UI/UX design, artificial intelligence, and smart XR interfaces in Pradipta Biswas latest book
UI/UX design and artificial intelligence are in a very different place compared to just a few years ago. What used to stay locked in labs or technical papers is now turning into real products, space mission cockpits, interfaces for extended reality glasses, and even tools for child accessibility. Pradipta Biswas new book lands exactly at this intersection: it aims to demystify the process of designing intelligent interfaces, bringing the latest AI and usability advances to a practical level, focused on people who need to design and test systems with real human users.
The book, published by Taylor & Francis under the title Intelligent User Interface: Usable Artificial Intelligence and Artificial Intelligence for Usability, connects three layers that are usually treated separately: AI and machine learning models, the UI/UX process, and applications in XR, human‑robot interaction, and cockpits. Instead of staying theoretical, the author showcases very concrete applications such as eye tracking systems, gesture-controlled displays, virtual reality simulations for spacecraft, and interfaces that predict the trajectories of vehicles and people in complex environments.
The book is not focused on teaching neural network math, but on showing how to use these technologies to build intelligent interfaces that are understandable and usable. To do that, Biswas blends concepts from human factors, computer vision, accessibility standards, and international guidelines with case studies, diagrams, lists of free software, and project ideas that students, designers, and engineers can explore.
Who is Pradipta Biswas and why this book matters
Pradipta Biswas has a strong track record at the intersection of human‑computer interaction, accessibility, and advanced interfaces. He completed his PhD in Computer Science at Cambridge, studying visual and auditory perception, fast pointing movements, and problem‑solving strategies in digital interaction contexts. During that period, he developed new algorithms for eye gaze-based technologies and filed patents, including an interactive Head‑Up Display controlled by gaze and gestures.
After Cambridge, Biswas returned to India and is now an Associate Professor in the Department of Design and Manufacturing at the Indian Institute of Science (IISc), as well as an associate faculty member at the Robert Bosch Centre for Cyber Physical Systems. He has also played key roles in international bodies: he was elected vice‑chairman of ITU Study Group 9, co‑chair of the Intersector Rapporteur Group on Audiovisual Media Accessibility (IRG AVA), and contributed to the Focus Group on Smart TV, all under the International Telecommunication Union (ITU). In short, he is not an outsider to the discussion: he helped define standards and guidelines that are used globally in accessible media and connected devices.
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In practice, Biswas continues to develop applied research. He has worked with the Indian Air Force on eye‑tracking technologies, led a virtual reality cockpit project for India first crewed spaceflight, and was one of five researchers in the country selected to study human‑machine interaction in the context of the International Space Station during the Axiom 4 mission. On top of that, he created a pioneering toy hackathon focused on adapting toys so that children with severe disabilities can communicate using interfaces controlled by eye movement.
From lab to cockpit: what the book covers in terms of technology
The book takes a broad but very concrete tour through different technology blocks that currently power intelligent interfaces. Some of the main topics include:
- Human factors applied to interfaces: cognitive load, perception, reaction time, visual and auditory comfort.
- Modern computer vision, including vision transformers and techniques for object and trajectory detection in dynamic environments.
- XR systems (virtual, augmented, and mixed reality), focusing on hardware such as headsets, smart glasses, and head‑up displays.
- Large language models (LLMs) used as an interface layer in human‑robot interactions and assistants in immersive environments.
- Usability evaluation techniques adapted for complex contexts such as cockpits, robotics, and space simulations.
One of the book strengths is how it frames AI and usability as a two‑way street. On one side, it shows how AI can make interfaces more flexible, adaptive, and accessible. On the other, it explains how usability principles help make AI systems themselves more understandable, predictable, and trustworthy for people, especially when they are operating vehicles, safety‑critical systems, or XR solutions for long periods.
Trajectory prediction and safety in intelligent systems
One of the book central topics is trajectory prediction. It may sound technical, but it has a direct impact on interface design for mobility, autonomous vehicles, and XR. The idea is to anticipate, based on historical data and context, where an agent will move over time. This agent can be a car, a drone, an industrial robot, or even a pedestrian on a busy street.
In autonomous driving scenarios, this prediction is essential to avoid collisions and plan safe routes. The interface has to present critical information to humans in a clear and timely way: likely trajectories, surrounding risks, and indicators of future maneuvers. The better the prediction, the more the interface can show only what matters, without overwhelming the person making real‑time decisions.
