Input Visualization: Collecting and Modifying Data with Visual RepresentationsWe examine input visualizations, visual representations that are designed to collect (and represent) new data rather than encode preexisting datasets. Information visualization is commonly used to reveal insights and stories within existing data. As a result, most contemporary visualization approaches assume existing datasets as the starting point for design, through which that data is mapped to visual encodings. Meanwhile, the implications of visualizations as inputs and as data sources have received little attention—despite the existence of visual and physical examples stretching back centuries. In this paper, we present a design space of 50 input visualizations analyzing their visual representation, data, artifact, context, and input. Based on this, we identify input modalities, purposes of input visualizations, and a set of design considerations. Finally, we discuss the relationship between input visualization and traditional visualization design and suggest opportunities for future research to better understand these visual representations and their potential.2024NBNathalie Bressa et al.Télécom Paris, IP ParisData StorytellingPrototyping & User TestingCHI
AI is Entering Regulated Territory: Understanding the Supervisors' Perspective for Model Justifiability in Financial Crime DetectionArtificial intelligence (AI) has the potential to bring significant benefits to highly regulated industries such as healthcare or banking. Adoption, however, remains low. AI's entry into complex socio-techno-legal systems raises issues of transparency, specifically for regulators. However, the perspective of supervisors, regulators who monitor compliance with applicable financial regulations, has rarely been studied. This paper focuses on understanding the needs of supervisors in anti-money laundering (AML) to better inform the design of AI justifications and explanations in highly regulated fields. Through scenario-based workshops with 13 supervisors and 6 banking professionals, we outline the auditing practices and socio-technical context of the supervisor. By combining the workshops’ insights with an analysis of compliance requirements, we identify the AML obligations that conflict with AI opacity. We then formulate seven needs that supervisors have for model justifiability. We discuss the role of explanations as reliable evidence on which to base justifications.2024ABAstrid Bertrand et al.Télécom Paris, Institut Polytechnique de ParisExplainable AI (XAI)AI Ethics, Fairness & AccountabilityAlgorithmic Fairness & BiasCHI
BubbleTex: Designing Heterogenous Wettable Areas for Carbonation Bubble Patterns on SurfacesMaterials are a key part of our daily experiences. Recently, researchers have been devising new ways to utilize materials directly from our physical world for the design of objects and interactions. We present a new fabrication technique that enables control of CO2 bubble positions and their size within carbonated liquids. Instead of soap bubbles, boiling water, or droplets, we show creation of patterns, images and text through sessile bubbles that exhibit a lifetime of several days. Surfaces with mixed wettability regions are created on glass and plastic using ceramic coatings or plasma projection leading to patterns that are relatively invisible to the human eye. Different regions react to liquids differently. Nucleation is activated after carbonated liquid is poured onto the surface with bubbles nucleating in hydrophobic regions with a strong adherence to the surface and can be controlled in size ranging from 0.5mm – 6.5mm. Bubbles go from initially popping or becoming buoyant during CO2 supersaturation to stabilizing at their positions within minutes. Technical evaluation shows stabilization under various conditions. Our design software allows users to import images and convert them into parametric pixelation forms conducive to fabrication that will result in nucleation of bubbles at required positions. Various applications are presented to demonstrate aspects that may be harnessed for a wide range of use in daily life. Through this work, we enable the use of carbonation bubbles as a new design material for designers and researchers.2023HSHarpreet Sareen et al.The University of Tokyo, Parsons School of DesignShape-Changing Interfaces & Soft Robotic MaterialsCustomizable & Personalized ObjectsCHI
On Selective, Mutable and Dialogic XAI: a Review of What Users Say about Different Types of Interactive ExplanationsExplainability (XAI) has matured in recent years to provide more human-centered explanations of AI-based decision systems. While static explanations remain predominant, interactive XAI has gathered momentum to support the human cognitive process of explaining. However, the evidence regarding the benefits of interactive explanations is unclear. In this paper, we map existing findings by conducting a detailed scoping review of 48 empirical studies in which interactive explanations are evaluated with human users. We also create a classification of interactive techniques specific to XAI and group the resulting categories according to their role in the cognitive process of explanation: "selective", "mutable" or "dialogic". We identify the effects of interactivity on several user-based metrics. We find that interactive explanations improve perceived usefulness and performance of the human+AI team but take longer. We highlight conflicting results regarding cognitive load and overconfidence. Lastly, we describe underexplored areas including measuring curiosity or learning or perturbing outcomes.2023ABAstrid Bertrand et al.Telecom Paris, Institut Polytechnique de ParisExplainable AI (XAI)AI-Assisted Decision-Making & AutomationCHI
The Dark Side of Perceptual Manipulations in Virtual Reality"Virtual-Physical Perceptual Manipulations'' (VPPMs) such as redirected walking and haptics expand the user's capacity to interact with Virtual Reality (VR) beyond what would ordinarily physically be possible. VPPMs leverage knowledge of the limits of human perception to effect changes in the user's physical movements, becoming able to (perceptibly and imperceptibly) nudge their physical actions to enhance interactivity in VR. We explore the risks posed by the malicious use of VPPMs. First, we define, conceptualize and demonstrate the existence of VPPMs. Next, using speculative design workshops, we explore and characterize the threats/risks posed, proposing mitigations and preventative recommendations against the malicious use of VPPMs. Finally, we implement two sample applications to demonstrate how existing VPPMs could be trivially subverted to create the potential for physical harm. This paper aims to raise awareness that the current way we apply and publish VPPMs can lead to malicious exploits of our perceptual vulnerabilities.2022WTWen-Jie Tseng et al.Institut Polytechnique de ParisImmersion & Presence ResearchDance & Body Movement ComputingCHI
