huashen218/convxai-cia-dataset huggingface dataset:
Title: What is AI Literacy? Competencies and Design Considerations
Authors: family: Long
given: Duri; family: Magerko
given: Brian
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Artificial intelligence (AI) is becoming increasingly integrated in user-facing technology, but public understanding of these technologies is often limited. There is a need for additional HCI research investigating a) what competencies users need in order to effectively interact with and critically evaluate AI and b) how to design learner-centered AI technologies that foster increased user understanding of AI. This paper takes a step towards realizing both of these goals by providing a concrete definition of AI literacy based on existing research. We synthesize a variety of interdisciplinary literature into a set of core competencies of AI literacy and suggest several design considerations to support AI developers and educators in creating learner-centered AI. These competencies and design considerations are organized in a conceptual framework thematically derived from the literature. This paper's contributions can be used to start a conversation about and guide future research on AI literacy within the HCI community.
Title: Twitter A11y: A Browser Extension to Make Twitter Images Accessible
Authors: family: Gleason
given: Cole; family: Pavel
given: Amy; family: McCamey
given: Emma; family: Low
given: Christina; family: Carrington
given: Patrick; family: Kitani
given: Kris M.; family: Bigham
given: Jeffrey P.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Social media platforms are integral to public and private discourse, but are becoming less accessible to people with vision impairments due to an increase in user-posted images. Some platforms (i.e. Twitter) let users add image descriptions (alternative text), but only 0.1% of images include these. To address this accessibility barrier, we created Twitter A11y, a browser extension to add alternative text on Twitter using six methods. For example, screenshots of text are common, so we detect textual images, and create alternative text using optical character recognition. Twitter A11y also leverages services to automatically generate alternative text or reuse them from across the web. We compare the coverage and quality of Twitter A11y's six alt-text strategies by evaluating the timelines of 50 self-identified blind Twitter users. We find that Twitter A11y increases alt-text coverage from 7.6% to 78.5%, before crowdsourcing descriptions for the remaining images. We estimate that 57.5% of returned descriptions are high-quality. We then report on the experiences of 10 participants with visual impairments using the tool during a week-long deployment. Twitter A11y increases access to social media platforms for people with visual impairments by providing high-quality automatic descriptions for user-posted images.
Title: What's Wrong with Computational Notebooks? Pain Points, Needs, and Design Opportunities
Authors: family: Chattopadhyay
given: Souti; family: Prasad
given: Ishita; family: Henley
given: Austin Z.; family: Sarma
given: Anita; family: Barik
given: Titus
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Computational notebooks - such as Azure, Databricks, and Jupyter - are a popular, interactive paradigm for data scientists to author code, analyze data, and interleave visualizations, all within a single document. Nevertheless, as data scientists incorporate more of their activities into notebooks, they encounter unexpected difficulties, or pain points, that impact their productivity and disrupt their workflow. Through a systematic, mixed-methods study using semi-structured interviews (n=20) and survey (n=156) with data scientists, we catalog nine pain points when working with notebooks. Our findings suggest that data scientists face numerous pain points throughout the entire workflow - from setting up notebooks to deploying to production - across many notebook environments. Our data scientists report essential notebook requirements, such as supporting data exploration and visualization. The results of our study inform and inspire the design of computational notebooks.
Title: Interacting with Literary Style through Computational Tools
Authors: family: Sterman
given: Sarah; family: Huang
given: Evey; family: Liu
given: Vivian; family: Paulos
given: Eric
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Style is an important aspect of writing, shaping how audiences interpret and engage with literary works. However, for most people style is difficult to articulate precisely. While users frequently interact with computational word processing tools with well-defined metrics, such as spelling and grammar checkers, style is a significantly more nuanced concept. In this paper, we present a computational technique to help surface style in written text. We collect a dataset of crowdsourced human judgments of style, derive a model of style by training a neural net on this data, and present novel applications for visualizing and browsing style across broad bodies of literature, as well as an interactive text editor with real-time style feedback. We study these interactive style applications with users and discuss implications for enabling this novel approach to style.
