UI/UX design and artificial intelligence are intersecting faster than ever, but most professionals still get this knowledge in a fragmented way, through scattered articles, tweets, and threads. What is missing is a resource that connects the latest in AI models and machine learning with the real process of designing interfaces, prototypes, usability tests, and digital products that actually make it to market.

This is exactly the gap that the book Intelligent User Interface: Usable Artificial Intelligence and Artificial Intelligence for Usability, published by Taylor & Francis and written by Pradipta Biswas, sets out to fill. The book aims to demystify the UI/UX design process in the AI era, explaining the latest technologies in a clear way, without forcing readers to dive into formulas or heavy theory to apply the concepts in their daily work.

The focus of the book is not to treat AI as a separate topic, but to show how it is already part of the user experience, whether in recommendation systems, adaptive interfaces, or immersive environments like virtual, augmented, and mixed reality. It is designed for people who design, develop, test, or manage digital products and want to understand, in a practical way, how intelligent interfaces are being built today.

Who Pradipta Biswas is and why it matters

Pradipta Biswas is not just a theorist writing about human-computer interaction. He is a researcher, professor, and has a solid track record connecting lab work, industry, and high-level projects.

He is currently an Associate Professor in the Department of Design and Manufacturing at the Indian Institute of Science (IISc), one of India’s most respected research institutions, and also serves as an associate professor at the Robert Bosch Centre for Cyber Physical Systems. In other words, he works directly with cyber-physical systems, advanced interfaces, robotics, and emerging technologies that blend the physical and digital worlds.

On the international front, Biswas has played a leading role at the International Telecommunication Union (ITU). He was elected vice-chair of the ITU Study Group 9, as well as serving as co-chair of the IRG AVA (Intersector Rapporteur Group on Audiovisual Media Accessibility) and participating in the Focus Group on Smart TV. These groups discuss global standards for accessibility, smart TV, and digital communication, topics that are directly linked to interface design, user experience, and inclusion.

Before that, during his PhD in Computer Science at Cambridge, Biswas dove deep into visual and auditory perception, rapid movement, and problem-solving strategies in the context of human-machine interaction. From that work came algorithms and technologies applied in areas like eye tracking and gesture control. One of the outcomes was an interactive Head Up Display controlled by gaze and gestures, a technology that lets users interact with the system without taking their hands off what they are doing, which is highly relevant in contexts like aviation and driving.

After returning to India, he expanded this work with practical projects. Highlights include:

• Collaborations with the Indian Air Force, advancing the use of eye tracking in high-demand scenarios.
• Participation in a virtual reality cockpit project for India’s first crewed space mission, bringing immersive simulation to training and interaction studies.
• Selection as one of five Indian researchers to conduct human-machine interaction studies on the International Space Station during the Axiom 4 mission.
• Leading a toy hackathon focused on children with severe disabilities, exploring gaze-controlled interfaces for assistive communication.

This blend of experiences is reflected in the book: it is not detached from reality, but a compilation of what the author has seen work in projects with robots, drones, XR, cockpits, and safety-critical systems.

Main topics covered in the book

The book Intelligent User Interface offers a broad map of the current state of UI/UX when combined with AI, always with a focus on practical application. Key topics include:

• AI and machine learning models applied to interfaces
• Interaction in XR systems (extended reality)
• Human-robot interaction
• Cockpit design and safety-critical systems
• Trajectory prediction for vehicles and pedestrians
• UI/UX standards, norms, and guidelines
• Setting up a lab for intelligent interaction research
• Usability, accessibility, and interface evaluation

Below are some of the highlights that help clarify the real scope of the book.

AI, computer vision, and intelligent interfaces

A significant part of the book is dedicated to explaining, in accessible language, how modern AI models applied to interfaces work. This includes:

• Computer vision to interpret the environment or the user (gestures, gaze, position, context).
• Vision transformers, an evolution over classic image recognition models, which allow for more precise understanding of scenes and context.
• Generative and language models being used as an interaction layer, rather than just isolated text engines.

The book also discusses LLMs (Large Language Models) applied as communication interfaces for robots and complex systems. Instead of rigid controls or structured commands, users interact in natural language, and the system bridges that conversation to concrete actions in hardware, simulations, or virtual environments.

XR, AR, VR, and immersive simulations

Another strong pillar of the book is XR systems (Extended Reality), which include:

• Virtual Reality (VR)
• Augmented Reality (AR)
• Mixed Reality

Biswas shows how layout logic, navigation flow, and feedback change when the interface is no longer on a flat screen and instead occupies the space around the user. He discusses examples such as:

• Interfaces in headsets and smart glasses.
• VR cockpit simulations for astronaut and pilot training.
• Virtual environments where user behavior is monitored in real time to adjust the experience.

