arXiv subjects

Allison Woodruff

Publications and source records attributed to Allison Woodruff.

At least 19 recordsLinked to original sources

arXiv2025

How Generative AI Empowers Attackers and Defenders Across the Trust & Safety Landscape

Generative AI (GenAI) is a powerful technology poised to reshape Trust & Safety. While misuse by attackers is a growing concern, its defensive capacity remains underexplored. This paper examines these effects through a qualitative study with 43 Trust & Safety experts across five domains: child safety, election integrity, hate and harassment, scams, and violent extremism. Our findings characterize a landscape in which GenAI empowers both attackers and defenders. GenAI dramatically increases the scale and speed of attacks, lowering the barrier to entry for creating harmful content, including sophisticated propaganda and deepfakes. Conversely, defenders envision leveraging GenAI to detect and mitigate harmful content at scale, conduct investigations, deploy persuasive counternarratives, improve moderator wellbeing, and offer user support. This work provides a strategic framework for understanding GenAI's impact on Trust & Safety and charts a path for its responsible use in creating safer online environments.

cs.HC↗

arXiv2025

A Risk Assessment Framework for Digital Identification Systems

We introduce a risk assessment framework for digital identification systems, as well as recommended best practices to enhance privacy, security, and other desirable properties in these systems. To generate these resources, we created a casebook of a wide range of digital identification systems, and we then applied expert analysis and critique to identify patterns. We piloted the framework on several reviews within our organization over a period of approximately one year, and found it to be robust and helpful for those reviews. This work is intended to inform product review and development, product policy, and standards efforts, and to help guide a consistent responsible approach to digital identification across the broader digital identification ecosystem.

cs.CY↗

arXiv2024

How Knowledge Workers Think Generative AI Will (Not) Transform Their Industries

Generative AI is expected to have transformative effects in multiple knowledge industries. To better understand how knowledge workers expect generative AI may affect their industries in the future, we conducted participatory research workshops for seven different industries, with a total of 54 participants across three US cities. We describe participants' expectations of generative AI's impact, including a dominant narrative that cut across the groups' discourse: participants largely envision generative AI as a tool to perform menial work, under human review. Participants do not generally anticipate the disruptive changes to knowledge industries currently projected in common media and academic narratives. Participants do however envision generative AI may amplify four social forces currently shaping their industries: deskilling, dehumanization, disconnection, and disinformation. We describe these forces, and then we provide additional detail regarding attitudes in specific knowledge industries. We conclude with a discussion of implications and research challenges for the HCI community.

cs.CY↗

arXiv2021

Exciting, Useful, Worrying, Futuristic: Public Perception of Artificial Intelligence in 8 Countries

As the influence and use of artificial intelligence (AI) have grown and its transformative potential has become more apparent, many questions have been raised regarding the economic, political, social, and ethical implications of its use. Public opinion plays an important role in these discussions, influencing product adoption, commercial development, research funding, and regulation. In this paper we present results of an in-depth survey of public opinion of artificial intelligence conducted with 10,005 respondents spanning eight countries and six continents. We report widespread perception that AI will have significant impact on society, accompanied by strong support for the responsible development and use of AI, and also characterize the public's sentiment towards AI with four key themes (exciting, useful, worrying, and futuristic) whose prevalence distinguishes response to AI in different countries.

cs.CY↗

arXiv2020

"A cold, technical decision-maker": Can AI provide explainability, negotiability, and humanity?

Algorithmic systems are increasingly deployed to make decisions in many areas of people's lives. The shift from human to algorithmic decision-making has been accompanied by concern about potentially opaque decisions that are not aligned with social values, as well as proposed remedies such as explainability. We present results of a qualitative study of algorithmic decision-making, comprised of five workshops conducted with a total of 60 participants in Finland, Germany, the United Kingdom, and the United States. We invited participants to reason about decision-making qualities such as explainability and accuracy in a variety of domains. Participants viewed AI as a decision-maker that follows rigid criteria and performs mechanical tasks well, but is largely incapable of subjective or morally complex judgments. We discuss participants' consideration of humanity in decision-making, and introduce the concept of 'negotiability,' the ability to go beyond formal criteria and work flexibly around the system.

