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Results for "information design"

Information Design under Uncertainty

MBZUAI ·

Munther Dahleh from MIT gave a talk on information design under uncertainty, focusing on the challenges of creating an information marketplace. The talk addressed the externality faced by firms when information is allocated to competitors, and considered two models for this externality. The presentation included mechanisms for both models and highlighted the impact of competition on the revenue collected by the seller. Why it matters: The research advances understanding of information markets and mechanism design, relevant to the growing data economy in the GCC region.

Making sense of data in the age of AI

MBZUAI ·

Laura Koesten, Assistant Professor of Human-Computer Interaction at MBZUAI, studies how people interpret and interact with data, driven by the increasing need to adapt digital environments to people. Her work focuses on making data more accessible and understandable for various audiences, drawing from her Ph.D. research at the University of Southampton and postdoctoral work at King's College London. She emphasizes the importance of data literacy for citizens in understanding how data is used in decision-making systems. Why it matters: This research contributes to bridging the gap between complex AI systems and human understanding, fostering broader societal engagement with data-driven technologies in the UAE and beyond.

Fact checking with ChatGPT

MBZUAI ·

A new paper from MBZUAI researchers explores using ChatGPT to combat the spread of fake news. The researchers, including Preslav Nakov and Liangming Pan, demonstrate that ChatGPT can be used to fact-check published information. Their paper, "Fact-Checking Complex Claims with Program-Guided Reasoning," was accepted at ACL 2023. Why it matters: This research highlights the potential of large language models to address the growing challenge of misinformation, with implications for maintaining information integrity in the digital age.

AI-Assisted Knowledge Navigation

MBZUAI ·

Akhil Arora from EPFL presented a framework for AI-assisted knowledge navigation, focusing on understanding and enhancing human navigation on Wikipedia. The framework includes methods for modeling navigation patterns, identifying knowledge gaps, and assessing their causal impact. He also discussed applications beyond Wikipedia, such as multimodal knowledge navigation assistants and multilingual knowledge gap mitigation. Why it matters: This research has the potential to improve information systems by making online knowledge more accessible and navigable, especially for platforms like Wikipedia that serve as critical resources for global knowledge sharing.

CTRL: Closed-Loop Data Transcription via Rate Reduction

MBZUAI ·

A talk introduces a computational framework for learning a compact structured representation for real-world datasets, that is both discriminative and generative. It proposes to learn a closed-loop transcription between the distribution of a high-dimensional multi-class dataset and an arrangement of multiple independent subspaces, known as a linear discriminative representation (LDR). The optimality of the closed-loop transcription can be characterized in closed-form by an information-theoretic measure known as the rate reduction. Why it matters: The framework unifies concepts and benefits of auto-encoding and GAN and generalizes them to the settings of learning a both discriminative and generative representation for multi-class visual data.

Designing the human side of AI

MBZUAI ·

MBZUAI held its inaugural Human-Computer Interaction (HCI) Symposium in Abu Dhabi, focusing on the human and societal impacts of AI. The event, led by Professor Elizabeth Churchill, featured workshops and keynotes from figures like Google's Matias Duarte. Participants collaborated to address critical design aspects of human-AI interaction and co-author a book. Why it matters: The symposium highlights the increasing importance of human-centered design in AI development, ensuring AI tools are useful, desirable, and beneficial for society in the GCC region and beyond.

Detect – Verify – Communicate: Combating Misinformation with More Realistic NLP

MBZUAI ·

Iryna Gurevych from TU Darmstadt discussed challenges in using NLP for misinformation detection, highlighting the gap between current fact-checking research and real-world scenarios. Her team is working on detecting emerging misinformation topics and has constructed two corpora for fact checking using larger evidence documents. They are also collaborating with cognitive scientists to detect and respond to vaccine hesitancy using effective communication strategies. Why it matters: Addressing misinformation is crucial in the Middle East, especially regarding public health and socio-political issues, making advancements in NLP-based fact-checking highly relevant.

Immersive Analytics: Visualising Data in the Space Around Us

MBZUAI ·

The article discusses immersive analytics, which uses VR and AR to visualize data in 3D and embed it into the user's environment, and reviews systems and techniques from the Data Visualisation and Immersive Analytics lab at Monash University. It explores the concept of "embodied sensemaking" and its potential to improve how people work with complex data. Professor Tim Dwyer directs the Data Visualisation and Immersive Analytics Lab at Monash University. Why it matters: Immersive analytics could significantly enhance data comprehension and decision-making across various sectors in the Middle East, where large-scale projects and smart city initiatives generate vast datasets.