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Controlled interface studies
Study AI interfaces, recommendations, explanations, dashboards, and decision-support tools in controlled conditions using screen-based eye tracking.
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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.
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.
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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.
Choose a research setup based on where the interaction happens and what you want to measure.
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Study AI interfaces, recommendations, explanations, dashboards, and decision-support tools in controlled conditions using screen-based eye tracking.
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Use eye tracking glasses to investigate how people interact with AI-enabled technology, automation, and physical systems while moving naturally through an environment.
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.
Turn recorded gaze into visualizations and measures that help you analyze attention, compare behavior, and connect what people look at with how they respond.
Use gaze plots, heatmaps, and other visualizations to explore where attention is directed and how viewing behavior unfolds.
Define specific areas of an interface or stimulus to measure and compare attention across elements.
Combine gaze data with decisions, response times, task performance, and other study measures to build a richer picture of the interaction.
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Choose screen-based or wearable eye tracking based on your research environment, study design, and the AI interaction you want to investigate.
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Designed for the real world, our advanced wearable eye tracker allows you to conduct behavioral research in a wide range of settings.
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A versatile wearable eye tracker suitable for UX, sports, consumer, and industrial environments. Designed to deliver reliable insights in dynamic, high-movement settings.
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This high-performance research system captures gaze data at speeds up to 1200 Hz. A screen-based eye tracker for extensive research from fixation-based studies to micro-saccades.
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Screen-based eye tracker, capturing gaze data at speeds up to 250 Hz. This powerful research system supports from fixation to saccade-based research outside of the lab.
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Our analytical software helps guide scientific and academic eye tracking research. Take control of your study and analyze the data in detail.
Talk to our team about your study design and research requirements.
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Study visual attention, workload, and situational awareness as people operate interfaces, monitor automation, and interact with complex systems.
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Examine gaze behavior, coordination, and safety as people and robots work together, share tasks, and navigate the same environments.
Find the right eye tracking solution for studying how people experience, evaluate, and interact with AI.
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This guide shows how eye tracking helps teams understand what users notice, how they process information, and where uncertainty appears in AI experiences.
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At Shanghai University SILC Business School, Associate Professor Li-Sheng He explores how people make decisions by studying how attention shapes the way they process visual information.
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In this learn article, we will present how eye tracking technology has been used to study cognitive processes and the insights that these studies have generated.
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Capturing human data using eye tracking in the era of AI matters because we need to dig deep into how someone sees reality, how their conscious and unconscious minds create it.
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This comprehensive guide explores how eye tracking provides a real-time, non-intrusive way to measure cognitive load and unlock insights into learning, decision-making, and performance.
Find answers about using eye tracking to study attention, decision-making, trust, and visual behavior as people interact with AI.
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.
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