Miracle-dz/UniFAR-FTUs huggingface dataset:
Opinions, Intentions, Freedom of Expression, ... , and Other Human Aspects of Misinformation Online

As a wicked problem, limiting the harm caused by misinformation requires merging multiple perspectives to the design of digital interventions, including an understanding of human behaviour and motivations in judging and promoting false information, as well as strategies to detect and stop its propagation without unduly infringing on rights or freedoms of expression. Tools and online services are continuously being developed to support different stakeholders in this battle, such as social media users, journalists, and policymakers. As our studies have demonstrated, the expected impact of online solutions is hampered by limitations associated with lack of explainability, complex user interface, limited datasets, restricted accessibility, biased algorithms, among others factors that can confuse, overwhelm, or mislead users in their own ways. These ethical implications are typically neglected when new digital solutions to tackle misinformation are conceived. This hands-on workshop proposes to unpack the state-of-the-art on social, societal and political studies and socio-technical solutions to stop mis-information, challenging the participants to first critically reflect upon limitations of existing approaches, to then co-create a future with integrating perspectives focusing on ethical aspects and societal impact.
“Money makes the world go around”: Identifying Barriers to Better Privacy in Children’s Apps From Developers’ Perspectives

The industry for children’s apps is thriving at the cost of children’s privacy: these apps routinely disclose children’s data to multiple data trackers and ad networks. As children spend increasing time online, such exposure accumulates to long-term privacy risks. In this paper, we used a mixed-methods approach to investigate why this is happening and how developers might change their practices. We base our analysis against 5 leading data protection frameworks that set out requirements and recommendations for data collection in children’s apps. To understand developers’ perspectives and constraints, we conducted 134 surveys and 20 semi-structured interviews with popular Android children’s app developers. Our analysis revealed that developers largely respect children’s best interests; however, they have to make compromises due to limited monetisation options, perceived harmlessness of certain third-party libraries, and lack of availability of design guidelines. We identified concrete approaches and directions for future research to help overcome these barriers.
'We Can Send A Man To The Moon But We Can't Control The Temperature In Our office'; A Considerate Approach To Workplace Thermal Comfort by Older Women

From Fanger's seminal work on thermal comfort in the 1970s, standards governing temperatures in the workplace enshrine clothing level calculations based on full business suits, and building regulations developed using only male metabolic data, locking in a default male perspective. Even later work that highlights gender biases with regard to metabolism calculation, inclusive of both genders has focused on younger women, and the voices of older working women are missing from this discourse. We invited women over 45 to explore what they find important in workplace thermal comfort, and how devices and interfaces might meet their needs and also encourage thermal adaptivity. Our study highlights factors such as 'fresh air', and the importance of empathy to fellow inhabitants. We bring new voices to the thermal comfort discourse which supports reducing energy use in the workplace, improving thermal environments and ensuring the needs of a diverse, aging workforce are considered.
EyeXplain Autism: Interactive System for Eye Tracking Data Analysis and Deep Neural Network Interpretation for Autism Spectrum Disorder Diagnosis

Over the past decade, Deep Neural Networks (DNN) applied to eye tracking data have seen tremendous progress in their ability to perform Autism Spectrum Disorder (ASD) diagnosis. Despite their promising accuracy, DNNs are often seen as ’black boxes’ by physicians unfamiliar with the technology. In this paper, we present EyeXplain Autism, an interactive system that enables physicians to analyse eye tracking data, perform automated diagnosis and interpret DNN predictions. Here we discuss the design, development and sample scenario to illustrate the potential of our system to aid in ASD diagnosis. Unlike existing eye tracking software, our system combines traditional eye tracking visualisation and analysis tools with a data-driven knowledge to enhance medical decision-making for physicians.
Styling Words: A Simple and Natural Way to Increase Variability in Training Data Collection for Gesture Recognition

Due to advances in deep learning, gestures have become a more common tool for human-computer interaction. When implementing a large amount of training data, deep learning models show remarkable performance in gesture recognition. Since it is expensive and time consuming to collect gesture data from people, we are often confronted with a practicality issue when managing the quantity and quality of training data. It is a well-known fact that increasing training data variability can help to improve the generalization performance of machine learning models. Thus, we directly intervene in the collection of gesture data to increase human gesture variability by adding some words (called styling words) into the data collection instructions, e.g., giving the instruction "perform gesture #1 faster" as opposed to "perform gesture #1. " Through an in-depth analysis of gesture features and video-based gesture recognition, we have confirmed the advantageous use of styling words in gesture training data collection.
Watching Myself Watching Birds: Abjection, Ecological Thinking, and Posthuman Design

