Feminist AI 101: Promo Video Transcript

Video link: https://vimeo.com/736963978

Lindsey: So Emily, your course outline for feminist AI 101 looks really cool. Can you tell us about your course? What is the course about? What makes it unique? 

Emily: Yeah, Absolutely. Thanks so much. I will be teaching feminist AI 101. And essentially it is a course to introduce non-technical people to the ideas of machine learning from a conceptual perspective.

And then, with that grounding, we're going to be able to start thinking really critically about how we use or might use machine learning for social good, including in international development efforts as well as nonprofit social sector, government services work here in the United States. And what makes the course really unique is that right now we have a growing movement and momentum in the social sectors for AI for good and absolutely there are some really neat ways that we can use AI for social good.

Yet at the same time, in data-rich United States, we have some amazing rock star feminists of color who are saying, Hang on! Hold up. This reproduces [and] amplifies inequalities, and we need to think a whole lot more about this.

And so the course is really unique in the sense that it tries to connect these two different discussions. Yes, we want to find ways to use AI for social good and at the same time we want to be really critical, thoughtful, [and] feminist in our applications. 

Lindsey: That sounds awesome. Who should come to this course? Who is your main audience for this course?

Emily: This is a course, for, as I mentioned before, non technical people. So if you're someone who is in the international development or non profit or government services, space and you're hearing that algorithms, machine learning might be used to solve problems and provide solutions in your everyday work life, then this is a course for you to really learn what this world is about to empower you to be part of those discussions.

So if you work in international development and you're a gender advisor, if you work in social inclusion, if you're a backstopper or a project manager, this course is gonna introduce you to these foundational concepts and get you ready to roll. So that oftentimes in software development, we talk about cross-functional teams. And that means that we want a technical person - typically a coder or a developer working in partnership with other people on the team who fill different roles.

But often what i'm seeing and hearing is that the non-technical folks hear “machine learning” and they say I don't know what that is, I can't involve in that but given what feminists of color are saying about how this might reproduce inequalities, we need to make sure that everybody is around the table and fighting for social justice and equity and equality while using machine learning as a potential technical solution.

LINDSEY: Yeah, one of the things that I think is so important about this is that and the way I've observed some of these things come about is that we don't realize some of these new ways we’re using technologies are dangerous until until they already have our data.

So, for example, you were sharing articles with me about the data around tracking menstrual cycles. And now in the context of the United States where in many States, it's illegal to get an abortion, this thing that people have been doing for years in terms of tracking their menstrual cycles - now people are actually realizing hey? this is really potentially dangerous, and could put me at risk. And so sometimes these things sound really cool but we don't realize that there's these real ethical dilemmas that are out there. And so we need to know that going into it.

EMILY: And we are going to dive right into that conundrum into the belly of the beast, If you will. I think there's a broadening public discussion that technology can be a double-edged sword. And so it's really going to empower attendees to think through those issues and chart a critical, careful and thoughtful course of action. So that we can really use machine learning to achieve the social outcomes that we're interested in.

LINDSEY: Great. Alright, thank you so much, Emily. So again, this is feminist AI, 101. We'll pop the dates in a text box up on the screen. Sign up now, and anything last things you want to say Emily?

EMILY: I would just say, because it is a technical topic but it's for non technical folks if you have any questions about whether or not this course is right for you or can add value to your professional career, or just things that you're thinking about. Feel free to reach out, and we can have a one-on-one chat on whether or not this is right for you and how it can meet your needs.