A survey of 92 library and information science (LIS) professionals in the UAE reveals strong cognitive AI competencies but gaps in behavioral and normative competencies related to AI biases and ethics. The study identifies a disconnect between the perceived importance of AI skills and the effectiveness of current training programs. It recommends that library training programs address AI ethics and biases.
MBZUAI alumnus Abdulaziz Aleissaee is working as a Senior Specialist in AI at Abu Dhabi Media Company after graduating from MBZUAI's inaugural class. He credits his early interest in video game NPCs with sparking his passion for AI, leading him to implement AI solutions at Abu Dhabi Media. He emphasizes the importance of sharing AI knowledge and combating AI illiteracy. Why it matters: This highlights MBZUAI's role in developing local AI talent and its graduates' contributions to AI adoption in key regional industries like media.
MBZUAI launched its Executive Program, a hybrid course for government and industry leaders to promote greater engagement with AI. The program's first session, led by MBZUAI President Eric Xing, covered the history and future of AI and machine learning. It aims to accelerate AI development across various sectors in the UAE, focusing on efficiency, cost savings, and environmental impact reduction. Why it matters: This initiative signals the UAE's commitment to fostering AI literacy and driving AI adoption across key sectors, aligning with national economic development plans.
A new paper from MBZUAI introduces JEEM, a benchmark dataset for evaluating vision-language models on their understanding of images grounded in four Arabic-speaking societies (Jordan, UAE, Egypt, and Morocco) and their ability to use local dialects. The dataset comprises 2,178 images and 10,890 question-answer pairs reflecting everyday life and culturally specific scenes. Evaluation of several Arabic-capable models (Maya, PALO, Peacock, AIN, AyaV) and GPT-4o revealed that while models can generate fluent language, they struggle with genuine understanding, consistency, and relevance, especially when cultural context is important. Why it matters: This research highlights the challenges of building AI systems that can truly understand and interact with diverse cultures, emphasizing the need for culturally grounded datasets and evaluation metrics.