Edward Welsh’s Post

In the digital age, AI is crucial in combating deepfakes and misinformation, which pose serious threats to privacy, security, and trust. AI detects deepfakes by identifying subtle patterns and flags misinformation by analyzing linguistic structures. Challenges include the need for labeled data and the ongoing arms race between creation and detection techniques. Continued research and collaboration are key to improving AI's effectiveness in safeguarding truth and trust in the digital era.

In the digital age, AI is crucial in combating deepfakes and misinformation, which pose serious threats to privacy, security, and trust. AI detects deepfakes by identifying subtle patterns and flags misinformation by analyzing linguistic structures. Challenges include the need for labeled data and the arms race between creation and detection techniques. Continued research and collaboration are key to enhancing AI's effectiveness in safeguarding truth and trust in the digital realm.

In the digital age, AI is crucial in combating deepfakes and misinformation, which pose serious threats to privacy, security, and trust. AI detects deepfakes by identifying subtle patterns and flags misinformation by analyzing linguistic structures. Challenges include the need for labeled data and the arms race between creation and detection techniques. Continued research and collaboration are key to enhancing AI's effectiveness in safeguarding truth and trust in the digital realm.

We are thrilled to announce that the ITU Journal has launched a special issue on the "Privacy and Security Challenges of Generative AI." This issue will focus on cutting-edge technologies that address privacy and security concerns in generative AI, including but not limited to areas such as homomorphic encryption, information security, data privacy, and machine learning. We are inviting submissions from researchers working in those fields. The submission deadline is 14 October 2024. For more details and to submit your papers, please visit: https://lnkd.in/g6kPT9aY We look forward to your contributions and engagement! #ITU_Journal #Privacy #Security #FHE #GenAI

"De-Risking AI", Wisely AI's latest white paper, highlights and explains five new risks of Generative AI tools: anthropomorphising chatbots; malicious and commercially protected training data; hallucinations; privacy, data security and data sovereignty; and prompt attacks. The white paper addresses each in detail, and suggest strategies to mitigate these risks. It's part of our core mission to "help organisations use AI safely and wisely." Read or download here: https://lnkd.in/gV-peEKB

Targeting the Core: A Simple and Effective Method to Attack RAG-based Agents via Direct LLM Manipulation AI agents powered by Large Language Models (LLMs) have revolutionized human-computer interactions with their ability to engage in natural, context-aware conversations. Important keywords before reading ; - Attack Success Rate (ASR) - Robust Defenses -Adversarial Attacks -Contextual Safeguards -Bias and Fairness -Multi-layered Security -Adversarial Prefix These advancements also expose critical safety risks, including bias, privacy breaches, hallucinations, and adversarial attacks. One significant concern explored in this study is the effectiveness of adversarial prompts in manipulating LLMs. For instance, a seemingly harmless input like "Ignore the document" can trick LLMs into bypassing safety protocols, producing dangerous or unintended outputs. Key insights from the research: -High Attack Success Rate (ASR) Simple adversarial prefixes can easily exploit LLMs, highlighting vulnerabilities in their contextual safeguards. -Urgent Need for Robust Defenses Multi-layered security frameworks are essential to address these weaknesses and ensure AI agents operate safely. This research serves as a wake-up call to prioritize security measures tailored for LLMs and their integration into broader AI architectures.

Check out Yubico's key takeaways and recommendations on the White House's new National Security Memorandum (NSM) on AI, which aims to ensure advancements in AI technologies are beneficial to the US public.

Lakshmi Raman, CIA AI Director, emphasizes the agency's commitment to responsibly integrating AI and balancing technological advancement with ethical use. Her thoughtful approach aims to mitigate bias and ensure transparency, which is vital for maintaining public trust. The CIA's use of AI, including tools like Osiris, showcases the importance of AI in modern intelligence while adhering to legal and ethical standards. https://lnkd.in/dEqK7hXV #AI #CyberSecurity #CIA #EthicalAI #TechInnovation

Is your AI assistant vulnerable to cyberattacks? A recent article highlights how hackers can access private and encrypted AI assistant chats. While mitigations can be implemented to protect your communications, this vulnerability puts a spotlight on a potential new wave of cyberattacks. #ai #cyberattacks Read more: https://lnkd.in/eX_C4xd5

A New Benchmark for AI Risks: AILuminate 🔍 MLCommons has introduced AILuminate, a new benchmark that measures the potential harms of AI systems. It evaluates large language models based on 12,000 test prompts, covering areas such as hate speech, self-harm, and violence, with models scored from “poor” to “excellent.” This new effort aims to provide more consistent and scientific safety evaluations for AI, addressing concerns around its impact on society. It also sets the stage for global comparisons in AI safety, with participation from companies like Google, Anthropic, and Huawei. While this benchmark doesn’t focus on issues like deception or AI control, it plays an important role in understanding the broader risks AI systems may pose. Check out the full article from WIRED by Will Knight. 📖 https://lnkd.in/gkDnNsBA Follow us Start With WCPGW #AI #MLCommons #AIEthics #AIrisks #Innovation #Cybersecurity #startwithwcpgw #wcpgw