BCNM at CHI 2020
CHI has been cancelled due to COVID-19, but let's celebrate the incredible work of our students, faculty, and alumni who were slated to present!
The ACM CHI Conference on Human Factors in Computing Systems is the premier international conference of Human-Computer Interaction, where researchers and practitioners gather to discuss the latest in interactive technology. We're thrilled so many BCNM members were selected to participate.
See below for a list of workshops, papers and projects by past and current BCNM members (highlighted in green). Don't see your name, email us at lara [at] berkeley.edu
Students
Noura Howell
Expanding Modes of Reflection in Design Futuring
Design futuring approaches, such as speculative design, design fiction and others, seek to (re)envision futures and explore alternatives. As design futuring becomes established in HCI design research, there is an opportunity to expand and develop these approaches. To that end, by reflecting on our own research and examining related work, we contribute five modes of reflection. These modes concern formgiving, temporality, researcher positionality, real-world engagement, and knowledge production. We illustrate the value of each mode through careful analysis of selected design exemplars and provide questions to interrogate the practice of design futuring. Each reflective mode offers productive resources for design practitioners and researchers to articulate their work, generate new directions for their work, and analyze their own and others' work.
LBW017: Teachable Machine: Approachable Web-Based Tool for Exploring Machine Learning Classification
Teachable Machine (teachablemachine.withgoogle.com) is a web-based GUI tool for creating custom machine learning classification models without specialized technical expertise. (Machine learning, or ML, lets systems learn to analyze data without being explicitly programmed.) We created it to help students, teachers, designers, and others learn about ML by creating and using their own classification models. Its broad uptake suggests it has empowered people to learn, teach, and explore ML concepts: People have created curriculum, tutorials, and other resources using Teachable Machine on topics like AI ethics at institutions including the Stanford d.school, NYU's Interactive Telecommunications Program, the MIT Media Lab, as well as creative experiments. Users in 201 countries have created over 125,000 classification models. Here we outline the project and its key contributions of (1) a flexible, approachable interface for ML classification models without ML or coding expertise, (2) a set of technical and design decisions that can inform future interactive machine learning tools, and (3) an example of how structured learning content surrounding the tool supports people accessing ML concepts.
Sarah Sterman
Interacting with Literary Style through Computational Tools
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.
Tonya Nguyen
Implications of Conversational Artificial Intelligence
The use of conversational AI has become more ubiquitous in public and private life. Al-though conversational artificial intelligence (AI) may be useful and seamless, using voice to mediate human-AI interaction raises potential privacy risks and socio-cultural implications for gender bias and childhood development. To better understand the downstream implications of AI, we pose a set of questions to frame how conversational AI and various stakeholders may interact within sociotechnical systems.
Faculty
Eric Paulos
Interacting with Literary Style through Computational Tools
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.
Bjoern Hartmann
Enabling Data-Driven API Design with Community Usage Data: A Need-Finding Study
APIs are becoming the fundamental building block of modern software and their usability is crucial to programming efficiency and software quality. Yet API designers find it hard to gather and interpret user feedback on their APIs. To close the gap, we interviewed 23 API designers from 6 companies and 11 open-source projects to understand their practices and needs. The primary way of gathering user feedback is through bug reports and peer reviews, as formal usability testing is prohibitively expensive to conduct in practice. Participants expressed a strong desire to gather real-world use cases and understand users' mental models, but there was a lack of tool support for such needs. In particular, participants were curious about where users got stuck, their workarounds, common mistakes, and unanticipated corner cases. We highlight several opportunities to address those unmet needs, including developing new mechanisms that systematically elicit users' mental models, building mining frameworks that identify recurring patterns beyond shallow statistics about API usage, and exploring alternative design choices made in similar libraries.
Composing Flexibly-Organized Step-by-Step Tutorials from Linked Source Code, Snippets, and Outputs (Honorable Mention)
Programming tutorials are a pervasive, versatile medium for teaching programming. In this paper, we report on the content and structure of programming tutorials, the pain points authors experience in writing them, and a design for a tool to help improve this process. An interview study with 12 experienced tutorial authors found that they construct documents by interleaving code snippets with text and illustrative outputs. It also revealed that authors must often keep related artifacts of source programs, snippets, and outputs consistent as a program evolves. A content analysis of 200 frequently-referenced tutorials on the web also found that most tutorials contain related artifactsduplicate code and outputs generated from snippetsthat an author would need to keep consistent with each other. To address these needs, we designed a tool called Torii with novel authoring capabilities. An in-lab study showed that tutorial authors can successfully use the tool for the unique affordances identified, and provides guidance for designing future tools for tutorial authoring.
