google·Feb 5, 2026·3 min readCurated summary

How AI tools can redefine universal design to increase accessibility

Google Research proposes Natively Adaptive Interfaces (NAI), a framework that uses multimodal and agentic AI to make interfaces adapt to individual users rather than forcing everyone into a fixed design. Developed through co-design with disability communities, NAI aims to reduce the accessibility gap by embedding assistive capabilities directly into products. Early prototypes suggest that personalized, context-aware interfaces can improve experiences for disabled users while also benefiting the broader population. ## Community-led co-design - Google follows the principle “Nothing About Us, Without Us,” involving people with disabilities as co-designers from the beginning. - Partnerships include RIT/NTID, The Arc of the United States, RNID, and Team Gleason. - These collaborations focus on real-world barriers and recognize the expertise of disability communities. - The approach also aims to create employment and economic opportunities for people who help shape the technology. ## Moving from reactive accessibility to adaptive interfaces - Google identifies an “accessibility gap” between the release of new features and the development of compatible assistive tools. - NAI addresses this by making accessibility native to the interface instead of adding it afterward. - Static navigation is replaced with dynamic, agent-driven modules that can interpret context and adjust the experience. ## Multi-system agents - An Orchestrator maintains shared context and delegates tasks to specialized sub-agents. - A Summarization Agent breaks down complex documents and assigns subtasks to expert agents. - A Settings Agent dynamically adjusts interface elements such as text size. - This structure lets users accomplish tasks without navigating complicated menus or searching for the right control. ## Multimodal interaction - Gemini-based prototypes combine voice, vision, and text rather than limiting accessibility to text-to-speech. - Live video can be converted into interactive audio descriptions. - Users can ask follow-up questions about specific visual details as events unfold. - Conversational interaction provides situational awareness and may reduce cognitive load. ## Proven prototypes - **StreetReaderAI** - Supports blind and low-vision users navigating physical spaces. - Combines an AI Describer that analyzes visual and geographic information with an AI Chat system for questions. - Maintains context so users can ask about previously encountered locations, such as the position of a bus stop. - **Multimodal Agent Video Player (MAVP)** - Makes audio description interactive rather than static. - Users can change the level of detail or ask questions during playback. - Uses an offline “dense index” of visual descriptions and retrieval-augmented generation (RAG) for fast responses. - **Grammar Laboratory** - Developed by RIT/NTID with Google.org support for American Sign Language and English learners. - Provides grammar instruction through ASL videos, English captions, spoken narration, and written transcripts. - Uses adaptive AI to customize lessons according to each student’s language preferences and interactions. ## The curb-cut effect - Accessibility features designed for people with significant constraints can benefit many other users. - Voice interfaces created for blind users may help sighted people who are multitasking. - AI synthesis and learning tools designed for people with learning disabilities can also support users who want information presented more clearly or flexibly. - NAI therefore treats accessibility as a source of better universal design, not as a specialized add-on. NAI’s central recommendation is to build accessibility into interfaces from the start, using multimodal AI, persistent context, and community-led design. The most effective systems will adapt to users while remaining accountable to the people whose needs they are intended to serve.

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Universal DesignAI AgentsGenerative AIAccessibility+4

toss·Jan 15, 2026Original article

Creating Toss's new face (opens in new tab)

Toss redesigned its brand persona graphics to transition from simple, child-like icons to more professional and inclusive human figures that better represent the brand's identity. This update aims to project a more trustworthy and intelligent image while ensuring the visual language is prepared for a global, multi-cultural audience. By balancing iconic simplicity with diverse representation, the new design system maintains brand consistency across various screen sizes and service contexts. ### Refining Proportions for Professionalism * The team adjusted the vertical facial ratio to move away from a "child-like" impression, finding a balance that suggests maturity and intelligence without losing the icon's friendly nature. * The placement of the eyes, nose, and mouth was meticulously tuned to maintain an iconic look while increasing the perceived level of trust. * Structural improvements were made to the body, specifically refining the curves where the neck and shoulders meet to eliminate the unnatural "blocky" feel of previous versions. * A short turtleneck was selected as the default attire to provide a clean, professional, and sophisticated look that works across different UI environments. ### Achieving Gender-Neutral Hairstyles * The design team aimed for "neutrality" in hair design to prevent the characters from being categorized into specific gender roles. * Several iterations were tested, including high-density detailed styles (which were too complex) and simple line-separated styles (which lacked visual density when scaled up). * The final selection focuses on a clean silhouette that follows the head line while adding enough volume to ensure the graphic feels complete and high-quality at any size. ### Implementing Universal Skin Tones and Diversity * To support Toss's expansion into global markets, the team moved away from a single skin tone that could be interpreted as a specific race. * While a "neutral yellow" (similar to standard emojis) was considered, it was ultimately rejected because it felt inconsistent and jarring when displayed in larger formats within the app. * Instead of a single "neutral" color, the team defined a palette of five distinct skin tones based on universal emoji standards. * New guidelines were established to mix these different skin tones in scenes with multiple characters, fostering a sense of inclusivity and representation that reflects a diverse user base. The evolution of the Toss persona illustrates that as a service grows, its visual language must move beyond simple aesthetics to address broader values like trust and inclusivity. Moving forward, the design system will continue to expand to ensure that no user feels excluded by age, gender, or race.

Universal DesignDesign SystemsUser InterfaceGraphic Design+3