User experience, UI/UX design, AI, and intelligent interfaces: what Pradipta Biswas’s new book reveals about the future of human-machine interaction
When we talk about UI/UX design today, we are no longer just talking about pretty screens, color palettes, and well-placed buttons. The game has changed. The new generation of interfaces involves Artificial Intelligence, Machine Learning models, immersive AR/VR/XR systems, interaction with robots, high-complexity cockpits, and even simulated space missions. And this is exactly the universe that the book Intelligent User Interface: Usable Artificial Intelligence and Artificial Intelligence for Usability, by Pradipta Biswas, sets out to unpack in an accessible way.
Published by Taylor & Francis, the book was born with a clear mission: to popularize the design process of User Interface (UI) and User Experience (UX) in a world where AI is no longer just a lab novelty, but part of everyday, real products. Instead of focusing only on the mathematical theory behind the models, the author shows how these technologies connect to practical decisions in design, usability, accessibility, and system evaluation.
The book’s main strength is combining two ends that usually walk separately: on one side, the latest advances in AI and machine learning; on the other, the concrete practice of designing intelligent interfaces for real people, operating in critical contexts like aviation, robotics, XR, and space missions. All of this comes with examples, case studies, design patterns, and tool lists that can be downloaded and used in labs or in academic and industrial projects.
The book’s focus: intelligent interfaces, usability, and AI in practice
Pradipta Biswas’s book lays out a broad overview of intelligent interfaces, tying together theory and application. It covers topics such as:
- Human factors and cognitive limits in complex systems
- Computer vision applied to human-machine interaction
- AR/VR/XR systems and their UI/UX challenges
- Large language models (LLMs) in conversational and robot interfaces
- Usability evaluation in high-criticality environments
- International standards and norms applied to UI/UX
Instead of treating AI as one generic block, the author breaks down recent models such as vision transformers and LLM-based interfaces for interactions with robots and complex systems. He shows how these models can be integrated into real interfaces, for example, to interpret natural language commands, predict vehicle or pedestrian trajectories, and adapt cockpit layouts based on context.
A central point is the idea of AI in service of usability. Rather than using algorithms only to automate tasks, the book discusses how AI can enhance user experience by:
- Reducing information overload on critical screens
- Prioritizing alerts based on real risk and context
- Adapting the interface to the operator’s experience level
- Providing intelligent, real-time support during complex tasks
For anyone working in or studying product design, engineering, computer science, or user experience, the content works as an up-to-date map of what’s possible with intelligent interfaces today, without requiring the reader to dive into every formula and statistical detail of the models.
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Trajectory, XR, and cockpits: where theory meets the real world
One of the most interesting parts of the book is its set of case studies on systems that depend on prediction, context, and fast responses. Among the examples explored are:
- Interfaces for XR systems, combining virtual, augmented, and mixed reality
- Human-robot interaction in industrial and research environments
- Cockpit design with intelligent support for pilots and operators
- Trajectory prediction systems for vehicles and pedestrians
Trajectory prediction stands out as an essential piece in scenarios like autonomous vehicles, drones, and vehicles in congested routes. Simply put, the goal is to predict where an agent will be in the future, considering its current position, speed, environment, and the behavior of nearby agents. This is critical to enable:
- Safe maneuvers in heavy traffic
- Collision avoidance
- More efficient routes
- Early signaling and alerts on the interface
In XR systems, the challenge is designing interfaces that coexist with the physical world. The book explains how extended reality platforms depend on advanced hardware like headsets and smart glasses, but also on very careful design of where and how information is displayed. Poorly planned data overlays can block the user’s view, cause motion sickness, visual fatigue, or even lead to errors in precision tasks.
In these contexts, AI comes into play to:
- Understand the surrounding environment through computer vision
- Detect surfaces, depth, and relevant objects
- Position graphical elements so they do not obstruct the view
- Adapt information density based on the user’s focus of attention
Labs, standards, and guidelines for intelligent interaction
Beyond models and use cases, the book also dives into a very practical side: what it takes to set up an intelligent interaction design lab that works with robots, drones, and XR systems. This includes everything from:
- Motion-capture and eye-tracking equipment
- Virtual and augmented reality devices
- Sensors and actuators for robots and drones
- Recommended open-source software for prototyping and testing
One extra perk is that the author lists tools that can be downloaded for free to work with the topics covered, making life easier for anyone setting up a lab in universities or research centers with limited budgets.
