Ethics isn't optional. It's the foundation.
In the age of AI, the questions of who owns data, who benefits from technology, and who gets left behind aren't abstract. They're urgent. My work is guided by a simple principle: technology should create value for people, not extract it from them.
Case Study
Diversity Photos v. Adobe
When I built Diversity Photos, the mission was clear: create ethical stock media that authentically represents people of color and underrepresented communities. What I didn't anticipate was that the platform would become the center of a fight that defines creator rights in the AI era.
Adobe trained AI models on Diversity Photos content without authorization. This wasn't a hypothetical concern or a policy debate — it was a direct violation of creator sovereignty. The images created by and for underrepresented communities were being used to train systems without consent, compensation, or acknowledgment.
I pursued arbitration. Not because it was easy, but because staying silent would normalize the extraction. If a trillion-dollar company can train AI on creator content without permission, what precedent does that set for every independent creator?
This case is about more than one platform or one company. It's about establishing that creators — especially creators from marginalized communities — have rights over their work that technology companies must respect.
Where I Stand
AI Training & Creator Rights
AI models should not be trained on content without explicit, informed consent from creators. Opt-out is not consent. Buried terms of service are not consent. Creators deserve transparency about how their work is used and fair compensation when it contributes to commercial AI systems.
Data Sovereignty
People should own and control their data. Period. Every product I build starts with this principle — data is stored with user consent, used only for stated purposes, and never sold to third parties. Privacy isn't a feature; it's a right.
Equitable Technology
Technology amplifies existing power structures. Without intentional design, it will amplify inequality. Building ethically means asking who benefits, who is harmed, and who is excluded — before shipping, not after.
Responsible AI Development
AI has immense potential to create opportunity, but only if developed responsibly. That means fair compensation for data labelers, transparent training data provenance, bias auditing, and accountability when systems cause harm.
Let's Talk About Ethics
Whether you're a journalist covering AI ethics, a founder thinking about responsible development, or someone who cares about these issues — I'd love to connect.
Get in Touch