NYU and NYU Abu Dhabi researchers are working on user-centric gender rewriting in NLP, especially for Arabic. They are building an Arabic Parallel Gender Corpus and developing models for gender rewriting tasks. The work aims to address representational harms caused by NLP systems that don't account for user preferences regarding grammatical gender. Why it matters: This research promotes fairness and inclusivity in Arabic NLP by enabling systems to generate gender-specific outputs based on user preferences, mitigating biases present in training data.
KAUST hosted a regional Women in Data Science (WiDS) conference, part of a global event held at over 100 regional institutions led by Stanford University. The KAUST event featured exclusively female speakers and aimed to highlight data science research and applications. KAUST is launching a 'Women in Data Sciences and Technology' initiative to support women's education and careers in the field. Why it matters: This initiative can help address the underrepresentation of women in data science in Saudi Arabia and the broader region.
The Special Olympics Global Center Summit in Abu Dhabi convened 300 advocates to discuss social inclusion for individuals with intellectual disabilities. A panel including MBZUAI's Elizabeth Churchill highlighted AI's role in inclusive technology design, especially in education. Churchill noted AI can personalize learning through tailored regimens, emotion detection, and understanding cognitive patterns. Why it matters: AI-driven personalization has potential to transform education and accessibility for children of determination and other underrepresented groups in the region.
MBZUAI is highlighting five female leaders in AI for International Women’s Day, noting its 28% female student body. Dr. Farida Al Hosani is developing an AI healthcare solution for non-communicable diseases and was appointed VP of MBZUAI’s Alumni Advisory Board. Dr. Hanan Aldarmaki focuses on improving Arabic automated speech recognition and recently won an award for a paper on Arabic speech processing. Why it matters: Showcasing women in AI leadership helps promote diversity and inclusion in the field, especially in the context of the rapidly growing AI ecosystem in the UAE.
KAUST is launching the "Dear AI" campaign and hackathon to address gender bias and under-representation of women and Saudi/Arab people in AI, after finding AI image tools return only 1% women for prompts like "imagine entrepreneur." The campaign calls for accurate representation in AI datasets from Saudi Arabia and beyond. KAUST notes that 47% of graduates in their AI academy are women. Why it matters: This campaign highlights the need for more inclusive AI training data and addresses gender imbalances in STEM fields in Saudi Arabia.