cs.CY↗

arXiv2020

Explainability Case Studies

Explainability is one of the key ethical concepts in the design of AI systems. However, attempts to operationalize this concept thus far have tended to focus on approaches such as new software for model interpretability or guidelines with checklists. Rarely do existing tools and guidance incentivize the designers of AI systems to think critically and strategically about the role of explanations in their systems. We present a set of case studies of a hypothetical AI-enabled product, which serves as a pedagogical tool to empower product designers, developers, students, and educators to develop a holistic explainability strategy for their own products.

cs.CY↗

arXiv2019

Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements

As more researchers have become aware of and passionate about algorithmic fairness, there has been an explosion in papers laying out new metrics, suggesting algorithms to address issues, and calling attention to issues in existing applications of machine learning. This research has greatly expanded our understanding of the concerns and challenges in deploying machine learning, but there has been much less work in seeing how the rubber meets the road. In this paper we provide a case-study on the application of fairness in machine learning research to a production classification system, and offer new insights in how to measure and address algorithmic fairness issues. We discuss open questions in implementing equality of opportunity and describe our fairness metric, conditional equality, that takes into account distributional differences. Further, we provide a new approach to improve on the fairness metric during model training and demonstrate its efficacy in improving performance for a real-world product

cs.LG↗

arXiv2009

A Vehicle for Research: Using Street Sweepers to Explore the Landscape of Environmental Community Action

Researchers are developing mobile sensing platforms to facilitate public awareness of environmental conditions. However, turning such awareness into practical community action and political change requires more than just collecting and presenting data. To inform research on mobile environmental sensing, we conducted design fieldwork with government, private, and public interest stakeholders. In parallel, we built an environmental air quality sensing system and deployed it on street sweeping vehicles in a major U.S. city; this served as a "research vehicle" by grounding our interviews and affording us status as environmental action researchers. In this paper, we present a qualitative analysis of the landscape of environmental action, focusing on insights that will help researchers frame meaningful technological interventions.

cs.HC↗

arXiv2007

Sabbath Day Home Automation: "It's Like Mixing Technology and Religion"

We present a qualitative study of 20 American Orthodox Jewish families' use of home automation for religious purposes. These lead users offer insight into real-life, long-term experience with home automation technologies. We discuss how automation was seen by participants to contribute to spiritual experience and how participants oriented to the use of automation as a religious custom. We also discuss the relationship of home automation to family life. We draw design implications for the broader population, including surrender of control as a design resource, home technologies that support long-term goals and lifestyle choices, and respite from technology.

cs.HC↗

arXiv2006

Where's the "Party" in "Multi-Party"? Analyzing the Structure of Small-Group Sociable Talk

Spontaneous multi-party interaction - conversation among groups of three or more participants - is part of daily life. While automated modeling of such interactions has received increased attention in ubiquitous computing research, there is little applied research on the organization of this highly dynamic and spontaneous sociable interaction within small groups. We report here on an applied conversation analytic study of small-group sociable talk, emphasizing structural and temporal aspects that can inform computational models. In particular, we examine the mechanics of multiple simultaneous conversational floors - how participants initiate a new floor amidst an on-going floor, and how they subsequently show their affiliation with one floor over another. We also discuss the implications of these findings for the design of "smart" multi-party applications.

cs.HC↗

arXiv2005

Making Space for Stories: Ambiguity in the Design of Personal Communication Systems

Pervasive personal communication technologies offer the potential for important social benefits for individual users, but also the potential for significant social difficulties and costs. In research on face-to-face social interaction, ambiguity is often identified as an important resource for resolving social difficulties. In this paper, we discuss two design cases of personal communication systems, one based on fieldwork of a commercial system and another based on an unrealized design concept. The cases illustrate how user behavior concerning a particular social difficulty, unexplained unresponsiveness, can be influenced by technological issues that result in interactional ambiguity. The cases also highlight the need to balance the utility of ambiguity against the utility of usability and communicative clarity.

