Artificial Intelligence (AI) brings advancements to support pathologists in navigating high-resolution tumor images to search for pathology patterns of interest. However, existing AI-assisted tools have not realized this promised potential due to a lack of insight into pathology and HCI considerations for pathologists’ navigation workflows in practice. We first conducted a formative study with six medical professionals in pathology to capture their navigation strategies. By incorporating our observations along with the pathologists’ domain knowledge, we designed NaviPath — a human-AI collaborative navigation system. An evaluation study with 15 medical professionals in pathology indicated that: (i) compared to the manual navigation, participants saw more than twice the number of pathological patterns in unit time with NaviPath, and (ii) participants achieved higher precision and recall against the AI and the manual navigation on average. Further qualitative analysis revealed that navigation was more consistent with NaviPath, which can improve the overall examination quality.

With estimates of at least 3.4 million Americans aged 40 years and older facing challenges due to vision impairment, advancements in haptic technology have been explored as an effective alternative approach to provide support in aspects such as accessible navigation. A scoping review was conducted to investigate recent literature on haptic technology used to guide blind or low-vision users to a destination, focusing on 28 articles that were identified using the PRISMA method. Results revealed a focus on the methods of haptic input, specifically the benefits and gaps in hands-free and hand-held devices. Several studies utilized the advantages of employing a multimodal feedback approach with audio to better convey navigation information, while explorations of the performance of different types of haptic feedback were also discussed. Overall, this study provides insights into recent advancements in haptic design, which can assist researchers in improving developments toward inclusive navigation technology for blind or low-vision individuals.

Mobility disabilities are among the most common disability types in the U.S., where the need to design safe powered mobility devices is increasingly important for user safety. For power wheelchair users, AI-enabled solutions have been introduced to avoid collisions. However, as control shifts from the user to automation, systems need to communicate intent clearly and maintain user trust. Auditory verbal cues can support decision-making: explanations may emphasize action-focused maneuvers or why-focused rationales. Tactile displays can also support communication through vibrations presented to the back or wrist. However, because safety-critical messages based on AI-inferred intent have not been systematically investigated and because power wheelchair users experience a different embodied interaction, there remains an opportunity to understand these factors. This pilot study explored the effects of communication strategy (action-focused, why-focused) and vibrotactile feedback location (seatback, wrist) on wheelchair performance and user perceptions. Six able-bodied participants completed wheelchair driving sessions while receiving obstacle alerts. Results indicated that seatback vibrations were associated with higher satisfaction ratings than wrist vibrations. No significant main effects were found for reaction time, decision-making accuracy, or usefulness ratings. These data can inform future studies designing intelligent wheelchair interfaces.