“Life doesn’t always give us what we deserve, but rather, what we demand. And so you must continue to push harder than any other person in the room.” Those words from Wadi Ben-Hirki, a young feminist activist from Nigeria, are a good reminder that gender equity is still a problem in nearly all fields. The tech field is no exception, and this has been obvious (and repeatedly stated) for decades. But the emergency of AI as a special and distinct field gives us the opportunity to highlight what women in technology have brought to the table.
Gender inclusivity and women’s empowerment are not just advertising tags or feel-good slogans. Call it essentialism or just empirics, but some notable women in AI are asking foundational questions and offering binary-splitting solutions. When the nonprofit consortium “Women in AI” recently met for a conference at Trinity College in Dublin, Ireland, the purpose of the conference wasn’t some kind of inward identity gazing, but instead an outward, socially relevant gaze on “ethically-driven AI design.” One of the organizers was Alessandra Sala whose “research at Nokia Bell Labs focuses on distributed algorithms and complexity analysis with an emphasis on graph algorithms and privacy issues in large-scale networks.”
An ongoing conversation about gender in technology, and AI in particular, is also critical for growth and self-reflection in the industry. Consider Jane Crofts, founder of Data to the People, a global data literacy nonprofit. One of her curiosity-spawned projects is Databilities, “an evidence-based data literacy competency framework that was launched at the 2018 United Nations World Data Forum.”
And consider also Abeba Birhane, a graduate student in cognitive science at University College Dublin, in Ireland. Birhane also works for the Irish software research center Lero. She specializes in complexity science and the philosophy of technology. Birhane has emerged as a powerful voice of anti-Cartesianism. What does that mean? Rene Descartes (hence “Cartesianism”) is the French philosopher responsible for constructing a “subject-object” dichotomy that is at the root of a lot of our assumptions about humans (the subject) being able to control and predict the world (the object).
Birhane provocatively names the audacious hypotheses that emerge from subject-object thinking: our assumption that we can “predict people’s behaviour with precision . . . tell whether someone is going to a commit crime before they do . . . The quest for absolute certainty has been at the top of Western science’s agenda,” she writes, and AI research similarly strives “for generalizability and predictability.” But reality is never predictable. It’s infinitely complex.
This is a shattering of the dominant AI narrative. It opens the door for a more nuanced and patient approach to reaching people—perhaps analogous to “deep canvassing,” the new (and technology and ethics-driven) campaign paradigm that is made up of ongoing conversations between canvassers and potential voters. It’s a process that allows complexity and human infinitude to drive the conversation—people change their minds, or solidify their positions for their reasons in dialogue with others. This endeavor is aided by the tech developed by Open Field, a project of two more notable tech women, Emily Del Beccaro and Ari Trujillo Wesler. Because more personalized and spontaneous campaigning requires the ability to fill in information while out canvassing rather than collecting and integrating it later, Open Field offers services like real time analytics dashboards and the ability to quickly customize scripts, among other things.