Socially Adaptive Autonomous Vehicles: Effects of Contingent Driving Behavior on Drivers' ExperiencesSocial scientists have argued that autonomous vehicles (AVs) need to act as effective social agents; they have to respond implicitly to other drivers' behaviors as human drivers would. In this paper, we investigate how contingent driving behavior in AVs influences human drivers' experiences. We compared three algorithmic driving models: one trained on human driving data that responds to interactions (a familiar contingent behavior) and two artificial models that intend to either always-yield or never-yield regardless of how the interaction unfolds (non-contingent behaviors). Results show that a familiar contingent behavior significantly reduces drivers' hesitance and stress when interacting with AVs. The direct relationship between familiar contingency and positive experience indicates that AVs should incorporate socially familiar driving patterns through contextually-adaptive algorithms to improve the chances of successful deployment and acceptance in mixed human-AV traffic environments.2025CYChishang "Mario" Yang et al.Automated Driving Interface & Takeover DesignAI-Assisted Decision-Making & AutomationAutoUI
ConTextural: A Toolpath-Based Texture Editing Tool for Extrusion 3D PrintersRecently, there has been increased interest in design tools for creating textures using toolpath manipulation for extrusion-based 3D printers. Most tools are limited in their ability to edit existing 3D models and the variety of possible textures. Here, we present ConTextural, a design tool for adding texture to existing 3D models using toolpath manipulation. Using a coloring-based user interface, ConTextural allows users to draw textures on 3D models. Inspired by knitting structures, we introduce the concept of texture primitives, constructing texture structures that enable abundant possibilities for texture patterns. We include a curated texture library, enabling users to easily craft intricate and personalized designs. We assess the tool’s impact on users' expressiveness, engagement, and satisfaction using a user study and demonstrate how it helps to produce uniquely distinct designs from a single 3D model. Additionally, we provide design examples highlighting functional applications for adding textures to existing 3D models.2025DKToni Kaplan et al.Technion Institute of TechnologyDesktop 3D Printing & Personal FabricationCustomizable & Personalized ObjectsCHI
Selective Water-Based Hardening of Polyvinyl Alcohol (PVA) Knitted TextilesThe increasing emphasis on sustainable practices in HCI requires the development of new materials-based approaches for fabrication, which consider degradation and recycling. In particular, textile products containing rigid elements are usually hard to recycle since they are assembled from different materials, which must be disassembled before recycling. We introduce a novel method for fabricating knitted textile objects containing both soft and rigid segments using PVA (Polyvinyl Alcohol). PVA is a biodegradable synthetic material that dissolves in water. When exposed to a controlled amount of water and dried, the textile hardens and becomes rigid. We contribute a hardening method and protocol. Additionally, we present methods to achieve selective hardening by using intarsia knitting with two types of PVA. After being subjected to the hardening protocol, one type of PVA hardens while the other remains soft. To illustrate the potential, capabilities, and applications, a series of selectively hardened knitted objects are presented.2025SAShahar Asor et al.Technion, Architecture and Town PlanningShape-Changing Interfaces & Soft Robotic MaterialsSustainable HCIEcological Design & Green ComputingCHI
Modeling Social Situation Awareness in Driving InteractionsThe design of self-driving vehicles requires an understanding of the social interactions between drivers in resolving vague encounters, such as at un-signalized intersections. In this paper, we make the case for social situation awareness as a model for understanding everyday driving interaction. Using a dual-participant VR driving simulator, we collected data from driving encounter scenarios to understand how (N=170) participant drivers behave with respect to one another. Using a social situation awareness questionnaire we developed, we assessed the participants' social awareness of other driver’s direction of approach to the intersection, and also logged signaling, speed and speed change, and heading of the vehicle. Drawing upon the statistically significant relationships in the variables in the study data, we propose a Social Situation Awareness model based on the approach, speed, change of speed, heading and explicit signaling from drivers.2024NKNavit Klein et al.Automated Driving Interface & Takeover DesignV2X (Vehicle-to-Everything) Communication DesignAutoUI