Title: To Write Code: The Cultural Fabrication of Programming Notation and Practice
Authors: family: Arawjo
given: Ian
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Writing and its means have become detached. Unlike written and drawn practices developed prior to the 20th century, notation for programming computers developed in concert and conflict with discretizing infrastructure such as the shift-key typewriter and data processing pipelines. In this paper, I recall the emergence of high-level notation for representing computation. I show how the earliest inventors of programming notations borrowed from various written cultural practices, some of which came into conflict with the constraints of digitizing machines, most prominently the typewriter. As such, I trace how practices of "writing code" were fabricated along social, cultural, and material lines at the time of their emergence. By juxtaposing early visions with the modern status quo, I question long-standing terminology, dichotomies, and epistemological tendencies in the field of computer programming. Finally, I argue that translation work is a fundamental property of the practice of writing code by advancing an intercultural lens on programming practice rooted in history.
Title: AL: An Adaptive Learning Support System for Argumentation Skills
Authors: family: Wambsganss
given: Thiemo; family: Niklaus
given: Christina; family: Cetto
given: Matthias; family: Söllner
given: Matthias; family: Handschuh
given: Siegfried; family: Leimeister
given: Jan Marco
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Recent advances in Natural Language Processing (NLP) bear the opportunity to analyze the argumentation quality of texts. This can be leveraged to provide students with individual and adaptive feedback in their personal learning journey. To test if individual feedback on students' argumentation will help them to write more convincing texts, we developed AL, an adaptive IT tool that provides students with feedback on the argumentation structure of a given text. We compared AL with 54 students to a proven argumentation support tool. We found students using AL wrote more convincing texts with better formal quality of argumentation compared to the ones using the traditional approach. The measured technology acceptance provided promising results to use this tool as a feedback application in different learning settings. The results suggest that learning applications based on NLP may have a beneficial use for developing better writing and reasoning for students in traditional learning settings.
Title: Scents and Sensibility: Evaluating Information Olfactation
Authors: family: Batch
given: Andrea; family: Patnaik
given: Biswaksen; family: Akazue
given: Moses; family: Elmqvist
given: Niklas
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Olfaction---the sense of smell---is one of the least explored of the human senses for conveying abstract information. In this paper, we conduct a comprehensive perceptual experiment on information olfactation: the use of olfactory and cross-modal sensory marks and channels to convey data. More specifically, following the example from graphical perception studies, we design an experiment that studies the perceptual accuracy of four cross-modal sensory channels---scent type, scent intensity, airflow, and temperature---for conveying three different types of data---nominal, ordinal, and quantitative. We also present details of a 24-scent multi-sensory display and its software framework that we designed in order to run this experiment. Our results yield a ranking of olfactory and cross-modal sensory channels that follows similar principles as classic rankings for visual channels.
Title: Optimal Sensor Position for a Computer Mouse
Authors: family: Kim
given: Sunjun; family: Lee
given: Byungjoo; family: van Gemert
given: Thomas; family: Oulasvirta
given: Antti
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Computer mice have their displacement sensors in various locations (center, front, and rear). However, there has been little research into the effects of sensor position or on engineering approaches to exploit it. This paper first discusses the mechanisms via which sensor position affects mouse movement and reports the results from a study of a pointing task in which the sensor position was systematically varied. Placing the sensor in the center turned out to be the best compromise: improvements over front and rear were in the 11-14% range for throughput and 20--23% for path deviation. However, users varied in their personal optima. Accordingly, variable-sensor-position mice are then presented, with a demonstration that high accuracy can be achieved with two static optical sensors. A virtual sensor model is described that allows software-side repositioning of the sensor. Individual-specific calibration should yield an added 4% improvement in throughput over the default center position.
Title: Investigating Collaborative Exploration of Design Alternatives on a Wall-Sized Display
Authors: family: Okuya
given: Yujiro; family: Gladin
given: Olivier; family: Ladevèze
given: Nicolas; family: Fleury
given: Cédric; family: Bourdot
given: Patrick
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Industrial design review is an iterative process which mainly relies on two steps involving many stakeholders: design discussion and CAD data adjustment. We investigate how a wall-sized display could be used to merge these two steps by allowing multidisciplinary collaborators to simultaneously generate and explore design alternatives. We designed ShapeCompare based on the feedback from a usability study. It enables multiple users to compute and distribute CAD data with touch interaction. To assess the benefit of the wall-sized display in such context, we ran a controlled experiment which aims to compare ShapeCompare with a visualization technique suitable for standard screens. The results show that pairs of participants performed a constraint solving task faster and used more deictic instructions with ShapeCompare. From these findings, we draw generic recommendations for collaborative exploration of alternatives.