Making Data Tangible: A Cross-disciplinary Design Space for Data PhysicalizationDesigning a data physicalization requires a myriad of different considerations. Despite the cross-disciplinary nature of these considerations, research currently lacks a synthesis across the different communities data physicalization sits upon, including their approaches, theories, and even terminologies. To bridge these communities synergistically, we present a design space that describes and analyzes physicalizations according to three facets: context (end-user considerations), structure (the physical structure of the artifact), and interactions (interactions with both the artifact and data). We construct this design space through a systematic review of 47 physicalizations and analyze the interrelationships of key factors when designing a physicalization. This design space cross-pollinates knowledge from relevant HCI communities, providing a cohesive overview of what designers should consider when creating a data physicalization while suggesting new design possibilities. We analyze the design decisions present in current physicalizations, discuss emerging trends, and identify underlying open challenges.2022SBS. Sandra Bae et al.University of Colorado BoulderData PhysicalizationCHI
Welcome to the Course: Early Social Cues Influence Women's Persistence in Computer ScienceFirst impressions influence subsequent behavior, especially when deciding how much effort to invest in an activity such as taking an online course. In computer programming courses, a context where social group stereotypes are salient, social cues early in the course can be used strategically to affirm members of historically underrepresented groups in their sense of belonging. We tested this idea in two randomized field experiments (N=53,922) by varying the social identity and status of the presenter of a welcome video and assessing online learners' persistence and achievement. Counter to our hypotheses, we found lower persistence among women in certain age groups if the welcome video was presented by a female instructor or by lower-status peers. Men remained unaffected. The results suggest that women are more responsive to social cues in online STEM courses, an environment where their social identity has been negatively stereotyped. Presenting a male and female instructor together was an effective strategy for retaining women in the course.2020RKRene F. Kizilcec et al.Cornell UniversityOnline Learning & MOOC PlatformsSTEM Education & Science CommunicationGender & Race Issues in HCICHI
Inclusive Education Technologies: Emerging Opportunities for People with Visual ImpairmentsTechnology has become central to many activities of learning, ranging from its use in classroom education to work training, mastering a new hobby, or acquiring new skills of living. While digitally-enhanced learning tools can provide valuable access to information and personalised support, people with specific accessibility needs, such as low or no vision, can often be excluded from their use. This requires technology developers to build more inclusive designs and to offer learning experiences that can be shared by people with mixed-visual abilities. There is also scope to integrate DIY approaches and provide specialised teachers with the ability to design their own low cost educational tools, adapted to pedagogical objectives and to the variety of visual and cognitive abilities of their students. For researchers, this invites new challenges of how to best support technology adoption and its evaluation in often complex educational settings. This workshop seeks to bring together researchers and practitioners interested in accessibility and education to share best practices and lessons learnt for technology in this space; and to jointly discuss and develop future directions for the next generation design of inclusive and effective education technologies.2018OMOussama Metatla et al.University of BristolCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Aging-Friendly Technology DesignUniversal & Inclusive DesignCHI
The Perils of Confounding Factors: How Fitts’ Law Experiments can Lead to False ConclusionsThe design of Fitts' historical reciprocal tapping experiment gravely confounds index of difficulty ID with target distance D: Summary statistics for the candidate Fitts model and a competing model may appear identical, and the validity of Fitts' model for some tasks can be legitimately questioned. We show that the contamination of ID by either target distance D or width W is due to the common practices of pooling and averaging data belonging to different distance-width (D,W) pairs for the same ID, and taking a geometric progression for values of D and W. We analyze a case study of the validation of Fitts' law in eye-gaze movements, where an unfortunate experimental design has misled researchers into believing that eye-gaze movements are not ballistic. We then provide simple guidelines to prevent confounds: Practitioners should carefully design the experimental conditions of (D,W), fully distinguish data acquired for different conditions, and put less emphasis on r² scores. We also recommend investigating the use of stochastic sampling for D and W.2018JGJulien Gori et al.Télécom ParisTech, Université Paris-SaclayUser Research Methods (Interviews, Surveys, Observation)Computational Methods in HCICHI
BIGFile: Bayesian Information Gain for Fast File RetrievalWe introduce BIGFile, a new fast file retrieval technique based on the Bayesian Information Gain framework. BIGFile provides interface shortcuts to assist the user in navigating to a desired target (file or folder). BIGFile’s split interface combines a traditional list view with an adaptive area that displays shortcuts to the set of file paths estimated by our computationally efficient algorithm. Users can navigate the list as usual, or select any part of the paths in the adaptive area. A pilot study of 15 users informed the design of BIGFile, revealing the size and structure of their file systems and their file retrieval practices. Our simulations show that BIGFile outperforms Fitchett et al.’s AccessRank, a best-of-breed prediction algorithm. We conducted an experiment to compare BIGFile with ARFile (AccessRank instantiated in a split interface) and with a Finder-like list view as baseline. BIGFile was by far the most efficient technique (up to 44% faster than ARFile and 64% faster than Finder), and participants unanimously preferred the split interfaces to the Finder.2018WLWanyu Liu et al.Telecom ParisTech, Université Paris-Saclay, Univ. Paris-Sud, CNRS, Inria, Université Paris-SaclayInteractive Data VisualizationTime-Series & Network Graph VisualizationVisualization Perception & CognitionCHI