LBW019: Supporting Circuit Design with a Block-Based, Generator Language
Modern electronic design automation (EDA) tooling tends to focus on either the system-level design or the low-level electrical connectivity between physical components on a printed circuit board (PCB). We believe that a usable and functional system for circuit design needs to be able to interleave both levels of abstraction seamlessly and allow designers to transition between them freely. Existing work has experimented with approaches like circuit synthesis, functional characterization, or fine grained physical modeling. Each of these approaches augment the design process as it exists today, with its fundamental split between various levels of abstraction. We notice that hierarchical block diagrams can capture both high-level system structure as well as fine grained physical connectivity, and use that symmetry to construct a model for electronic circuits that can span the entire design process. Additionally, we construct user interfaces for our model that can support users of different skill levels throughout a design task. We discuss the design of our system, detailing both fundamental abstractions and usability trade-offs, and demonstrate its current capabilities through the design of example electronics projects.
Alumni
Michelle Carney
LBW017: Teachable Machine: Approachable Web-Based Tool for Exploring Machine Learning Classification
Teachable Machine (teachablemachine.withgoogle.com) is a web-based GUI tool for creating custom machine learning classification models without specialized technical expertise. (Machine learning, or ML, lets systems learn to analyze data without being explicitly programmed.) We created it to help students, teachers, designers, and others learn about ML by creating and using their own classification models. Its broad uptake suggests it has empowered people to learn, teach, and explore ML concepts: People have created curriculum, tutorials, and other resources using Teachable Machine on topics like AI ethics at institutions including the Stanford d.school, NYU's Interactive Telecommunications Program, the MIT Media Lab, as well as creative experiments. Users in 201 countries have created over 125,000 classification models. Here we outline the project and its key contributions of (1) a flexible, approachable interface for ML classification models without ML or coding expertise, (2) a set of technical and design decisions that can inform future interactive machine learning tools, and (3) an example of how structured learning content surrounding the tool supports people accessing ML concepts.
Human-Centered Approaches to Fair and Responsible AI
As AI changes the way decisions are made in organizations and governments, it is ever more important to ensure that these systems work according to values that diverse users and groups find important. Researchers have proposed numerous algorithmic techniques to formalize statistical fairness notions, but emerging work suggests that AI systems must account for the real-world contexts in which they will be embedded in order to actually work fairly. These findings call for an expanded research focus beyond statistical fairness to that which includes fundamental understandings of human use and the social impact of AI systems, a theme central to the HCI community. The HCI community can contribute novel understandings, methods, and techniques for incorporating human values and cultural norms into AI systems; address human biases in developing and using AI; and empower individual users and society to audit and control AI systems. Our goal is to bring together academic and industry researchers in the fields of HCI, ML and AI, and the social sciences to devise a cross-disciplinary research agenda for fair and responsible AI systems. This workshop will build on previous algorithmic fairness workshops at AI and ML conferences, map research and design opportunities for future innovations, and disseminate them in each community.
Laura Devendorf
Craftspeople as Technical Collaborators: Lessons Learned through an Experimental Weaving Residency (Honorable Mention)
While craft has had increasing influence on HCI research, HCI researchers tend to engage craft in limited capacities, often focusing on the juxtapositions of "traditional" craft and "innovative" computing. In this paper, we describe the structure and results of a six-week "experimental weaving residency" to show how HCI practitioners, engineers, and craftspeople perform similar work and can productively collaborate to envision new technological interfaces at early stages of development. We address both social and technical challenges of residencies and critically reflect on biases about technical and craft labor that we held prior to the residency. We share our experiences and lessons learned in the hopes of supporting future collaborations with craftspeople and broadening the techniques we use to address design challenges.
Making Design Memoirs: Understanding and Honoring Difficult Experiences (Honorable Mention)
Design is commonly understood as a storytelling practice, yet we have few narratives with which to describe the felt experiences of struggle, pain, and difficulty, beyond treating them as subjects to resolve. This work uses the praxis of embodied design as a way to bring more complex narratives to the community for contemplation---to engage and entangle personal and difficult stories within a public context. We propose the term Design Memoirs for these first-person practices and reflections. Design Memoirs are subjective and corporeal in nature, and provide a direct and observable way to reckon with felt experiences through, and for, design. We demonstrate Design Memoirs by drawing on our own experiences as mothers, caregivers, and corporeal subjects. Following Barad, we propose a practice of diffractive reading to locate resonances between Design Memoirs which render difficult autobiographical material addressable, shareable, and open for new interpretations. We present this strategy as a method for arriving at deeper understandings of difficult experiences.
