voice-compatible and voice-based crowd tasks for native English speakers. We also report on a field study where participants used our system in their homes. We find that crowdsourcing through voice can provide greater flexibility to crowd workers by allowing them to work in brief sessions, enabling multi-tasking, and reducing the time and effort required to initiate tasks. We conclude by proposing a set of design guidelines for the creation of crowd tasks for voice and the development of future voice-based crowdsourcing systems.
Title: Dark Patterns after the GDPR: Scraping Consent Pop-ups and Demonstrating their Influence
Authors: family: Nouwens
given: Midas; family: Liccardi
given: Ilaria; family: Veale
given: Michael; family: Karger
given: David; family: Kagal
given: Lalana
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: New consent management platforms (CMPs) have been introduced to the web to conform with the EU's General Data Protection Regulation, particularly its requirements for consent when companies collect and process users' personal data. This work analyses how the most prevalent CMP designs affect people's consent choices. We scraped the designs of the five most popular CMPs on the top 10,000 websites in the UK (n=680). We found that dark patterns and implied consent are ubiquitous; only 11.8% meet our minimal requirements based on European law. Second, we conducted a field experiment with 40 participants to investigate how the eight most common designs affect consent choices. We found that notification style (banner or barrier) has no effect; removing the opt-out button from the first page increases consent by 22-23 percentage points; and providing more granular controls on the first page decreases consent by 8-20 percentage points. This study provides an empirical basis for the necessary regulatory action to enforce the GDPR, in particular the possibility of focusing on the centralised, third-party CMP services as an effective way to increase compliance.
Title: WithYou: Automated Adaptive Speech Tutoring With Context-Dependent Speech Recognition
Authors: family: Zhang
given: Xinlei; family: Miyaki
given: Takashi; family: Rekimoto
given: Jun
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Learning to speak in foreign languages is hard. Speech shadowing has been rising as a proven way to practice speaking, which asks a learner to listen and repeat a native speech template as simultaneously as possible. However, shadowing can be hard to do because learners can frequently fail to follow the speech and unintentionally interrupt a practice session. Worse, as a technical way to evaluate shadowing performance in real-time has not been established, no automated solutions are available to help. In this paper, we propose a technical framework with context-dependent speech recognition to evaluate shadowing in real-time. We propose a shadowing tutor system called WithYou, which can automatically adjust the playback and the difficulty of a speech template when learners fail, so shadowing becomes smooth and tailored. Results from a user study show that WithYou provides greater speech improvements (14%) than the conventional method (2.7%) with a lower cognitive load.
Title: ThermalRing: Gesture and Tag Inputs Enabled by a Thermal Imaging Smart Ring
Authors: family: Zhang
given: Tengxiang; family: Zeng
given: Xin; family: Zhang
given: Yinshuai; family: Sun
given: Ke; family: Wang
given: Yuntao; family: Chen
given: Yiqiang
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: The heterogeneous and ubiquitous input demands in smart spaces call for an input device that can enable rich and spontaneous interactions. We propose ThermalRing, a thermal imaging smart ring using low-resolution thermal camera for identity-anonymous, illumination-invariant, and power-efficient sensing of both dynamic and static gestures. We also design ThermalTag, thin and passive thermal imageable tags that reflect the heat from the human hand. ThermalTag can be easily made and applied onto everyday objects by users. We develop sensing techniques for three typical input demands: drawing gestures for device pairing, click and slide gestures for device control, and tag scan gestures for quick access. The study results show that ThermalRing can recognize nine drawing gestures with an overall accuracy of 90.9%, detect click gestures with an accuracy of 94.9%, and identify among six ThermalTags with an overall accuracy of 95.0%. Finally, we show the versatility and potential of ThermalRing through various applications.
