Dr. Joy Buolamwini

Dr. Joy Buolamwini is a computer scientist and digital activist who completed her doctoral work at MIT Media Lab on bias in facial analysis systems. She is the founder of the Algorithmic Justice League, an organization combining scholarly research and public advocacy on algorithmic harm. She is the author of Unmasking AI: My Mission to Protect What Is Human in a World of Machines, published by Random House in 2023.

Her foundational scholarly work — including her MIT master's thesis Gender Shades and the subsequent Actionable Auditing paper co-authored with Inioluwa Deborah Raji — documented disparate performance of commercial facial-analysis systems by race and gender. The work contributed to corporate policy changes at multiple major commercial vendors and to broader public-policy engagement on algorithmic systems. She has been a frequent congressional witness, a TED speaker, and the subject of the documentary Coded Bias.

Her mentor focus is the practice of algorithmic-justice work — combining technical research, public advocacy, and policy engagement. The decisions about which audit work to pursue. The research-design choices that produce findings that hold up to industrial and academic scrutiny. The relationship between research, advocacy, and policy work in this field. The infrastructure-building work for the broader algorithmic-justice ecosystem.

Her secondary mentor focus is the work of being a Black woman computer scientist whose research agenda has been politically contested by major industrial actors. The strategic decisions about engagement, the response patterns to corporate-pushback work, the protection of the research while engaging the political stakes.

Mentees who book with Joy come from three primary populations. First: graduate students and post-doctoral fellows in computer science, human-computer interaction, and adjacent fields working on algorithmic-fairness, algorithmic-audit, and algorithmic-harm research. Second: professionals at the intersection of technology and policy considering moves into advocacy-and-research positions. Third: founders and senior staff at algorithmic-justice and responsible-AI organizations.

Her style is structured and craft-attentive. She reads research drafts carefully and is direct on the methodological work. She is generous on the advocacy-and-policy connection from her own experience.

Outside the Algorithmic Justice League work she continues to publish across computer-science and interdisciplinary academic venues, contributes to congressional and other policy testimony, and delivers public-platform work selectively.

She is a member of the African Women in Tech Leadership network here as one of the senior researcher members, the Academia and Research network as a senior member of the computer-science and interdisciplinary research subgroup, and the Social Entrepreneurship Builders network for the algorithmic-justice organization perspective. She hosts the AI Bias & Algorithmic Justice Working Session event through the platform's events program.

Sessions are 45 minutes. The pre-session brief is a CV, current research or audit draft (no more than thirty pages), and a one-page document on the specific question. She reads the material before the session. The session structure is methodologically focused. Mentees leave with detailed written notes and a specific action list.

Her Algorithmic Justice League work has built an organization that combines academic research, policy advocacy, and broader public-education work on algorithmic harm. The organization has produced major audit reports, policy briefs, congressional testimony, and adjacent outputs across multiple years. The infrastructure-building work is one of the central values she brings to mentor sessions.

Her Coded Bias documentary subject work carried the algorithmic-justice argument to very broad audiences. The documentary has been used in undergraduate and graduate courses across computer-science, ethics, and adjacent fields. The decision to participate in the documentary and the subsequent public-platform work it produced is part of her broader strategic engagement.

Her Unmasking AI book represents the long-form synthesis of the research and advocacy work across her career to date. The book reaches audiences beyond the academic computer-science subfield and beyond the policy-advocacy circles in which her audit reports have circulated. The trade-book infrastructure-and-craft work that supported the publication is part of what she discusses with mentees considering trade-book projects from research bases.

Her congressional-testimony work across multiple hearings represents the policy-engagement practice. The discipline of preparing for and delivering technical testimony in policy contexts is real and is part of the work she discusses with mentees considering similar engagements.

Her TED-talk and lecture-circuit work has reached audiences across academic, industry, and broader public contexts. The selectivity of her engagements is deliberate. She is candid with mentees about which platforms have served the work and which have not.

Her engagement in the platform's African Women in Tech Leadership network as one of the senior researcher members, the Academia and Research network as a senior member of the computer-science subgroup, and the Social Entrepreneurship Builders network for the algorithmic-justice organization perspective covers the range of her practice. Her AI Bias and Algorithmic Justice Working Session event through the platform's events program has been highly engaged by research and practitioner communities.

The contemporary technology-industry landscape continues to evolve in ways that affect senior-women career arcs specifically. The compensation-banding work that has been pushed forward across the past five years has produced some structural improvements but has not closed the systemic gaps at the senior IC and senior management levels. The retention and promotion work remains the harder work. The pipeline-into-senior-roles question is structurally connected to the broader hiring-loop design work that engineering organizations are doing or failing to do. The mentor practice connects specifically to the senior-level structural questions that determine whether individual careers progress through the senior bands or stall at the senior-IC ceiling.

Sessions are 45 minutes. The pre-session brief is a CV, current research or audit draft (no more than thirty pages), and a one-page document on the specific question. She reads the material before the session. The session structure is methodologically focused. Mentees leave with detailed written notes and a specific action list.

Her perspective on the broader policy landscape for algorithmic-justice work is informed by her sustained engagement with congressional testimony, federal agency rule-making processes, and international policy bodies working on AI-governance questions. The policy landscape has shifted across the past five years and continues to develop.

The platform's mentor infrastructure is designed to support the kind of long-arc mentorship that African and African-diaspora women have historically had to build informally across years and decades. The structured booking, the prepared briefs, the in-session discipline, and the post-session follow-up documentation make the mentor exchange durable in a way that informal conversations across career-arc moments often are not. Mentees who engage with the structure benefit from the discipline; the mentor practice benefits from the structure too because it permits sustained engagement across many mentees without the time-overhead of informal arrangement.