Co-authored formal comments submitted to the United Nations Committee on the Elimination of Discrimination against Women (CEDAW) on behalf of Women in AI Ethics+ (WAIE+), in collaboration with Laura Carter, PhD. The submission responds to Draft General Recommendation No. 41, "Dismantling Gender Stereotypes and the Unequal Power Relations that Sustain Them," with focused analysis on AI's role in perpetuating gender discrimination.

The submission centers a distinction that tends to get lost in AI policy conversations: consumer-facing tools attract scrutiny, but predictive systems quietly shaping access to social services, credit, healthcare, and child welfare are where gender stereotyping does some of its most entrenched and least visible damage. The comments push the Committee toward the specificity and enforceability standard it has applied in other sectors, because process-oriented recommendations that call for dialogue and frameworks without naming obligations don't protect anyone.

Specific recommendations include: transparency and explainability requirements for AI used in consequential decisions affecting women; mandatory pre-deployment gender impact assessments before AI tools enter public service delivery; gender-disaggregated outcome data collection and publication; accessible complaint mechanisms for women harmed by discriminatory outputs; and direct naming of non-consensual synthetic intimate imagery as a distinct, documented form of AI-enabled gender-based harm that policy language needs to address at scale.

Co-author:Laura Carter, PhD, submitted on behalf of WAIE+ (WAIEplus)

Links: | Read the submission on the OHCHR website (search for WAIE+ under CSOs) | DOI: 10.5281/zenodo.20129761

Skills demonstrated: International human rights policy, AI governance, gender impact analysis, formal regulatory comment drafting, UN treaty body engagement, civil society advocacy

Relevant context: CEDAW is the primary international treaty on gender discrimination. General Recommendations carry interpretive authority for the 189 States parties to the Convention. This submission was one of the few from civil society organizations to focus specifically on algorithmic and data-driven systems in public service delivery, rather than consumer-facing AI alone.