In XR environments, the logic is similar, but applied to immersive experiences. If the system can predict where a person will look or walk, it can move overlays, text, and icons smoothly, keeping everything aligned with the real scene. The book discusses how this trajectory prediction improves interaction fluidity, reduces VR motion sickness, and prevents key elements from disappearing from the field of view at the wrong moment.
In both cases, the UI/UX layer is not a visual afterthought: it is a core part of safety and comfort. The author highlights that overconfidence in predictive models without a well‑designed interface can backfire, increasing risk and confusing operators. That is why the book argues that the interface should discreetly display how certain or uncertain a prediction is, allow for quick corrections, and always make it clear that the human can take over control.
XR, virtual reality, and augmented reality in interface design
Another important section of the book details how XR is used in different contexts. Instead of treating VR and AR just as entertainment experiences, the book focuses on more critical and technical applications such as:
- Virtual reality cockpit simulations for training astronauts and pilots, including the project tied to the Indian space mission.
- Head‑up display interfaces that project data into the field of view, controlled via gaze and gestures.
- Human‑robot interactions in lab environments using VR and AR to visualize robots internal states and planned routes.
- XR environments with drones, where users monitor and control devices remotely with graphical layers overlaid on live video.
In these scenarios, interface design has to consider much more than aesthetics. The book discusses specific XR layout patterns, placement of elements in 3D space, rules for information density within the visual field, and coordinated use of spatial audio and haptic feedback. All of this is tied to user testing, measuring everything from task performance to physical comfort, fatigue, and subjective sense of control.
Tools, standards, and how to set up an intelligent interaction lab
The book does not stay at the conceptual level. It also offers a practical view of equipment and standards for those who want to build a lab or experimental space for intelligent interaction. Key points include:
- Types of sensors and devices for eye tracking and gesture capture.
- Basic components for labs with robots, drones, and XR systems.
- Recent standards and guidelines related to UI/UX, audiovisual accessibility, and connected devices, including ITU work.
- A list of free or open‑access software for computer vision experiments, simulation, usability evaluation, and prototyping.
Each chapter closes with graphical illustrations and a quick facts section that works as a fast review of the key concepts. The author also suggests new project ideas especially aimed at students and early‑career researchers, pointing to opportunities to explore intelligent interfaces in areas such as education, mobility, healthcare, and accessibility.
LLMs, conversational interfaces, and human‑robot interaction
A more recent part of the intelligent interfaces field appears in the book through the use of large language models in physical‑digital interaction contexts. It is not just about text chat: the discussion covers voice interfaces, natural language control of robots, and the combination of LLMs with sensor, vision, and location data.
In these scenarios, the language model becomes a kind of conversational brain that has to respect devices physical limitations. The book discusses how to align natural commands with safe, predictable actions, define clear boundaries for what the system can and cannot do, and avoid overly creative responses turning into dangerous behavior in robotics, mobility, or cockpits. All of this relies heavily on careful interaction design: clear feedback, explicit confirmation of sensitive actions, and visual presentation of the system states and intentions.
Who the book is for
The intended audience is very well defined. The book is aimed at:
- Engineering and design students and faculty who want to understand how AI and usability meet in practice.
- Interface and user experience designers interested in applying modern AI concepts without getting lost in mathematical formalism.
- Product managers and technical leaders who need to make decisions about AI use in new products, especially in XR, robotics, and embedded systems.
The goal is to explain the latest technologies in an accessible way without sacrificing conceptual depth. Instead of requiring heavy theoretical reading, the book connects each technology to a use case, a design guideline, or a project that can be reproduced or adapted.
Impact on the future of UI/UX and intelligent interfaces
By bringing together human factors, modern AI, XR, and international standards in a single package, Pradipta Biswas book helps organize a field that many people still see as a set of separate islands. The core message is straightforward: we can no longer treat UI/UX, AI, and interaction hardware as isolated tracks. The next generation of meaningful products will likely emerge from the intersection of these areas.
For people working with technology and user experience, the content offers a solid foundation for thinking about interfaces that go beyond flat screens. Whether in a virtual cockpit, augmented reality glasses, a collaborative robot, or an accessible interface for children with motor impairments, the book shows how to use artificial intelligence in service of usability, not the other way around. And it keeps one foot firmly in practice: real‑world cases, available tools, and concrete paths to experiment with, measure, and improve intelligent interfaces in both physical and digital environments.
