VLDB 2026 Research / reviewers in the wild / expert
Shixian Xie
dblp:341/8468
· DBLP profile ↗
5ranked-venue papers
3as first author
5since 2021 · last 2026
0000-0002-8438-9281ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 5 · 3 first-author · 5 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Investigating How Leaders Decide on AI Innovations: Opportunities for HCIabstractAround 90% of CEOs see AI as the “most critical technology for ensuring future profitability and competitiveness.” At the same time, up to 95% of AI projects fail. Currently, little is known about the leaders who approve and guide AI initiatives. We call them AI Deciders. This study investigates how AI Deciders reason about AI benefits and risks, and how their knowledge about AI influences their decisions on what and where to innovate. We interviewed AI Deciders across diverse organizations. We found no ideation. AI Deciders just consider one concept at a time. Design and HCI played no role in deciding what to build. Many AI Deciders overestimate AI’s benefits while underestimating risks. Based on these findings, we identified opportunities for design and HCI to support impactful and responsible AI innovation. This should reduce AI project failure. Shixian Xie, Sijia Xiao, Cindy Peng, Ganesh Mani, John Zimmerman, Motahhare Eslami |
CHI | 1 |
| 2025 | Exploring What People Need to Know to be AI Literate: Tailoring for a Diversity of AI Roles and Responsibilities
Shixian Xie, John Zimmerman, Motahhare Eslami |
CHI | 1 |
| 2023 | "I Would Like to Design": Black Girls Analyzing and Ideating Fair and Accountable AIabstractArtificial intelligence (AI) literacy is especially important for those who may not be well-represented in technology design. We worked with ten Black girls in fifth and sixth grade from a predominantly Black school to understand their perceptions around fair and accountable AI and how they can have an empowered role in the creation of AI. Thematic analysis of discussions and activity artifacts from a summer camp and after-school session revealed a number of findings around how Black girls: perceive AI, primarily consider fairness as niceness and equality (but may need support considering other notions, such as equity), consider accountability, and envision a just future. We also discuss how the learners can be positioned as decision-making designers in creating AI technology, as well as how AI literacy learning experiences can be empowering. Jaemarie Solyst, Shixian Xie, Ellia Yang, Angela Stewart, Motahhare Eslami, Jessica Hammer, Amy Ogan |
CHI | 2 |
| 2023 | Booklet-Based Design Fiction to Support AI LiteracyabstractChildren interact frequently with artificial intelligence (AI) in their everyday lives. Their understanding of AI technology, however, is often very limited. AI literacy is vital to make informed and empowered decisions about engaging with technology. The ability to imagine future technology designs and applications is a core competency of AI literacy, but few studies have used booklets, a well-studied design fiction tool, as a technique with children in imagining future AI. We explored how a booklet-based design fiction method can support AI literacy with fifth graders (N = 7) from marginalized backgrounds. We describe two benefits of using booklets to create AI design fiction with children in our educational workshop: (1) grounding abstract AI concepts, (2) prolong post session dialogues. This work contributes a new type of scaffolded activity that supports youth learners in AI education. Shixian Xie, Jaemarie Solyst, Amy Ogan, Jessica Hammer |
SIGCSE (2) | 1 |
| 2023 | The Potential of Diverse Youth as Stakeholders in Identifying and Mitigating Algorithmic Bias for a Future of Fairer AIabstractYouth regularly use technology driven by artificial intelligence (AI). However, it is increasingly well-known that AI can cause harm on small and large scales, especially for those underrepresented in tech fields. Recently, users have played active roles in surfacing and mitigating harm from algorithmic bias. Despite being frequent users of AI, youth have been under-explored as potential contributors and stakeholders to the future of AI. We consider three notions that may be at the root of youth facing barriers to playing an active role in responsible AI, which are youth (1) cannot understand the technical aspects of AI, (2) cannot understand the ethical issues around AI, and (3) need protection from serious topics related to bias and injustice. In this study, we worked with youth (N = 30) in first through twelfth grade and parents (N = 6) to explore how youth can be part of identifying algorithmic bias and designing future systems to address problematic technology behavior. We found that youth are capable of identifying and articulating algorithmic bias, often in great detail. Participants suggested different ways users could give feedback for AI that reflects their values of diversity and inclusion. Youth who may have less experience with computing or exposure to societal structures can be supported by peers or adults with more of this knowledge, leading to critical conversations about fairer AI. This work illustrates youths' insights, suggesting that they should be integrated in building a future of responsible AI. Jaemarie Solyst, Ellia Yang, Shixian Xie, Amy Ogan, Jessica Hammer, Motahhare Eslami |
Proc. ACM Hum. Comput. Interact. | 3 |