HUGO, a High-Resolution Tactile Emulator for Complex SurfacesMany of our activities rely on tactile feedback perceived through mechanoreceptors in our skin. While visual and auditory devices provide immersive experiences, cutaneous feedback devices are typically limited in the range of sensations they provide and are hence usually used and tested on relatively simple synthetic surfaces. We present a device designed in a human-centered process, triggering the mechanoreceptors sensitive to pressure, low-frequency vibrations, and high-frequency vibrations, enabling one to experience touch of complex real-world surfaces. The device is based on a parallel manipulator and a pin-array, that operate simultaneously at 200Hz and emulate coarse and fine geometrical features, respectively. The decomposition into coarse and fine features, alongside the high operation frequency, enable simulation of virtual surfaces. This was corroborated via experiments on complex real-world surfaces via both a quantitative recognition test and a usability questionnaire. We believe that this design can be incorporated in numerous applications.2023YHYair Herbst et al.Technion - Israel Institute of TechnologyIn-Vehicle Haptic, Audio & Multimodal FeedbackVibrotactile Feedback & Skin StimulationCHI
Stop the [Image] Steal: The Role and Dynamics of Visual Content in the 2020 U.S. Election Misinformation CampaignImages are powerful. Visual information can be useful in attracting attention, improve persuasion, trigger stronger emotions, and is easy to share and spread. We examine the characteristics of the popular images shared on Twitter as part of ``Stop the Steal'', the widespread misinformation campaign during the 2020 U.S. election. We analyze the spread of the forty images that were shared the most on Twitter as part of this campaign. Using a coding process, we categorize and label the images according to their type, content, origin, and role, and perform a mixed-method analysis of these images’ spread on Twitter. Our results show that popular images include both photographs and text rendered as image. Only very few of these popular images included alleged photographic evidence of fraud; and none of the popular photographs had been manipulated. Most images reached a significant portion of their total spread within several hours from their first appearance, and popular- and less-popular accounts were both involved in various stages of their spread.2022HMHana Matatov et al.Politics, Polarization and Partisanship; Politics, Polarization and PartisanshipCSCW
The Effects of Warmth and Competence Perceptions on Users' Choice of an AI SystemPeople increasingly rely on Artificial Intelligence (AI) based systems to aid decision-making in various domains and often face a choice between alternative systems. We explored the effects of users' perception of AI systems' warmth (perceived intent) and competence (perceived ability) on their choices. In a series of studies, we manipulated AI systems' warmth and competence levels. We show that, similar to the judgments of other people, there is often primacy for warmth over competence. Specifically, when faced with a choice between a high-competence system and a high-warmth system, more participants preferred the high-warmth system. Moreover, the precedence of warmth persisted even when the high-warmth system was overtly deficient in its competence compared to an alternative high competence-low warmth system. The current research proposes that it may be vital for AI systems designers to consider and communicate the system's warmth characteristics to its potential users.2021ZGZohar Gilad et al.Technion – Israel Institute of TechnologyAI Ethics, Fairness & AccountabilityAlgorithmic Transparency & AuditabilityCHI
Evaluating Expert Curation in a Baby Milestone Tracking AppEarly childhood developmental screening is critical for timely detection and intervention. babyTRACKS (Formerly Baby CROINC, CROwd INtelligence Curation.) is a free, live, interactive developmental tracking mobile app with over 3,000 children's diaries. Parents write or select short milestone texts, like "began taking first steps," to record their babies' developmental achievements, and receive crowd-based percentiles to evaluate development and catch potential delays.<br>Currently, an expert-based Curated Crowd Intelligence (CCI) process manually groups incoming novel parent-authored milestone texts according to their similarity to existing milestones in the database (for example, starting to walk), or determining that the milestone represents a new developmental concept not seen before in another child's diary. CCI cannot scale well, however, and babyTRACKS is mature enough, with a rich enough database of existing milestone texts, to now consider machine learning tools to replace or assist the human curators. Three new studies explore (1) the usefulness of automation, by analyzing the human cost of CCI and how the work is currently broken down; (2) the validity of automation, by testing the inter-rater reliability of curators; and (3) the value of automation, by appraising the "real world" clinical value of milestones when assessing child development.<br>We conclude that automation can indeed be appropriate and helpful for a large percentage, though not all, of CCI work. We further establish realistic upper bounds for algorithm performance; confirm that the babyTRACKS milestones dataset is valid for training and testing purposes; and verify that it represents clinically meaningful developmental information.2019ABAyelet Ben-Sasson et al.University of HaifaCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Special Education TechnologyMental Health Apps & Online Support CommunitiesCHI