Summary: UCLA researchers have developed a webcam-based eye-tracking tool for Qualtrics online surveys that verifies human presence and participation during survey completion, while also allowing researchers to collect eye-tracking data without specialized hardware. Background: Online survey research is facing growing data integrity problems as AI agents become more capable of completing surveys in ways that look human. Existing safeguards such as CAPTCHAs and attention checks can be bypassed and do not reliably determine human presence and engagement. As AI-based browsing and response tools become readily accessible, there is a growing need for stronger methods to protect online research integrity from bot-generated responses. At the same time, researchers also seek improved tools for understanding how participants visually engage with survey content. Because of this, there is a need for a survey-integrated system that can both verify respondent presence and collect eye-tracking data using standard consumer hardware. Innovation: UCLA researchers have developed a tool that embeds webcam-based eye tracking directly into Qualtrics online surveys. Using a standard computer camera and machine learning, the system estimates eye-gaze location in real time and provides a form of human verification based on physical presence during survey completion. The tool is designed as a plug-and-play Qualtrics template, allowing researchers to launch eye-tracking-enabled surveys without needing to write code. The innovation operates through a persistent tracking layer integrated into the survey environment, configurable embedded-data settings, and a client-side buffering approach that captures gaze coordinates and timestamps during a session before transmitting the data upon page submission. By combining human verification with behavioral data collection, the technology strengthens survey integrity while also providing researchers a practical method to study respondent attention and engagement. Potential Applications: ● Online survey research ● Human verification in digital studies ● Bot detection in behavioral research ● Eye-tracking in Qualtrics surveys ● Attention and engagement analysis ● Market research and consumer behavior studies ● Remote academic and clinical research data collection ● Surveillance infrastructure Advantages: ● Verifies that a respondent is physically present ● Provides stronger protection against AI bot survey completion ● Utilizes a standard webcam rather than specialized eye-tracking hardware ● Integrates directly into Qualtrics ● Allows researchers to collect eye-tracking data without coding ● Separates configuration from code for easier use ● Supports continuous recording across survey blocks ● Enables both survey security and behavioral data collection in one system State of Development: First description of complete invention. Related Papers: ● https://www.pnas.org/doi/10.1073/pnas.2518075122https://roundtable.ai/https://repdata.com/WebEyeTrack ● https://arxiv.org/abs/2508.19544 ● https://www.cambridge.org/core/journals/judgment-and-decisionmaking/article/webcambased-online-eyetracking-forbehavioralresearch/B726E77B68A76577F9BC6BB8F1EBC6E4 ● https://link.springer.com/article/10.3758/s13428-017-0913-7 Reference: UCLA Case No. 2026-192 Lead Inventor: Ian Krajbich - UCLA Psychology Department