In recent years, Sustainable HCI researchers have begun to investigate “noticing” as a design research method useful in efforts to decenter the human in design. Through an autoethnographic bird watching practice combining field observation, journaling, and making practices, we examine how noticing affects us and our way of relating to birds. We found that bird watching surfaces a feeling of abjection, or a simultaneous repulsion and fascination with a part of oneself one rejects in pursuit of personal growth. Along the way, we honed a practice of attunement through deep listening and field recording, which enabled immersive "ecological" experiences. We offer (1) an account of our method and process, (2) the framework of abjection as an approach to designing amongst the complexity of human/non-human interaction, and (3) reflections on how to design for ecological thinking in the push towards a posthuman design.
StoryDrawer: A Co-Creative Agent Supporting Children's Storytelling through Collaborative Drawing

Storytelling is a common creative activity for children. During storytelling, children need creative support and are subjected to cognitive challenges. This paper explores a co-creative agent - StoryDrawer, which supports children in creating oral stories through collaborative drawing. StoryDrawer works with children in two strategies: Child says and AI draws; and Child scribbles and AI completes. These two collaborative strategies allow children to draw their stories as an externalization and provoke unexpected ideas. This paper presents the interaction design, collaborative strategies and implementation of StoryDrawer, and conducts a user study for the fun and task effectiveness of StoryDrawer. The results reveal that our system can encourage children's active participation in storytelling and help them create novel stories through human-computer collaboration.
ElectroRing: Subtle Pinch and Touch Detection with a Ring

We present ElectroRing, a wearable ring-based input device that reliably detects both onset and release of a subtle finger pinch, and more generally, contact of the fingertip with the user’s skin. ElectroRing addresses a common problem in ubiquitous touch interfaces, where subtle touch gestures with little movement or force are not detected by a wearable camera or IMU. ElectroRing’s active electrical sensing approach provides a step-function-like change in the raw signal, for both touch and release events, which can be easily detected using only basic signal processing techniques. Notably, ElectroRing requires no second point of instrumentation, but only the ring itself, which sets it apart from existing electrical touch detection methods. We built three demo applications to highlight the effectiveness of our approach when combined with a simple IMU-based 2D tracking system.
A Tangible Block Editor for the Scratch Programming Language

We describe the early-stage development of a tangible block editor for the educational programming language Scratch that is intended to contribute to an environment that will allow blind and visually impaired (BVI) students (grades 6-12) to learn computer programming concepts alongside their sighted peers (both independently and in pairs) in mainstream classrooms. In this late breaking work, we describe our design that incorporates many of the key strategies of the Scratch visual code editor meant to promote engagement and lower hurdles to programming. Novel key elements of the design include: the strategic use of magnets and locally interlocking block edges to ensure only blocks with valid syntax can be connected, the use of telescoping tubing to specify parameter/operand location and allow their expansion for nested expressions and a block-sized-channel grid work surface that provides structure to aid BVI students in navigating and manipulating their programs.
Color by Numbers: Interactive Structuring and Vectorization of Sketch Imagery

We present a novel, interactive interface for the integrated cleanup, neatening, structuring and vectorization of sketch imagery. Converting scanned raster drawings into vector illustrations is a well-researched set of problems. Our approach is based on a Delaunay subdivision of the raster drawing. We algorithmically generate a colored grouping of Delaunay regions that users interactively refine by dragging and dropping colors. Sketch strokes defined as marking boundaries of different colored regions are automatically neatened using Bézier curves, and turned into closed regions suitable for fills, textures, layering and animation. We show that minimal user interaction using our technique enables better sketch vectorization than state of art automated approaches. A user study, further shows our interface to be simple, fun and easy to use, yet effectively able to process messy images with a mix of construction lines, noisy and incomplete curves, sketched with arbitrary stroke style.
A User-Oriented Approach to Space-Adaptive Augmentation: The Effects of Spatial Affordance on Narrative Experience in an Augmented Reality Detective Game