Title: On-Face Olfactory Interfaces
Authors: family: Wang
given: Yanan; family: Amores
given: Judith; family: Maes
given: Pattie
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: On-face wearables are currently limited to piercings, tattoos, or interactive makeup that aesthetically enhances the user, and have been minimally used for scent-delivery methods. However, on-face scent interfaces could provide an advantage for personal scent delivery in comparison with other modalities or body locations since they are closer to the nose. In this paper, we present the mechanical and industrial design details of a series of form factors for on-face olfactory wearables that are lightweight and can be adhered to the skin or attached to glasses or piercings. We assessed the usability of three prototypes by testing with 12 participants in a within-subject study design while they were interacting in pairs at a close personal distance. We compare two of these designs with an "off-face" olfactory necklace and evaluate their social acceptance, comfort as well as perceived odor intensity for both the wearer and observer.
Title: Charge for a whole day: Extending Battery Life for BCI Wearables using a Lightweight Wake-Up Command
Authors: family: Agarwal
given: Mohit; family: Sivakumar
given: Raghupathy
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Commercially available EEG-based Brain-Computer Interface (BCI) wearable headsets are always-on and are thus power hungry, requiring users to charge the headsets multiple times a day. In this paper, we tackle the problem of wake-up command design and detection for BCI headsets, and explore how battery life can be made to last for approximately a whole day. The key challenge that we address is enabling the headset to operate in a near-sleep mode but still reliably detect and interpret an EEG-based wake-up command from the user. Towards addressing the challenge, we present a solution that is built upon eye-blinks. Our core contribution is Trance, a user-friendly and robust wake-up command for BCI headsets that is computationally lightweight. We show using experimental results coupled with multiple data sets collected through user-studies that Trance can extend battery life by approximately 2.7x or to approximately 10 hours for a typical wearable battery, while remaining user-friendly.
Title: Novice-AI Music Co-Creation via AI-Steering Tools for Deep Generative Models
Authors: family: Louie
given: Ryan; family: Coenen
given: Andy; family: Huang
given: Cheng Zhi; family: Terry
given: Michael; family: Cai
given: Carrie J.
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: While generative deep neural networks (DNNs) have demonstrated their capacity for creating novel musical compositions, less attention has been paid to the challenges and potential of co-creating with these musical AIs, especially for novices. In a needfinding study with a widely used, interactive musical AI, we found that the AI can overwhelm users with the amount of musical content it generates, and frustrate them with its non-deterministic output. To better match co-creation needs, we developed AI-steering tools, consisting of Voice Lanes that restrict content generation to particular voices; Example-Based Sliders to control the similarity of generated content to an existing example; Semantic Sliders to nudge music generation in high-level directions (happy/sad, conventional/surprising); and Multiple Alternatives of generated content to audition and choose from. In a summative study (N=21), we discovered the tools not only increased users' trust, control, comprehension, and sense of collaboration with the AI, but also contributed to a greater sense of self-efficacy and ownership of the composition relative to the AI.
Title: Callisto: Capturing the "Why" by Connecting Conversations with Computational Narratives
Authors: family: Wang
given: April Yi; family: Wu
given: Zihan; family: Brooks
given: Christopher; family: Oney
given: Steve
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: When teams of data scientists collaborate on computational notebooks, their discussions often contain valuable insight into their design decisions. These discussions not only explain analysis in the current notebook but also alternative paths, which are often poorly documented. However, these discussions are disconnected from the notebooks for which they could provide valuable context. We propose Callisto, an extension to computational notebooks that captures and stores contextual links between discussion messages and notebook elements with minimal effort from users. Callisto allows notebook readers to better understand the current notebook content and the overall problem-solving process that led to it, by making it possible to browse the discussions and code history relevant to any part of the notebook. This is particularly helpful for onboarding new notebook collaborators to avoid misinterpretations and duplicated work, as we found in a two-stage evaluation with 32 data science students.
