Why I Built This

I keep coming back to one question.

Not to survive. Not to get through the system without getting hurt. To actually have dignity — the kind that doesn't depend on whether the algorithm was trained on data that includes anyone who looks like them, or whether the right person is paying attention that day.

I've watched AI systems make consequential decisions about real people with no record of how they got there. No standard. No named address for the accountability when something went wrong and a real person absorbed the cost of it. That's not a technology failure. That's a design choice.

Design choices can be made differently.

I grew up in Santa Clara. Not near Silicon Valley — in it, before most people knew to call it that. I was here before the map existed. I leaned into AI not because someone handed me credentials but because it was presented to me and it felt right.

I co-built an emotionally intelligent AI system in the early days when there were no frameworks and no protocols. I trained a legal aid model on Bay Area court data for communities that couldn't afford representation. I produced 50 videos on AI education in 2023 and participated in the U.S. Copyright Office's inaugural AI listening sessions — the first time that body formally asked what accountability in AI should look like.

I watched from the inside what happens when there is no accountability layer. No integrity governance. No safeguard architecture. I didn't theorize the problem. I lived it.

The window to be an author of this infrastructure — rather than a subject of it — is open right now. That is not a comfortable statement. It implies the current approach isn't good enough. That the people deploying these systems owe something more to the people they affect. That "the model made the decision" is not an answer.

It's an abdication.

I welcome that implication.