Space-adaptive algorithms aim to effectively align the virtual with the real to provide immersive user experiences for Augmented Reality(AR) content across various physical spaces. While such measures are reliant on real spatial features, efforts to understand those features from the user’s perspective and reflect them in designing adaptive augmented spaces have been lacking. For this, we compared factors of narrative experience in six spatial conditions during the gameplay of Fragments, a space-adaptive AR detective game. Configured by size and furniture layout, each condition afforded disparate degrees of traversability and visibility. Results show that whereas centered furniture clusters are suitable for higher presence in sufficiently large rooms, the same layout leads to lower narrative engagement. Based on our findings, we suggest guidelines that can enhance the effects of space adaptivity by considering how users perceive and navigate augmented space generated from different physical environments.
Including Adults with Severe Intellectual Disabilities in Co-Design through Active Support

In recent work, design researchers have sought to ensure that people with disabilities are engaged as competent and valued contributors to co-design. Yet, little is known about how to achieve this with adults with severe intellectual disabilities. Navigating design in the context of complex care practices is challenging, charged with uncertainty, and requires sustained effort of methodological and affective adjustments. To establish a respectful co-design relationship and enrich participation, we turn to Active Support (AS), an evidence-based strategy for engaging adults with severe intellectual disabilities. We present a reflective account of long-term field work that utilized the four aspects of AS, a) every moment has potential; b) graded assistance; c) little and often; d) maximizing choice and control. We discuss how these principles contribute to deepening HCI methods by ensuring interactional turns for adults with severe disabilities, revealing their unique competences, thereby shaping design direction and providing design insight.
Designing Ground Truth and the Social Life of Labels

Ground-truth labeling is an important activity in machine learning. Many studies have examined how crowdworkers apply labels to records in machine learning datasets. However, there have been few studies that have examined the work of domain experts when their knowledge and expertise are needed to apply labels. We provide a grounded account of the work of labeling teams with domain experts, including the experiences of labeling, collaborative configurations and work-practices, and quality issues. We show three major patterns in the social design of ground truth data: Principled design, Iterative design, and Improvisational design. We interpret our results through theories of from Human Centered Data Science, and particularly work on human interventions in data science work through the design and creation of data.
Consequences, Schmonsequences! Considering the Future as Part of Publication and Peer Review in Computing Research

Research in computing is becoming increasingly concerned with understanding and mitigating unintended consequences of technology developments. However, those concerns are rarely reflected in how we submit, review, and publish our own work. Specifically, in talking about how our new apps, devices, and algorithms will change the world, we focus almost exclusively on positive consequences. There have been calls to require some speculation about negative impacts as part of the peer review process. This workshop will explore how to think about and report potential negative consequences in our papers in a way that’s practical, inclusive, and achievable. The aim is to draw on scholarship around creative-yet-grounded speculation about technology futures and to consider how these might be applied to publication and peer review. The workshop aims to inspire the CHI conference and the computing research community to meaningfully consider and act upon the potential negative implications of their work.
Towards Risk Indication In Mountain Biking Using Smart Wearables

Mountain biking as a recreational sport is currently thriving. During the ongoing COVID-19 pandemic, even more people started compensating for a lack of activity through individual outdoor sports, such as cycling. However, when executed beyond paved forest roads, mountain biking is a sport with subjective and objective risks, in which crashes often can not be entirely avoided and athletes may get injured. In this late-breaking work, we showcase a concept for a crash risk indication application for sports smartwatches. First, we review a wide range of related work, which formed the basis for our crash risk indication metric. We discuss options for the sensor-based detection of internal and external risk factors and propose a way to aggregate them, which will allow dynamic and potentially automatic fine-tuning by observing or obtaining feedback from the athlete. In addition, we present a concept for a smartwatch application that will provide constant feedback and an unobtrusive signal to the athlete when an unusually high risk is detected. Finally, we give an outlook on the necessary steps to implement our approach as a smartwatch app.
Security Notifications in Static Analysis Tools: Developers’ Attitudes, Comprehension, and Ability to Act on Them

Static analysis tools (SATs) have the potential to assist developers in finding and fixing vulnerabilities in the early stages of software development, requiring them to be able to understand and act on tools’ notifications. To understand how helpful such SAT guidance is to developers, we ran an online experiment (N=132) where participants were shown four vulnerable code samples (SQL injection, hard-coded credentials, encryption, and logging sensitive data) along with SAT guidance, and asked to indicate the appropriate fix. Participants had a positive attitude towards both SAT notifications and particularly liked the example solutions and vulnerable code. Seeing SAT notifications also led to more detailed open-ended answers and slightly improved code correction answers. Still, most SAT (SpotBugs 67%, SonarQube 86%) and Control (96%) participants answered at least one code-correction question incorrectly. Prior software development experience, perceived vulnerability severity, and answer confidence all positively impacted answer accuracy.
Enhancing the Perceived Emotional Intelligence of Conversational Agents through Acoustic Cues

