MBZUAI student Zain Muhammad Mujahid is researching methods to detect media bias using NLP and LLMs. His approach profiles bias across media outlets using LLMs like ChatGPT to predict bias based on 16 identifiers. The research aims to develop a tool that instantly provides a bias profile for a given media URL. Why it matters: This research has the potential to combat misinformation and enhance media literacy in the region by providing tools to identify biased reporting, and it is expanding to Arabic and other languages.
A new methodology emulating fact-checker criteria assesses news outlet factuality and bias using LLMs. The approach uses prompts based on fact-checking criteria to elicit and aggregate LLM responses for predictions. Experiments demonstrate improvements over baselines, with error analysis on media popularity and region, and a released dataset/code at https://github.com/mbzuai-nlp/llm-media-profiling.
Muhammad Arslan Manzoor became MBZUAI's first NLP Ph.D. graduate, focusing his research on media bias under Professor Preslav Nakov. His thesis, 'MGM,' explored using audience overlap graphs to predict the factuality and bias of news media, an approach that differs from traditional textual analysis. Manzoor's work aims to improve the efficiency of media profiling in real-time by leveraging relationships captured in media graphs. Why it matters: This research offers innovative methods for identifying bias in news, which is crucial for promoting informed social discourse and combating disinformation in the region.
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.
MBZUAI researchers found that only 5.7% of music in existing datasets used to train generative music systems comes from non-Western genres. They discovered that 94% of the music represented Western music, while Africa, the Middle East, and South Asia accounted for only 0.3%, 0.4%, and 0.9% respectively. The team also tested whether parameter-efficient fine-tuning with adapters could improve generative music systems on underrepresented styles, presenting their findings at NAACL. Why it matters: This research highlights the critical need for more diverse datasets in AI music generation to better serve global musical traditions and audiences.
Researchers from MBZUAI, University of Washington, and other institutions presented studies at EMNLP 2024 exploring how LLMs represent cultures. A survey analyzed dozens of recent studies on LLMs and culture and proposes a new framework for future research. The survey found that there is no widely accepted definition of 'culture' in NLP, making it challenging to interpret how models represent culture through language. Why it matters: This highlights a key gap in the field and emphasizes the need for a more rigorous and consistent understanding of culture in AI, especially as LLMs become more globally integrated.
MBZUAI Professor Preslav Nakov has developed FRAPPE, an interactive website that analyzes news articles to identify persuasion techniques. FRAPPE helps users understand framing, persuasion, and propaganda at an aggregate level, across different news outlets and countries. Presented at EACL, FRAPPE uses 23 specific techniques categorized into six broader buckets, such as 'attack on reputation' and 'manipulative wording'. Why it matters: The tool addresses the increasing difficulty in discerning factual information from disinformation, providing a means to identify biases in news media from different countries.
This article discusses the application of AI in semiconductor chip design and manufacturing, with a focus on examples such as IR-drop estimation and lithography processes. It mentions Youngsoo Shin, a KAIST professor and founder of Baum, who is an expert in this area. The article also briefly mentions panel discussion hosted by MBZUAI. Why it matters: AI-driven chip design and manufacturing could accelerate semiconductor innovation in the GCC region and beyond.