The book also addresses recent standards, norms, and guidelines related to:
- UI/UX and layout for critical systems
- Accessibility in audiovisual media and connected devices
- Best design practices for smart TVs and related platforms
This focus on standards is no coincidence. Pradipta Biswas served as vice-chairman of ITU Study Group 9 and co-chair of IRG AVA (a group focused on audiovisual accessibility), as well as joining the Focus Group on Smart TV at the International Telecommunication Union (ITU). This background shows up in the book as a bridge between the technical requirements of international bodies and design decisions that affect millions of users.
From the Cambridge lab to space missions
The vision presented in the book did not appear out of thin air. It is closely tied to Pradipta Biswas’s journey as a researcher. During his PhD in Computer Science at Cambridge, he studied in depth:
- Visual and auditory perception in human-machine interaction
- Fast pointing movements and response times
- Problem-solving strategies in complex interfaces
At that stage, he also developed new algorithms for eye-tracking technology, exploring gaze and gestures as natural forms of control. One of these developments resulted in an interactive Head-Up Display controlled by gaze and gestures, patented and designed for scenarios where taking your hands off the main controls can be dangerous or impossible.
After returning to India, Biswas began applying these concepts in high-impact projects. Highlights include:
- Collaboration with the Indian Air Force on eye-tracking-based systems
- Leading the design of a virtual reality cockpit for India’s first manned space mission
- Taking part, as one of only five researchers selected in the country, in a study on human-machine interaction on the International Space Station during the Axiom 4 mission
- Heading a pioneering toy hackathon that adapted toys so that children with severe disabilities could communicate through eye-controlled interfaces
This combination of academic research, international standards work, and real-world projects at the cutting edge of technology gives the book extra weight. It is not an isolated theoretical discussion, but a summary of lessons learned in contexts where human error, poor design, or confusing interfaces can have serious consequences.
From computer vision to LLMs: AI’s role in next-gen interfaces
A significant portion of the book is dedicated to new AI systems and how they show up in the visible UI/UX layer. Some of the topics covered include:
- Vision transformers and their use in scene and object recognition
- LLM-based interfaces for robots and complex systems
- Virtual reality simulators for training space missions
- Usability evaluation techniques tailored to immersive and automated environments
Vision transformers are used to give systems a more human-like view of the world, identifying visual patterns with high accuracy. This enables, for example, a robot to better understand its surroundings, or an AR/VR system to place virtual elements in the right spot without breaking depth perception.
LLMs, in turn, show up as bridges between human language and machine commands. Instead of requiring rigid syntax or complex clicking flows, interfaces can let users describe what they want to do in natural language. The system then interprets the intent, executes actions, and returns feedback in a conversational way. The book explores how this approach can be used in:
- Control interfaces for collaborative robots
- Support systems in cockpits and command centers
- Virtual assistants in training or simulation environments
A recurring highlight is the concern with usability evaluation. It is not enough to bolt on AI and assume everything is better. The author discusses methods to measure whether the interface actually helps, reduces errors, lowers cognitive load, and remains understandable to users with different experience levels.
Target audience: from engineering students to designers and PMs
Even though it covers advanced topics, the book targets readers who need practical depth without drowning in theory. The main audience includes:
- Students of engineering and design
- Professors and researchers in human-computer interaction
- UI/UX designers who want to better understand AI’s role
- Product managers working on AI-powered and immersive products
To make the bridge between theory and practice easier, each chapter includes:
- Graphic illustrations to explain visual concepts and architectures
- Quick fact lists for review and memorization
- Project ideas for students and early-career researchers
- References to free software that let readers experiment with the concepts
This format helps both newcomers and seasoned professionals who need to update their view of AI in interfaces. Instead of offering only scattered concepts, the book suggests concrete paths for experimentation, research, and prototype development.
Why this kind of book matters for the future of UI/UX
The book arrives at a time when UI/UX, AI, and immersive systems are coming together in an irreversible way. Autonomous cars, wearables, collaborative robots, smart industrial spaces, space missions, and everyday digital products all share one common point: they depend on interfaces capable of turning complexity into clear, safe actions.
Books like Pradipta Biswas’s help make sense of this landscape, showing that:
- AI does not replace design: it extends what design can do
- Human factors stay at the center, even in highly automated systems
- Standards and norms have a direct impact on the quality of the interfaces we use
- Applied research in extreme contexts (like space and aviation) produces insights that are useful for everyday products
At the end of the day, the book shows that the future of interfaces is not just about more technology, but about technology that fits the reality of the people using it. By connecting UI/UX design, Artificial Intelligence, XR systems, robot interaction, and space simulations, Pradipta Biswas’s work offers a solid overview of how the next generation of intelligent interfaces is being conceived, tested, and deployed in the real world.
