Responsible innovation in AI: How you can shape the future | Hugging Face

I'm Emily. Thank you to our friends at Eficode for putting together this beautiful day today. I am excited to talk to you about responsible innovation in AI. I also want to point out that while I do focus on AI, a lot of the information can be applied to many different types of innovation. I'm curious, before we start, how many folks in this room identify as non-engineers? Do we have any non-software developers in the room? Okay, that was kind of interesting because people were waiting to look around first [Laughs], and only then identify. Good. I'm excited you're here. I am also not an engineer. Excited to raise my hand there. I'll tell you a little bit more about my background in a few slides. Hopefully everyone can get something out of this talk. I like to think about responsible AI and responsible innovation in terms of something that's much larger than a technical challenge. We all can play a hand in responsible innovation. It's a shared project. We have our engineers involved. We have the policy team involved, ethics teams, on and on and on. We're all here to do a good job and shape the future of AI. This is essentially what we'll talk about today. I want to define responsibility and then talk you through my five pillars. I've been trying for weeks to come up with a better word than pillar, because I felt that sounds a little hoity-toity. If anyone has any advice after the talk, I'd love to hear it. Then we'll share some examples of folks that maybe didn't do a great job - and some folks that did. Just generally, you know what I look like, but I like to share a photo of myself because then you get to see my chicken. This is Francis. I am a non-engineer, as I mentioned. I have worked at several startups across several different industries. The thread throughout all of that is that I am people-obsessed. I got my start at Hugging Face working very specifically on diversity, inclusion, equity and belonging. For anyone that works in the AI or the machine learning space knows that this is quite a challenge. My role has since expanded to be much more of an employee experience, culture, recruiting type role. I get to give talks like this to awesome people like you, which is exciting. In case anybody is not familiar with Hugging Face, this is our logo. You will now never forget that's the name of this emoji. We are an open source platform where people build and share AI tools together. Are folks familiar with Hugging Face? Have people used it in the past? I see some shaking and some hands raising. Great. I swear I will not focus all of my examples on Hugging Face. But we will pop up every now and again, because we are doing a good job at some things, so I would like to share that. [Laughs] I also want to point out, before we begin, that Hugging Face is fully decentralized. Frankly, when I started at Hugging Face, I didn't have a great understanding for what that actually meant. But in short, it means that every employee at the company is a leader. Our CEO does not set goals for the company that then cascade down through each of the teams. It actually is sort of flipped on its head. Each of our employees is responsible for setting their own goals, often for coming up with their own projects that they believe will be impactful. Our CEO's job is to sell the company. That's important to point out as we get into some of the examples. We will see them moving forward, because decisions, contributions - and innovation really happen at a faster pace across this global community, because there's no single leadership chain. So, responsibility. I was hoping to be able to give you a quick, easy definition, but I can't. [Laughs] We're going to talk about what that means in the context of AI and innovation. We need to ensure that we are considering the broader implications of our work and how it affects society as a whole. It's about being inclusive and making sure that we are not just creating technology for technology's sake, but rather for the benefit of all.