Margaret Burnett

schoolOregon State Universitybar_chart#887 Global Rank

Total Papers

HCI Rank

#887

Research Areas

Years Active

Recent Publications

"Over-the-Hood" AI Inclusivity Bugs and How 3 AI Product Teams Found and Fixed Them

While much research has shown the presence of AI's "under-the-hood'" biases (e.g., algorithmic, training data, etc.), what about "over-the-hood" inclusivity biases: barriers in user-facing AI products that disproportionately exclude users with certain problem-solving approaches? Recent research has begun to report the…

CHI '26CorrespondingProgramming Education & Computational Thinking +2

"Fast, easy, simple"? SES-diverse transfer students' sociotechnical experiences registering for classes

Recruiting, retaining, and educating students in computing is a frequent research topic in CHI. However, students' sociotechnical experiences of registering for classes are understudied -- especially those of socioeconomic-diverse students. These experiences matter: research shows that registration problems bring long…

IUI '25CorrespondingAI Ethics, Fairness & Accountability +2

Measuring User Experience Inclusivity in Human-AI Interaction via Five User Problem-Solving Styles

Motivations: Recent research has emerged on generally how to improve AI products’ human-AI interaction (HAI) user experience (UX), but relatively little is known about HAI-UX inclusivity. For example, what kinds of users are supported, and who are left out? What product changes would make it more inclusive? Objective…

CHI '24CorrespondingCollaborative Learning & Peer Teaching +2

The Matchmaker Inclusive Design Curriculum: A Faculty-Enabling Curriculum to Teach Inclusive Design Throughout Undergraduate CS

Despite efforts to raise awareness of societal and ethical issues in CS education, research shows students often do not act upon their new awareness (Problem 1). One such issue, well-established by HCI research, is that much of technology contains barriers impacting numerous populations—such as minoritized genders, ra…

IUI '225th+ AuthorAI-Assisted Decision-Making & Automation

TiiS: After-Action Review for AI (AAR/AI)

Dodge 等人提出 AAR/AI 行动后复盘框架，旨在通过人工智能辅助技术改进决策回顾与反思过程。

IUI '22CorrespondingExplainable AI (XAI) +1

How Do People Rank Multiple Mutant Agents?

How might a person decide on which of several AI-powered sequential decision-making systems to rely? For example, imagine car buyer Blair shopping for a self-driving car, or developer Dillon trying to choose an appropriate ML model to use in their application. Their first choice might be infeasible (e.g., too expensiv…

CHI '19CorrespondingInclusive Design +1

From Gender Biases to Gender-Inclusive Design: An Empirical Investigation

In recent years, research has revealed gender biases in numerous software products. But although some researchers have found ways to improve gender participation in specific software projects, general methods focus mainly on detecting gender biases -- not fixing them. To help fill this gap, we investigated whether the…

CHI '18CorrespondingExplainable AI (XAI) +2

How the Experts Do It: Assessing and Explaining Agent Behaviors in Real-Time Strategy Games

How should an AI-based explanation system explain an agent's complex behavior to ordinary end users who have no background in AI? Answering this question is an active research area, for if an AI-based explanation system could effectively explain intelligent agents' behavior, it could enable the end users to understand…

CHI '183rd AuthorGender & Race Issues in HCI

Panel: Extending Conversations about Gender and HCI

This panel aims to create a space for participants at CHI 2018 to see how far we have come as a community in raising and addressing issues of gender, and how far we have yet to go. Our intent is for open discussion to support the community’s intentions to move towards greater equity, inclusivity, and diversity.

IUI '18CorrespondingExplainable AI (XAI) +2

Toward Foraging for Understanding of StarCraft Agents: An Empirical Study

Assessing and understanding intelligent agents is a difficult task for users that lack an AI background. A relatively new area, called "Explainable AI," is emerging to help address this problem, but little is known about how users would forage through information an explanation system might offer. To inform the develo…

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