We're hiring experienced professionals to evaluate and compare business presentation slide decks. This paid study focuses on training artificial intelligence models to recognize high-quality professional presentations.
Digital Product Users: Feedback on Everyday Tasks
Remote (Global)
$30
October 21, 2026
Job description
What We're Researching
We're running a paid study on how people navigate everyday digital interfaces. We want to understand the common friction points users experience when completing basic online activities. Your feedback directly informs how we structure future digital tools.
How It Works
You will complete a set of guided questions and a few small usability tasks. During the session, you will review brief scenarios and share your honest reactions to the process. We will ask you to think aloud as you navigate through the provided examples. The entire process takes place remotely from your personal computer.
Who This Is For
We welcome everyday internet users who regularly engage with digital products. You do not need specialized technical knowledge or professional software experience to participate in this study. Anyone comfortable navigating web browsers and sharing their open thoughts is encouraged to apply.
Responsibilities
- Complete a brief set of digital tasks and short questions
- Share your honest opinions on the ease of use
- Navigate through provided scenarios while explaining your thought process
- Provide clear feedback on what works well and what could be improved
Requirements
- Regular user of basic digital products and web browsers
- Comfortable sharing your thoughts openly during a guided session
- Access to a reliable computer with an internet connection
Apply now
Opens terac.com in a new tab. If they ask how you found the role, mention RemoWork.
We're running a paid study on clinical decision-making to help benchmark medical AI systems. This work feeds directly into improving how automated tools interpret pharmaceutical data and patient cases.
We're running a paid study on clinical image interpretation to build robust performance benchmarks. This work directly supports the development of more accurate diagnostic evaluation tools by establishing reliable scoring rubrics.
We're running a paid study on medical imaging diagnostics to build high-quality clinical reference benchmarks. This work directly supports the validation of advanced clinical tools by establishing reliable scoring rubrics based on expert reads.