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.
Assessing Social Anxiety Through Digital Biomarkers Embedded in a Gaming Task

Digital biomarkers of mental health issues offer many advantages, including timely identification for early intervention, ongoing assessment during treatment, and reducing barriers to assessment stemming from geography, age, fear, or disparities in access to systems of care. Embedding digital biomarkers into games may further increase the reach of digital assessment. In this study, we explore game-based digital biomarkers for social anxiety, based on interaction with a non-player character (NPC). We show that social anxiety affects a player's accuracy and their movement path in a gaming task involving an NPC. Further, we compared first versus third-person camera perspectives and the use of customized versus predefined avatars to explore the influence of common game interface factors on the expression of social anxiety through in-game movements. Our findings provide new insights about how game-based digital biomarkers can be effectively used for social anxiety, affording the benefits of early and ongoing digital assessment.
Typing Efficiency and Suggestion Accuracy Influence the Benefits and Adoption of Word Suggestions

Suggesting words to complete a given sequence of characters is a common feature of typing interfaces. Yet, previous studies have not found a clear benefit, some even finding it detrimental. We report on the first study to control for two important factors, word suggestion accuracy and typing efficiency. Our accuracy factor is enabled by a new methodology that builds on standard metrics of word suggestions. Typing efficiency is based on device type. Results show word suggestions are used less often in a desktop condition, with little difference between tablet and phone conditions. Very accurate suggestions do not improve entry speed on desktop, but do on tablet and phone. Based on our findings, we discuss implications for the design of automation features in typing systems.
RElectrode: A Reconfigurable Electrode For Multi-Purpose Sensing Based on Microfluidics

In this paper, we propose a reconfigurable electrode, RElectrode, using a microfluidic technique that can change the geometry and material properties of the electrode to satisfy the needs for sensing a variety of different types of user input through touch/touchless gestures, pressure, temperature, and distinguish between different types of objects or liquids. Unlike the existing approaches, which depend on the specific-shaped electrode for particular sensing (e.g., coil for inductive sensing), RElectrode enables capacity, inductance, resistance/pressure, temperature, pH sensings all in a single package. We demonstrate the design and fabrication of the microfluidic structure of our RElectrode, evaluate its sensing performance through several studies, and provide some unique applications. RElectrode demonstrates technical feasibility and application values of integrating physical and biochemical properties of microfluidics into novel sensing interfaces.
Soma-noti: Delivering Notifications Through Under-clothing Wearables

Different form factors of wearable technology provide unique opportunities for output based on how they are connected to the human body. In this work, we investigate the idea of delivering notifications through devices worn on the underside of a user’s clothing. A wearable worn in such a manner is in direct contact with the user’s skin. We leverage this proximity to test the performance of 10 on-skin sensations (Press, Poke, Pinch, Heat, Cool, Blow, Suck, Vibrate, Moisture and Brush) as methods of notification delivery. We developed prototypes for each stimulus and conducted a user study to evaluate them across 6 locations commonly covered by upper body clothing. Results indicate significant differences in reaction time, error rates and comfort which may influence the design of future under-clothing wearables.
Touch without Touching: Overcoming Social Distancing in Semi-Intimate Relationships with SansTouch

Social distancing may force people to restrict social touch practices. Our survey (N=136) highlighted substantial social touch breakdowns during the COVID-19 pandemic for semi-intimate relationships (e.g., friends, colleagues), with handshakes being the most reduced, and frustrations at having to re-establish social touch habits. We then designed SansTouch, a multi-modal hand sleeve used together along with a smartphone to enable mediated hand-to-hand interactions such as handshakes or holding hands. To invoke the mediated touch, users synchronously mimic the hand position as in real life while holding SansTouch. Users can feel the touch sensation in real time without touching. Participants from our observational study (N=12) quickly adopted the hand-to-hand interactions of SansTouch for exchanging greetings face-to-face with colleagues and reported stronger preferences towards using SansTouch as opposed to mid-air gestures (e.g., waving). We discuss design implications, including the trade-offs of multi-modality for touch devices in face-to-face communication.