cs.HC↗

arXiv2004

Detecting User Engagement in Everyday Conversations

This paper presents a novel application of speech emotion recognition: estimation of the level of conversational engagement between users of a voice communication system. We begin by using machine learning techniques, such as the support vector machine (SVM), to classify users' emotions as expressed in individual utterances. However, this alone fails to model the temporal and interactive aspects of conversational engagement. We therefore propose the use of a multilevel structure based on coupled hidden Markov models (HMM) to estimate engagement levels in continuous natural speech. The first level is comprised of SVM-based classifiers that recognize emotional states, which could be (e.g.) discrete emotion types or arousal/valence levels. A high-level HMM then uses these emotional states as input, estimating users' engagement in conversation by decoding the internal states of the HMM. We report experimental results obtained by applying our algorithms to the LDC Emotional Prosody and CallFriend speech corpora.

cs.SD↗

arXiv2004

"User Interfaces" and the Social Negotiation of Availability

In current presence or availability systems, the method of presenting a user's state often supposes an instantaneous notion of that state - for example, a visualization is rendered or an inference is made about the potential actions that might be consistent with a user's state. Drawing on observational research on the use of existing communication technology, we argue (as have others in the past) that determination of availability is often a joint process, and often one that takes the form of a negotiation (whether implicit or explicit). We briefly describe our current research on applying machine learning to infer degrees of conversational engagement from observed conversational behavior. Such inferences can be applied to facilitate the implicit negotiation of conversational engagement - in effect, helping users to weave together the act of contact with the act of determining availability.

cs.HC↗

arXiv2004

Conversation Analysis and the User Experience

We provide two case studies in the application of ideas drawn from conversation analysis to the design of technologies that enhance the experience of human conversation. We first present a case study of the design of an electronic guidebook, focusing on how conversation analytic principles played a role in the design process. We then discuss how the guidebook project has inspired our continuing work in social, mobile audio spaces. In particular, we describe some as yet unrealized concepts for adaptive audio spaces.

cs.HC↗

arXiv2003

How Push-To-Talk Makes Talk Less Pushy

This paper presents an exploratory study of college-age students using two-way, push-to-talk cellular radios. We describe the observed and reported use of cellular radio by the participants. We discuss how the half-duplex, lightweight cellular radio communication was associated with reduced interactional commitment, which meant the cellular radios could be used for a wide range of conversation styles. One such style, intermittent conversation, is characterized by response delays. Intermittent conversation is surprising in an audio medium, since it is typically associated with textual media such as instant messaging. We present design implications of our findings.

cs.HC↗

arXiv2003

Media Affordances of a Mobile Push-To-Talk Communication Service

This paper presents an exploratory study of college-age students using two-way, push-to-talk cellular radios. We describe the observed and reported use of cellular radio by the participants, the activities and purposes for which they adopted it, and their responses. We then examine these empirical results using mediated communication theory. Cellular radios have a unique combination of affordances relative to other media used by this age group, including instant messaging (IM) and mobile phones; the results of our analysis do suggest explanations for some observed phenomena but also highlight the counter-intuitive nature of other phenomena. For example, although the radios have many important dissimilarities with IM from the viewpoint of mediated communication theory, the observed use patterns resembled those of IM to a surprising degree.

cs.HC↗

arXiv2003

The Mad Hatter´s Cocktail Party: A Social Mobile Audio Space Supporting Multiple Simultaneous Conversations

This paper presents a mobile audio space intended for use by gelled social groups. In face-to-face interactions in such social groups, conversational floors change frequently, e.g., two participants split off to form a new conversational floor, a participant moves from one conversational floor to another, etc. To date, audio spaces have provided little support for such dynamic regroupings of participants, either requiring that the participants explicitly specify with whom they wish to talk or simply presenting all participants as though they are in a single floor. By contrast, the audio space described here monitors participant behavior to identify conversational floors as they emerge. The system dynamically modifies the audio delivered to each participant to enhance the salience of the participants with whom they are currently conversing. We report a user study of the system, focusing on conversation analytic results.

cs.HC↗

arXiv2002

Eavesdropping on Electronic Guidebooks: Observing Learning Resources in Shared Listening Environments

We describe an electronic guidebook, Sotto Voce, that enables visitors to share audio information by eavesdropping on each other's guidebook activity. We have conducted three studies of visitors using electronic guidebooks in a historic house: one study with open air audio played through speakers and two studies with eavesdropped audio. An analysis of visitor interaction in these studies suggests that eavesdropped audio provides more social and interactive learning resources than open air audio played through speakers.

cs.HC↗