 Good morning, everyone, and welcome back to beautiful Palo Alto, California. We're here at the Women in Data Science Worldwide Conference, where 400 attendees are expected to attend here in person on campus at Stanford, with thousands of attendees around the world in 57 countries joining virtually worldwide. This is all a part of a celebration of International Women's Day. Happy International Women's Day to all of the women out there watching this, who are fighting the good fight, who are in data science, or who are in the technology community. We see you and we honor you, and we are very excited to bring in a power-packed lineup of extraordinarily brilliant women in data science to you. We're going to have over 10 guests today. We're going to have everything from students, to engineers, to leaders, to founders. We're going to look at the cross-sections of everything from human trafficking to space satellites to we're going to have folks from Pinterest. We're going to have folks from a variety of different walks of life that are looking at how we can use AI and data science for inclusion, for public health, for fighting fraud, for fighting child abuse, for many of the issues that affect all of our daily lives, regardless of gender. Very excited also to be celebrating the ninth year of WID's conference. They started in 2015 with a one-day event here in Stanford, and nine years later, absolutely crushing it. Some fun numbers for you. There are now over 200 events around the world. There is a Datathon, there are podcasts, there's a WID's Academy, there's a NextGen Outreach program, there's an uplink platform for career training. There are over 150,000 participants in this community worldwide, in 160 countries. That is an absolutely impressive piece of data, even with those impressive numbers. Representation for women in data science still has a long way to go, and that's exactly why the conversations we're going to have on the cube here today are absolutely vital and so important. Currently, less than 20% of students in data science are female, and unfortunately, less than 10% of decision makers in the field are female. Why does this matter? Because this affects unconscious bias in AI. The models that are being developed today, and the machines that are learning on them, the data there is often biased because we don't have women in the room. Because if there's only one in 10 decision makers helping program these models, how can we ensure that those models are inclusive? When this happens, the models actually exacerbate the lack of inclusion within our sector, and we need women in the boardroom representing the vital issues at the highest level. Data science isn't just for super technical folks, it's for people who understand the science around what people and groups do. We need to understand how the data that affects our everyday lives then gets turned into the products and technological solutions that shape our future, literally touching just about every single thing we do. We're also going to be talking about accessibility. We're going to be talking about talent shortages and ways to fight that, and hopefully, from all of our fabulous guests, we're going to be getting some fantastic advice on how to be a better ally and how to encourage more women to pursue careers and to stand up for the things they believe in in data science. Thank you all for tuning in today. My name is Savannah Peterson, live here in Palo Alto, California, with theCUBE for our all-day broadcast at Women in Data Science Worldwide.