What Is Feminist Artificial Intelligence? Perspectives from the Middle East and North Africa

What Is Feminist Artificial Intelligence? Perspectives from the Middle East and North Africa

by Nagla Rizk, PhD

Humanities, Social Sciences & Thought AI & Society UBDigital and Information technology: general topicsUBJDigital and information technologies: social and ethical aspects
🎙 Nagla Rizk, PhD 👥 1K 📅 February 10, 2026 ⏱ 51 min 👁 114 📄 expert opinion 🧭 2026-08-16
Available in: English (current) Français

Keywords

feminist AIgender biasintersectionalityresponsible AIMENA

Summary

In this talk, Nagla Rizk, Professor of Economics at the American University in Cairo, explores the concept of feminist artificial intelligence (AI) from a Middle East and North Africa (MENA) perspective. She begins by defining key terms: AI, generative AI, agentic AI, feminism, and intersectionality. She then presents evidence of gender bias in AI systems, including biased image search results, gendered language in translation, and biased hiring algorithms (e.g., Amazon’s tool). She discusses real-world impacts on women in gig work, credit, and health, highlighting how data, algorithms, and people interact to perpetuate inequalities. Rizk defines feminist AI as a proactive, transformational approach to dismantle oppressive systems and build inclusive AI based on principles of justice, transparency, and agency. She introduces related concepts like technofeminism and data feminism, and outlines principles for feminist AI derived from responsible AI frameworks. She provides examples of feminist AI solutions, including gender-neutral voice assistants, bias auditing tools, and initiatives from her region. She highlights her own work at the Access to Knowledge for Development Center, including research on women’s health data, gig work, and an intelligent tutoring system for girls. She concludes by advocating for a feminist AI agenda that addresses intersectionality, promotes disaggregated data, and adopts a multistakeholder approach.

205 words

Critical Evaluation

Value of the Information & Strength of the Argument

The talk provides valuable insights into the need for feminist AI, supported by concrete examples of AI bias and its societal impacts. The speaker’s argumentation is coherent, moving from problem identification to definition and solutions. She effectively uses case studies and her own research to illustrate points. However, the argumentation is largely one-sided, with limited discussion of potential criticisms or limitations of feminist AI approaches. The interactive elements mentioned are not fully captured in the transcript, but the presentation is structured and persuasive.

92 words

Title / Content Match

The title accurately reflects the content, which defines feminist AI and provides perspectives from the MENA region.

Quality & Reliability

8/10

The talk is grounded in the speaker's extensive academic and policy expertise, referencing documented cases of AI bias and her own research. However, it is primarily an opinion/advocacy piece with limited critical examination of counterarguments.

Key Moments

Markers derived by PSI from the transcript: the creator did not define chapters.

Cited Sources

  • Oxford Handbook of Ethics of Artificial Intelligence — Mentioned as authored work by the speaker.
  • The State of Open Data, Histories and Horizons — Mentioned as authored work by the speaker.
  • Invisible Women — Referenced as a book with examples of gender bias in design.

Concurring Sources

  • Amazon's hiring tool — Referenced as an example of AI bias in recruitment.
  • Apple Card algorithm — Referenced as an example of gender bias in credit decisions.

Contribution & Novelties

The talk provides a comprehensive overview of feminist AI from a MENA perspective, emphasizing the importance of context and intersectionality. It offers a framework for understanding feminist AI principles and showcases practical examples from the region, contributing to the global discourse on AI ethics and gender.

Pour aller plus loin :

  • Technofeminism — A theoretical framework analyzing the intersection of gender and technology.
  • Data Feminism — A way of thinking about data science informed by feminist critical thought.
  • Intersectionality — A concept highlighting how social categories overlap to shape experiences.
  • Responsible AI — Principles for ethical AI development and deployment.

100 words

Radar Profile

The radar profile shows high scores in information quantity, quality, and reliability, with a moderate technical level. This indicates a well-informed and credible talk that is accessible to a broad audience, with a strong emphasis on real-world examples and expert knowledge.

Reliability 8/10