Reveal the human experience of AI
Human-AI interaction

Reveal the human experience of AI

Eye tracking adds objective attention data to human-centered AI research, helping teams study how people visually engage with AI recommendations, explanations, interfaces, and decision-support systems. 

See what happens before the decision 

Simulations provide a controlled way to study how people respond to AI, automation, and decision-support systems.

Eye tracking adds another layer, revealing what people look at before they act, which information attracts attention, what gets revisited, and what may go unnoticed.

See what happens before the decision 

Benefits

Benefits

Design AI around how people think and act

Use gaze data to uncover how people engage with AI, giving you evidence to refine experiences and make interactions clearer, more useful, and easier to understand.

  • Make recommendations more relevant

    Discover what people consider before accepting or rejecting AI suggestions to identify which supporting content helps them make a choice.

  • Make AI easier to understand

    See whether explanations, confidence indicators, sources, and supporting details attract attention to guide clearer ways of communicating AI outputs.

  • Support more informed decisions

    Connect gaze with choices, response times, and task outcomes to uncover how AI-generated information contributes to decision-making.

  • Build evidence around trust

    Combine gaze with questionnaires and behavioral measures to investigate how people monitor, verify, and respond to AI-generated information.

  • Create more intuitive AI interfaces

    Identify where people search, hesitate, or overlook content when using assistants, copilots, and adaptive interfaces to uncover points of friction.

  • Choose designs with confidence

    Compare how people visually navigate alternative interfaces and explanations to identify which concepts communicate information most effectively.

Uses

Applications

Study AI interactions in controlled and real-world settings

Choose a research setup based on where the interaction happens and what you want to measure.

Tobii Pro Spark used in UX design studies.

Controlled interface studies

Study AI interfaces, recommendations, explanations, dashboards, and decision-support tools in controlled conditions using screen-based eye tracking.

Tobii Glasses X  human machine interaction

Real-world interaction

Use eye tracking glasses to investigate how people interact with AI-enabled technology, automation, and physical systems while moving naturally through an environment.

Research insights

Research measures

What you can measure 

Turn visual attention into measurable data to understand how people engage with AI-generated information, explanations, and interfaces.

  • Fixations and dwell time

    Measure which information receives attention and how long people spend examining it.

  • Visual sequence

    See the order in which recommendations, explanations, sources, warnings, and other information are viewed.

  • Revisits

    Identify information people return to as they evaluate an AI output or make a decision.

  • Areas of interest

    Compare attention across specific interface elements, such as recommendations, confidence indicators, explanations, and controls.

Data integration

From gaze data to research insight

Turn recorded gaze into visualizations and measures that help you analyze attention, compare behavior, and connect what people look at with how they respond.

Visualize attention

Use gaze plots, heatmaps, and other visualizations to explore where attention is directed and how viewing behavior unfolds.

Compare areas of interest

Define specific areas of an interface or stimulus to measure and compare attention across elements.

Connect gaze with outcomes

Combine gaze data with decisions, response times, task performance, and other study measures to build a richer picture of the interaction.

From gaze data to research insight

Our technology

Our products

Eye tracking technology for human-centered AI research

Choose screen-based or wearable eye tracking based on your research environment, study design, and the AI interaction you want to investigate.

Not sure which setup fits your research?

Talk to our team about your study design and research requirements.

Other solutions

Explore more ways people engage with technology

Bring eye tracking into your AI research

Find the right eye tracking solution for studying how people experience, evaluate, and interact with AI.

Use cases

Deepen your understanding of human-AI interaction

FAQs

Quick answers

Explore human-centered AI research

Find answers about using eye tracking to study attention, decision-making, trust, and visual behavior as people interact with AI.

Resources & community

Resources & community

Everything you need to get started

Free training, open-source tools, and direct support, designed to get you from unboxing to publishable results as fast as possible.

  • Tobii Academy

    Free online learning platform with structured courses covering every stage of eye tracking research, from fundamental concepts to advanced analysis techniques.

    → Eye tracking fundamentals and methodology

    → Experiment design best practices

    → Tobii Pro Lab software training

    → Data analysis and interpretation

    → Certification tracks

  • Open-source research tools

    50+ community-curated tools, experiment scripts, and integration libraries across the full eye tracking workflow. PsychoPy, MATLAB, Python, LSL, and more.

    Curated catalogue

    PsychoPy integration

    Tobii GitHub

  • Tobii Connect support portal

    Knowledge base, firmware updates, troubleshooting guides, and direct support from Tobii's technical team. Your first stop for any hardware or software question.

    → Product setup and troubleshooting guides

    → Firmware and software downloads

    → Data quality methodology documentation

    → Direct ticket support for registered products

    → Sample projects and demo recordings