Title: Predicting and Diagnosing User Engagement with Mobile UI Animation via a Data-Driven Approach
Authors: family: Wu
given: Ziming; family: Jiang
given: Yulun; family: Liu
given: Yiding; family: Ma
given: Xiaojuan
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Animation, a common design element in user interfaces (UI), can impact user engagement (UE) with mobile applications. To avoid impairing UE due to improper design of animation, designers rely on resource-intensive evaluation methods like user studies or expert reviews. To alleviate this burden, we propose a data-driven approach to assisting designers in examining UE issues with their animation designs. We first crowdsource UE assessments of mobile UI animations. Based on the collected data, we then build a novel deep learning model that captures both spatial and temporal features of animations to predict their UE levels. Evaluations show that our model achieves a reasonable accuracy. We further leverage the animation feature encoded by our model and a sample set of expert reviews to derive potential UE issues of a particular animation. Finally, we develop a proof-of-concept tool and evaluate its potential usage in actual design practices with experts
Title: Color and Animation Preferences for a Light Band eHMI in Interactions Between Automated Vehicles and Pedestrians
Authors: family: Dey
given: Debargha; family: Habibovic
given: Azra; family: Pfleging
given: Bastian; family: Martens
given: Marieke; family: Terken
given: Jacques
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: In this paper, we report user preferences regarding color and animation patterns to support the interaction between Automated Vehicles (AVs) and pedestrians through an external Human-Machine-Interface (eHMI). Existing concepts of eHMI differ -- among other things -- in their use of colors or animations to express an AV's yielding intention. In the absence of empirical research, there is a knowledge gap regarding which color and animation leads to highest usability and preferences in traffic negotiation situations. We conducted an online survey (N=400) to investigate the comprehensibility of a light band eHMI with a combination of 5 color and 3 animation patterns for a yielding AV. Results show that cyan is considered a neutral color for communicating a yielding intention. Additionally, a uniformly flashing or pulsing animation is preferred compared to any pattern that animates sideways. These insights can contribute in the future design and standardization of eHMIs.
Title: A Participatory Simulation of the Accountable Capitalism Act
Authors: family: Tomlinson
given: Bill; family: Silberman
given: M. Six; family: Torrance
given: Andrew W.; family: Squire
given: Kurt; family: Atwal
given: Paramdeep S.; family: Mandalik
given: Ameya N.; family: Railkar
given: Sahil; family: Black
given: Rebecca W.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Interactive computing systems increasingly allow for experimental evaluations of fundamental issues in law, government, and society. In this paper, we describe a participatory simulation of the Accountable Capitalism Act, a bill proposed in 2018 by US Senator Elizabeth Warren. We present findings from an empirical study conducted using this system, relating to the impact of 1) interactive visualization and 2) the Accountable Capitalism Act legal framework on the behavior of participants acting as corporate directors. From this study, we draw lessons about research possibilities at the juncture of HCI and legal and policy studies. This study contributes an analysis and evaluation of a design probe used to investigate potential impacts of the Accountable Capitalism Act, experimental evidence from a study conducted using the design probe, and guidance for future participatory simulations that seek to inform the design of social institutions.
Title: GUIComp: A GUI Design Assistant with Real-Time, Multi-Faceted Feedback
Authors: family: Lee
given: Chunggi; family: Kim
given: Sanghoon; family: Han
given: Dongyun; family: Yang
given: Hongjun; family: Park
given: Young-Woo; family: Kwon
given: Bum Chul; family: Ko
given: Sungahn
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Users may face challenges while designing graphical user interfaces, due to a lack of relevant experience and guidance. This paper aims to investigate the issues users face during the design process, and how to resolve them. To this end, we conducted semi-structured interviews, based on which we built a GUI prototyping assistance tool called GUIComp. This tool can be connected to GUI design software as an extension, and it provides real-time, multi-faceted feedback on a user's current design. Additionally, we conducted two user studies, in which we asked participants to create mobile GUIs with or without GUIComp, and requested online workers to assess the created GUIs. The experimental results show that GUIComp facilitated iterative designs and the participants with GUIComp had better a user experience and produced more acceptable designs than those who did not use it.
