Senate Foreign Relations Committee Democrats issued a statement regarding reports of a bribe from UAE officials to the Trump family. They urged the Biden Administration to investigate these allegations thoroughly and provide Congress with relevant information. The statement highlights concerns about foreign influence and potential illicit financial activities in U.S. politics involving Middle Eastern actors. Why it matters: This political development concerns allegations of corruption involving foreign officials and could impact diplomatic relations between the United States and the UAE, though it is not directly related to artificial intelligence.
Dr. Abdelrahman AlMahmoud from TII's Secure Systems Research Center (SSRC) will participate in a WGISTA webinar on adopting a digital mindset in auditing and fighting corruption. The webinar, organized by the International Organization of Supreme Audit Institutions (INTOSAI), will discuss the impact of emerging technologies on public sector auditing. Dr. AlMahmoud will share insights on how AI and Big Data can enable auditors to process data at a new scale. Why it matters: This highlights the UAE's growing role in applying advanced technologies like AI and big data to improve governance and accountability in the public sector.
Xiuying Chen from KAUST presented her work on improving the trustworthiness of AI-generated text, focusing on accuracy and robustness. Her research analyzes causes of hallucination in language models related to semantic understanding and neglect of input knowledge, and proposes solutions. She also demonstrated vulnerabilities of language models to noise and enhances robustness using augmentation techniques. Why it matters: Improving the reliability of AI-generated text is crucial for its deployment in sensitive domains like healthcare and scientific discovery, where accuracy is paramount.
The paper introduces VENOM, a text-driven framework for generating high-quality unrestricted adversarial examples using diffusion models. VENOM unifies image content generation and adversarial synthesis into a single reverse diffusion process, enhancing both attack success rate and image quality. The framework incorporates an adaptive adversarial guidance strategy with momentum to ensure the generated adversarial examples align with the distribution of natural images.
MBZUAI researchers are studying how AI can be used to combat disinformation and improve news verification during elections, as AI amplifies the volume and speed of fake news. Dilshod Azizov is using machine learning to spot patterns in news that will improve verification, while Preslav Nakov's FRAPPE system identifies persuasive techniques and framing in news articles. FRAPPE uses machine learning and NLP to analyze news presentation and reporting, aiming to help users understand the underlying context of news. Why it matters: This research highlights the potential of AI to both negatively and positively impact democratic processes, emphasizing the need for tools to analyze and verify information in the face of increasing AI-generated disinformation.