Sasha Luccioni
๐ค SpeakerAppearances Over Time
Podcast Appearances
So try to picture a scientist in your mind.
Don't look at me.
What do you see?
This is what Dolly 2 sees.
It's a common image generation model.
Let's compare this to stable diffusion, another one.
A lot of the same thing, right?
Men in glasses and lab coats, and none of them look like me.
And the thing is, is that we looked at all these different image generation models and found a lot of the same thing.
Significant representation of whiteness and masculinity across all 150 professions that we looked at.
Even if compared to the real world, the US Labor Bureau of Statistics, these models show lawyers as men and CEOs as men almost 100 percent of the time, even though we all know, as many of you here are CEOs and lawyers,
Not all of them are white and male.
And sadly, my tool hasn't been used to write legislation yet, but I recently presented it at a UN event about gender bias as an example of how we can make tools for people from all walks of life, even those who don't know how to code, to engage with and better understand AI, because we use professions, but you can use any terms that are of interest to you.
And as these models are being deployed, are being woven into the very fabric of our societies, our cell phones, our social media feeds, even our justice systems and our economies have AI in them.
And it's really important that AI stays accessible so that we know both how it works and when it doesn't work.
And there's no single solution for really complex things like bias or copyright or climate change.
But by creating tools to measure AI's impact, we can start getting an idea of how bad they are and start addressing them as we go.
start creating guardrails to protect society and the planet.
And once we have this information, companies can use it in order to say, OK, we're going to choose this model because it's more sustainable, this model because it respects copyright.
Legislators who really need information to write laws can use these tools to develop new regulation mechanisms or governance for AI as it gets deployed into society.