Copyright Assumption Testing
Assigned to: Tuvana, Arda
We believed that: Enterprise users would prefer a tool that helps them quickly check if AI-generated images are safe to use. We thought they’d value this feature because it saves legal time and prevents copyright issues.
We observed that: We tested our prototype with three people who tried out our platform.
Archit said the dashboard looked “good but cluttered.” He thought higher-level managers would want to see only the most important numbers, not small details like daily usage. He said the copyright check was the main benefit, but the layout could be simpler. It’s important for us to not overwhelm our users.
Will noticed the “98% safe” score and said, “What’s happening with that 2% that’s not compliant?” He wanted to click the number and see what caused it. He also said that for big teams, uploading one image at a time wouldn’t work. He suggested adding bulk upload and even a Google Slides plug-in that works like Grammarly to check all images at once.
Aidan said the interface worked fine for a prototype but looked “a bit rough.” He said he wouldn’t completely trust it yet for enterprise use because the confidence scores weren’t explained. Still, he liked the idea and said it could “help companies avoid lawsuits” if it worked well and scaled better.
Overall, everyone liked the idea of copyright safety, but they wanted clearer explanations, faster checks, and easier ways to use it at scale.
From that we learned: People care about trust and efficiency. Enterprise users want to understand why an image is not safe and see clear explanations for the numbers. They also want this tool to fit into their normal workflow, not something that makes them upload one image at a time.
Therefore, we will: We will redesign the feature into a simpler dashboard that is easier to understand and use. We will make sure to implement plug-ins for easier access to platforms like Google Slides and allow users to upload many photos at once. We will also work on improving the score so that if it shows 98%, it explains what the missing 2% means and what the specific risks are. Lastly, we will test these updates with more users to see if the simpler design and added features make them trust the platform more and be more likely to use it.
Ethics Assumption Testing
Assigned to: Reyna, Nayan
We believed that: Enterprise buyers would value ethical verification of images and would pay extra stock pricing.
We observed that: Ethical verification mattered situationally. Users said in some cases they would value ethical verification but in others they would not. It mattered more for small teams or governments that cared about ethics and less for large companies that solely prioritized profit. We also observed that users were not very clear on what we meant by “ethical” and confused it with the copyright verification.
From that we learned: We learned that users may not place as much importance on the ethics of the images as much as the copyright aspect, as users stated that corporations will most likely only pay attention if it is a matter of legal consequences.
Therefore, we will: Add clarity and explanations of what goes into our ethical verification of images on the prototype and what it means/what its implications are. Place more emphasis on the copyright aspect of images as an incentive for enterprises to purchase our images.
General Takeaways & Going Forward
We observed that users saw value in the copyright protection aspect of our prototype but were less enthusiastic about the ethics behind our image generation. They believed enterprises would pay more for copyright protection but would be less likely to do so solely for ethically-sourced images. Based on common mistakes/confusion we noticed during prototype testing, there are several changes we plan to focus on. We plan to add a stock photo specific tab that allows users to search through our stock photos. We also plan to clarify the ai image generation page as users were confused by our wording. Finally, we will add a page specifically about our company’s mission/what differentiates us to clarify how our images are ethically sourced and produced.
Transcripts: https://docs.google.com/document/d/1gGKeuts61_sF42qXAPQvo2OGsdsdl4r2obWcAfbr0s0/edit?usp=sharing