Title: Searching for Mental Health: A Mixed-Methods Study of Young People's Online Help-seeking
Authors: family: Pretorius
given: Claudette; family: McCashin
given: Darragh; family: Kavanagh
given: Naoise; family: Coyle
given: David
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Seeking help is often an important step in addressing mental health difficulties. Evidence suggests that positive help-seeking experiences contribute to an increased likelihood of future help-seeking and achieving improved outcomes. However, help-seeking is a complex process. Alongside traditional sources, digital technologies offer many pathways to help. Using a mixed methods approach across two studies, this paper explores key design factors for online mental health resources that can support young people's help-seeking. First, a large online survey (n=1308) highlighted challenges and identified common help-seeking scenarios, including information-seeking, person-centred approaches and crisis situations. Using survey data, personas were developed to represent different help-seekers - each characterised by a particular help-seeking scenario. The personas were then used in co-design workshops to facilitate further exploration of help-seeking needs. Four key design considerations were identified: connectedness, accessible information, personalisation, and immediacy. Based on our findings, we provide design recommendations that are grounded in existing theories of help-seeking.
Title: Culture in Action: Unpacking Capacities to Inform Assets-Based Design
Authors: family: Wong-Villacres
given: Marisol; family: DiSalvo
given: Carl; family: Kumar
given: Neha; family: DiSalvo
given: Betsy
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: The field of Human-Computer Interaction (HCI) aims at securing a lasting impact for technology-based interventions in the context of social inequities. Increasingly, HCI scholars are proposing assets-based design as an effective approach towards this issue. Rather than starting from people's needs and deficits, this approach posits that design should start from a deep understanding of people's assets. A pending issue, however, is how to account for the situated nature of assets; that is, how to decide which asset to leverage and for what design purpose. Drawing from cultural sociology and shifting the emphasis from assets to capacities, we propose Swidler's theory of culture-in-action as an analytical lens for unpacking the complex relationship between capacities, goals, and structural limitations. Leveraging findings from a Participatory Design engagement with 35 Latino immigrant parents for envisioning parent-education technologies, we demonstrate the applicability of this lens. We contribute to HCI scholarship by further discussing 1) how to analyze capacities' design potential, and 2) the methodological particularities for collecting them.
Title: Investigating the Effects of Self-Avatars and Story-Relevant Avatars on Children's Creative Storytelling
Authors: family: Zarei
given: Niloofar; family: Chu
given: Sharon Lynn; family: Quek
given: Francis; family: Rao
given: Nanjie 'Jimmy'; family: Brown
given: Sarah Anne
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Storytelling is a critical step in the cognitive development of children. Particularly, this requires children to mentally project into the story context and to identify with the thoughts of the characters in their stories. We propose to support free imagination in creative storytelling through an enactment-based approach that allows children to embody an avatar and perform as the story character. We designed our story creation interface with two modes of avatar: the story-relevant avatar and the self-avatar, to investigate the effects of avatar design on the quality of children's creative products. In our study with 20 child participants, the results indicate that self-avatars can create a stronger sense of identification and embodied presence, while story-relevant avatars can provide a scaffold for mental projection.
Title: Restorative Play: Videogames Improve Player Wellbeing After a Need-Frustrating Event
Authors: family: Tyack
given: April; family: Wyeth
given: Peta; family: Johnson
given: Daniel
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: People often use videogames to restore wellbeing after negative experiences in day-to-day life. Although some research suggests that play can restore wellbeing, few studies have investigated the means by which restoration occurs. We employed self-determination theory (SDT) to understand how and to what degree play improves wellbeing after a need-frustrating event, and how players understand experiences of competence in play. Sixty-five participants worked at a competence manipulation task prior to playing a competence-satisfying videogame. Competence, affect, and vitality improved during play, and in-game experiences of need frustration were observed to effectively predict post-play negative affect. Post-experiment interviews indicate that videogames are seen to support competence relative to perceived skill, extending our knowledge of how design can support competence and restoration. We demonstrate that play can restore wellbeing, present need frustration as a means to explain negative experiences with interactive systems, and discuss effects of design on competence.