Alison Smith
Papers
1
Total Citations
19
H-Index
1
About
Dr. Alison Smith is a pioneering researcher in Explainable AI (XAI), with a focus on making artificial intelligence systems more transparent and accessible to diverse users. Her key research areas include human-AI interaction, multimodal explanations, and the design of intuitive interfaces for non-expert stakeholders. Dr. Smith’s most notable contribution is her concept of “Graspable AI,” which introduces physical forms as a novel explanation modality for XAI. This work challenges traditional verbal and visual explanations by proposing tangible, interactive representations that allow users to physically “grasp” AI decision-making processes. Her 2022 paper on this topic has already garnered 19 citations, signaling its growing influence in the field. By addressing how different users—from data scientists to laypeople—prefer to understand AI outcomes, Dr. Smith is reshaping the design of explainability tools. Her research bridges cognitive science, design, and computer science, offering practical pathways for building trust in AI systems. As the demand for ethical and user-centered AI grows, Dr. Smith’s work stands out for its creativity and real-world applicability.
Research Focus
Key Achievements
Top Papers
- 1Graspable AI: Physical Forms as Explanation Modality for Explainable AI19 citations · 2022