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Laura M. Vardoulakis

dblp:402/9933 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0009-9818-9334ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 2 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
2 papers
Human-AI interaction · 100%
Interdisciplinary, comprehensive, and emerging computing
2 papers
Medical and health informatics · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-AI interaction › human-centered AI
participatory AI
0.912025
Participatory AI Considerations for Advancing Racial Health Equity · CHI 2025

Methods — techniques the papers use, named apart from their topics

qualitative workshops · 2.0participatory design · 1.7
YearPublicationVenuePosition
2026 Promise or Peril? Exploring Black Adults' Perspectives on the Use of Artificial Intelligence in Health Contexts
abstract
As artificial intelligence (AI) is rapidly integrated into healthcare, ensuring that this innovation helps to combat health inequities requires engaging marginalized communities in health AI futuring. However, little research has examined Black populations’ perspectives on the use of AI in health contexts, despite the widespread health inequities they experience–inequities that are already perpetuated by AI. Addressing this research gap, through qualitative workshops with 18 Black adults, we characterize participants’ cautious optimism for health AI addressing structural well-being barriers (e.g., by providing second opinions that introduce fairness into an unjust healthcare system), and their concerns that AI will worsen health inequities (e.g., through health AI biases they deemed inevitable and the problematic reality of having to trust healthcare providers to use AI equitably). We advance health AI research by articulating previously-unreported health AI perspectives from a population experiencing significant health inequities, and presenting key considerations for future work.
Andrea G. Parker, Laura M. Vardoulakis, Christina N. Harrington
CHI2
2025 Participatory AI Considerations for Advancing Racial Health Equity
Andrea G. Parker, Laura M. Vardoulakis, Jatin Alla, Christina N. Harrington
CHI2