What HCI Can Learn from ASMR: Becoming Enchanted with the Mundane
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.
Unfabricate: Designing Smart Textiles for Disassembly
Smart textiles development is combining computing and textile technologies to create tactile, functional objects such as smart garments, soft medical devices, and space suits. However, the field also combines the massive waste streams of both the digital electronics and textiles industries. The following work explores how HCI researchers might be poised to address sustainability and waste in future smart textiles development through interventions at design time. Specifically, we perform a design inquiry into techniques and practices for reclaiming and reusing smart textiles materials and explore how such techniques can be integrated into smart textiles design tools. Beginning with a practice in sustainable or "slow" fashion, unravelling a garment into yarn, the suite of explorations titled "Unfabricate" probes values of time and labor in crafting a garment; speculates how a smart textile garment may be designed with reuse in mind; and imagines how electronic and textile components may be given new life in novel uses.
Uncertainty is prevalent characteristic of contemporary life, and a central challenge of HCI. This one-day workshop will explore how HCI has and might continue to engage uncertainty as a generative feature in design, as opposed to a force to mitigate and control. We hope to convene researchers from broad ranging areas to explore the many ways in which uncertainty appears in our research and the different types of responses that HCI has to offer. There is an incredible variety of conceptual formulations of uncertainty and related ideas like risk, ambiguity, and suspense that raise both difficult challenges as well as significant opportunities for creative engagement with societal challenges. During the workshop, we won't seek to "solve" uncertainty but rather expand the ways in which we think about and navigate it. In doing so, we will experiment with and contribute to new practices, methods, and concepts for embracing uncertainty. Outcomes of the workshop will include documentation of exercises designed to evoke uncertainty in participants, concept mappings, and a collection of short essays written and refined by participants.
Jingyi Li
LBW061: Laser Cut Layered Gels for Lighting Design
Recent advancements in lighting design have focused on the visualization and simulation of programmable LED lighting fixtures. However, single-bulb conventional fixtures alongside subtractive color filter gels are still widely used in many art galleries and installations, photography studios, and experimental theatres due to their low cost and existing prevalence in industry. We introduce a novel approach to creating lighting effects for single-bulb fixtures with gels, which enables designers to quickly and inexpensively produce complex, multi-colored effects approximating a target digital image. Our system uses a grid-based approach which cuts small openings in different colored gels and layers them together, forming color combinations when lit. Our work expands the design space of lighting gels with a precise and expressive method, enabling designers to experiment with novel lighting effects through an iterative personal fabrication process.
Supporting Visual Artists in Programming through Direct Inspection and Control of Program Execution
Programming offers new opportunities for visual art creation, but understanding and manipulating the abstract representations that make programming powerful can pose challenges for artists who are accustomed to manual tools and concrete visual interaction. We hypothesize that we can reduce these barriers through programming environments that link state to visual artwork output. We created Demystified Dynamic Brushes (DDB), a tool that bidirectionally links code, numerical data, and artwork across the programming interface and the execution environment – i.e., the artist's in-progress artwork. DDB automatically records stylus input as artists draw, and stores a history of brush state and output in relation to the input. This structure enables artists to inspect current and past numerical input, state, and output and control program execution through the direct selection of visual geometric elements in the drawing canvas. An observational study suggests that artists engage in program inspection when they can visually access geometric state information on the drawing canvas in the process of manual drawing.
You can also watch the video for this here and below!
More on the project here!
Bo Ruberg
Challenges of Designing Consent: Consent Mechanics in Video Games as Models for Interactive User Agency (Honorable Agency)
This paper argues for a conceptual framework that treats user consent in interactive technologies as a design challenge necessitating careful, culturally-informed consideration. We draw on recent work in HCI as well as queer and feminist theory that understands consent as rooted in negotiating agency in order to frame our exploration of unique difficulties and potential solutions to meaningful opportunities for user consent in the design of computational technologies. Through a critical analysis of three video games that offer different models of consent—each of which communicates different values through its design—we introduce the concept of consent mechanics. Consent mechanics describe designed interactions that allow players to consent to or opt out of in-game experiences, often those related to sexuality or intimacy. Here, we approach video games as windows onto design considerations surrounding interactive technologies more broadly, suggesting crucial questions and tactics for how to design user agency ethically into computational systems.