In this context, artificial intelligence is the engine that makes the interface react intelligently: predicting actions, adapting menus, prioritizing alerts, and even avoiding cognitive overload at critical moments.

Trajectory prediction and safety in autonomous systems

The book dedicates a specific section to trajectory prediction. In simple terms, this is the ability to predict where an agent will be in the future, whether that agent is a car, a drone, or a pedestrian. This capability is crucial for:

• Autonomous vehicles, which need to anticipate the movements of other cars and people to decide on safe maneuvers.
• Drones and robots that share space with humans or other equipment.
• Navigation systems in complex environments like airports, factories, and smart cities.

Trajectory prediction is directly connected to UI/UX when we think about how information is presented to users. Visual alerts, audio warnings, dashboard highlights, HUD elements, and XR visualizations are designed based on what the system predicts will happen, not just what has already occurred.

Standards, guidelines, and lab setup

Beyond the conceptual and applied parts, the book brings a very practical component: it covers the latest standards and guidelines that affect UI/UX, human-robot interaction, XR, and accessibility. This includes standards for:

• Layout design for different device types and contexts.
• Accessibility in audiovisual media, aligned with ITU groups focused on accessibility.
• Interfaces for smart TVs and connected devices.

Another differentiator is the section where Biswas details the equipment and infrastructure needed to set up a lab for intelligent interaction. He covers items such as:

• Eye tracking and gesture capture systems.
• VR, AR, and MR headsets.
• Drones, robots, and simulation platforms.
• Software for analysis, prototyping, and usability evaluation.

For people in universities, research centers, or even companies that want to invest in advanced UX labs, this part works as a very straightforward starter guide.

Human factors, usability, and evaluation

Even with such a strong focus on AI and advanced technologies, the book does not neglect the classic foundation of user-centered design. It addresses:

• Human factors: cognitive limitations, perception, reaction time, mental workload.
• Usability evaluation techniques, adapted for contexts with AI in the loop.
• Objective and subjective measurement of experience, including metrics based on sensor data.

Each chapter offers not only explanations but also graphic illustrations and a list of quick facts for rapid review. This makes it easier to recall concepts without rereading the entire chapter, which is very handy for anyone in the middle of a project who needs to quickly check a specific point.

Another interesting element is that the book offers project ideas that can be explored by students and early-career researchers. These are proposals related to intelligent interfaces, combining AI with human-machine interaction and XR applications, helping readers turn theory into concrete prototypes and experiments.

Tools we use daily

Translation

Text Inspection & Clipping

Social Media

Search & Research

Recruitment

Programming

Productivity & Organization

Operations

Marketing & Sales

Finance & Investment

Education

Design & Media

Data & Analytics

Content & Writing

Automation

LLMs, conversational interaction, and space simulations

With the rise of Large Language Models (LLMs), the book also explores how these models fit into the UI/UX landscape:

• Conversational interfaces for robots and physical systems.
• Agents that mediate interaction between users and complex environments, such as virtual reality simulations.
• Applications in space simulators, where AI helps coordinate tasks, explain systems, and support training.

Biswas discusses both the potential and the current limitations of this technology, emphasizing the importance of not treating LLMs as a magic solution, but as one more component in systems that need to be safe, predictable, and usable.

Free tools and supporting material

One very practical feature of the book is a list of free software tools related to the topics covered. It includes tools for:

• Interface and interaction prototyping.
• XR system simulation and testing.
• Applying computer vision and machine learning models.
• Usability analysis and evaluation.

This shortens the gap between theory and practice, allowing readers to explore the concepts without relying on expensive tools or very specific environments.

Who the book is for

The target audience of the book is clear and reflects its focus on practical application backed by up-to-date technical foundations. It was written for:

• Engineering and design students interested in UI/UX, AI, and human-computer interaction.
• Professors and researchers looking for updated supporting material for courses and projects.
• Interface designers who want a better understanding of how to integrate AI into their workflow.
• Product managers and technology professionals who need to make informed decisions about intelligent features in digital products.

The goal is to help these people understand the latest advances in AI and machine learning as they relate to interfaces, without requiring them to dive into advanced mathematics. The idea is to offer enough depth for practical use, without getting stuck in excessive formalism.

Ultimately, Pradipta Biswas’s book works as a map of the current landscape of UI/UX in the age of artificial intelligence, with one foot firmly in practice and the other firmly in research. For anyone living the day-to-day reality of digital products, complex interactions, and increasingly intelligent systems, it is a resource that helps connect technology, design, and human experience into a single line of thought.