Title: What HCI Can Learn from ASMR: Becoming Enchanted with the Mundane
Authors: family: Klefeker
given: Josephine; family: striegl
given: libi; family: Devendorf
given: Laura
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: In this paper we explore how the qualities of Autonomous Sensory Meridian Response (ASMR) media - its pairing of sonic and visual design, ability to subvert fast-paced technology for slow experiences, production of somatic responses, and attention to the everyday-might reveal new design possibilities for interactions with wearable technology. We recount our year-long design inquiry into the subject which began with an interview with a "live" ASMR creator and design probes, a series of first-person design exercises, and resulted in the creation of two interactive garments for attending, noticing, and becoming enchanted with our our everyday surroundings. We conclude by suggesting that these ASMR inspired designs cultivate personal, intimate, embodied, and felt practices of attention within our everyday, mundane, environments.
Title: Getting out of Out of Sight: Evaluation of AR Mechanisms for Awareness and Orientation Support in Occluded Multi-Room Settings
Authors: family: Osmers
given: Niklas; family: Prilla
given: Michael
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Augmented Reality can provide orientation and awareness in situations in which objects or people are occluded by physical structures. This is relevant for many situations in the workplace, where objects are scattered across rooms and people are out of sight. While several AR mechanisms have been proposed to provide awareness and orientation in these situations, little is known about their effect on people's performance when searching objects and coordinating with each other. In this paper, we compare three AR based mechanisms (map, x-ray, compass) according to their utility, usability, social presence, task load and users' preferences. 48 participants had to work together in groups of four to find people and objects located around different rooms. Results show that map and x-ray performed best but provided least social presence among participants. We discuss these and other observations as well as potential impacts on designing AR awareness and orientation support.
Title: In Helping a Vulnerable Bot, You Help Yourself: Designing a Social Bot as a Care-Receiver to Promote Mental Health and Reduce Stigma
Authors: family: Kim
given: Taewan; family: Ruensuk
given: Mintra; family: Hong
given: Hwajung
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Helping others can have a positive effect on both the giver and the receiver. However, supporting someone with depression can be complicated and overwhelming. To address this, we proposed a Facebook-based social bot displaying depressive symptoms and disclosing vulnerable experiences that allows users to practice providing reactions online. We investigated how 55 college students interacted with the social bot for three weeks and how these support-giving experiences affected their mental health and stigma. By responding to the bot, the participants reframed their own negative experiences, reported reduced feelings of danger regarding an individual with depression and increased willingness to help the person, and presented favorable attitudes toward seeking treatment for depression. We discuss design opportunities for accessible social bots that could help users to keep practicing peer support interventions without fear of negative consequences.
Title: Disseminating Research News in HCI: Perceived Hazards, How-To's, and Opportunities for Innovation
Authors: family: Smith
given: C. Estelle; family: Nevarez
given: Eduardo; family: Zhu
given: Haiyi
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: Mass media afford researchers critical opportunities to disseminate research findings and trends to the general public. Yet researchers also perceive that their work can be miscommunicated in mass media, thus generating unintended understandings of HCI research by the general public. We conduct a Grounded Theory analysis of interviews with 12 HCI researchers and find that miscommunication can occur at four origins along the socio-technical infrastructure known as the Media Production Pipeline (MPP) for science news. Results yield researchers' perceived hazards of disseminating their work through mass media, as well as strategies for fostering effective communication of research. We conclude with implications for augmenting or innovating new MPP technologies.
Title: Lawful Users: Copyright Circumvention and Legal Constraints on Technology Use
Authors: family: Fiesler
given: Casey
Venue: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract: The study of human-computer interaction requires consideration of aspects of interactions with technology that may be outside of the control of both user and designer. One example of when a user's question of "can I do this?" may have an answer beyond technological affordances is that of legal constraints. This paper considers an example of this phenomenon: section 1201 of the Digital Millennium Copyright Act (DMCA) in the United States, which criminalizes circumventing copyright protection such as digital rights management (DRM). The DMCA also includes a triennial policymaking process that considers exemptions to the law to protect "lawful users" from adverse effects. Through an analysis of public comments of support for exemptions, this paper explores the ways in which users see the law as a hindrance to desired uses of technology. This analysis sheds light on users' expectations for rights of use, how these expectations clash with policy, and what this might mean for technology designers. Drawing lessons from the infrastructure problem in HCI, this paper concludes with laying out solutions that can both work within policy constraints, and more importantly, work to change them.