Danielle Pease’s Post

Everyone's jumping on the AI hype train, but are we considering all the implications? 🤔 AI, especially Large Language Models (LLMs), are revolutionizing auditing. They're boosting efficiency, enhancing data analysis, and even giving junior team members a 6-year experience boost overnight! 🚀 At Validis, we prioritize a robust approach to LLM use, focusing on the critical triad: ✅ Privacy: Encrypt and anonymize data before feeding it to LLMs. ✅ Security: Implement stringent cybersecurity measures and access controls. ✅ Data Quality: Curate high-quality datasets and maintain human oversight. But this is just a high-level overview. Our CTO, Andrew Wardle, has written a quick guide highlighting the challenges and solutions for each of these aspects. Don't let the AI revolution catch you off guard – stay informed and prepared! 💡 Read the full guide 'The Auditor’s AI Triple Threat: Privacy, Security, and Data Quality in the era of LLMs': [link in the comments] #BlogPost #AI #Auditing #DataPrivacy #Cybersecurity #DataQuality #ValidisInsights

Great insight from our CTO Andrew Wardle Don't let the AI revolution catch you off guard! Take a look at the recent Validis blog for a breakdown of the Auditor's AI Triple Threat: Privacy, Security & Data Quality #AI #Auditing #DataPrivacy #CyberSecurity #DataQuality #Validis

🚨 Why AI needs HUMAN OVERSIGHT in cybersecurity 🧠 👋 Imagine your cybersecurity systems running on AI that detects threats before they even happen. Pretty futuristic and cool, right? But here’s the thing—without human oversight, AI can also make some pretty terrifying decisions. 🤯 Here’s a real issue: 🔍 AI bias in threat detection: AI might flag a harmless action because it "learned" from biased data. No system is perfect without human guidance. 💡 My take: AI is powerful, but ethical frameworks and governance are the glue that ensures AI decisions don’t put your company at risk. Remember that technology serves us best when we stay in control. 🔑 Key thought: AI can help automate security, but it can’t replace the need for ethical judgment and strong governance. How are you making sure your AI tools stay ethical? #aigovernance #ethicalai #aibias

🔐 As we integrate AI into our systems, we MUST recognize the critical role of cybersecurity in safeguarding our innovations. Here are some key points from my latest talk on why AI cannot be implemented without robust cybersecurity measures (special shoutout to Breaking Barriers Women in CyberSecurity (BBWIC) Foundation for hosting the talk): 🔍 Attack Vectors: Data Poisoning: Malicious actors can manipulate training data to compromise model integrity. Model Theft: Unauthorized extraction of AI models can lead to significant intellectual property loss. Adversarial Attacks: Attackers can exploit vulnerabilities in AI systems to mislead or manipulate model outcomes. 🛡️ Mitigation Strategies: Ensemble Modeling: Combining multiple models can enhance resilience against attacks by diversifying decision-making processes. Access Controls: Implementing strict access management ensures that only authorized personnel can interact with sensitive data and models. Continuous Monitoring: Regularly auditing AI systems for vulnerabilities is crucial to preemptively identify and address threats. ⚖️ Ethical Considerations: Balancing innovation with responsibility is vital. Organizations must prioritize ethical practices in AI development to ensure trust and accountability. The future of AI is bright, but it must be built on a foundation of security. Let’s work together to ensure our AI implementations are not just innovative but secure and ethical! ---------------------- Learned something from by deck? Comment below :) Repost ♻️ Follow ➕ #cyber #ai #cyberandai #cybersecurity #data

I think it’s safe to say AI has embedded itself into nearly every aspect of our daily lives at this point. We use it to get where we’re going, to decide what to watch next, and maybe even to be more productive at work. But AI is still scary for a lot of people. What is the end goal? Will it replace humans? Is it dangerous? And the most terrifying question of all: Where does all the data go? As a CISO, it’s my job to keep any and all data in my care safe, secure, and private. How do I do that? The short answer is by creating — and enforcing — policies to keep the data vault locked (and the keys out of reach). When it comes to AI and data security, there are a lot of questions to ask — and answer. So, I sat down and tackled some of our most frequently asked questions for the latest Eleos blog post. Questions like: - When it comes to AI, what are the main security concerns? And why do you need a CISO to address them? - Is it ethical to utilize AI for healthcare documentation, behavioral or otherwise? - What’s the lowdown on all the regulatory certifications Eleos has earned? How are they different, and why do they matter? Get the answers to those questions — and more — in my full article: https://lnkd.in/eyy2c56W And if you want to geek out on data security even more, check out the Eleos Health Trust Center: https://trust.eleos.health #AI #cybersecurity #dataprivacy

We couldn't agree more, and we couldn't have said it better, Raz Karmi. Peep Raz's post below, and click on over to the link in comments to read the full post. #AISecurity #HealthcareAI #BehavioralHealthAI

Watch Dr. Srdan Dzombeta, EY EMEIA and EY Europe West Cybersecurity Leader, and I, as we delve into the transformative power of AI, as its enhancing efficiency and driving innovation in public services. From crime data analysis to optimizing healthcare resources, AI is making a significant impact, however, not without its challenges. We discuss the importance of bridging the skills gap with AI and ensuring ethical, unbiased AI deployment. Watch the full video to discover how AI is revolutionizing the government & infrastructure industry.  #AI #GovernmentInnovation #Cybersecurity

🔒 Did you know that data feudalism is becoming a growing threat in AI models? AI and machine learning security expert Gary McGraw discusses the implications in Decipher's latest article. #cybersecurity #dataprivacy #AIsecurity In this insightful piece, Gary McGraw dives into the concept of data feudalism within LLM foundation models and its security implications. He also explores whether narrowly focused models can help mitigate these concerns. Here are the key takeaways: 🔎 Data feudalism refers to the concentration of data and power in a few AI models, limiting access and control over valuable information. 🔐 This concentration poses significant security risks, including data breaches, bias, and illicit use of personal information. 🛡️ Narrowly focused models that specialize in specific tasks could offer a potential solution to reduce the impact of data feudalism. 💡 McGraw suggests that regulatory intervention may also be necessary to address these emerging challenges. As AI models continue to evolve, understanding and addressing data feudalism is vital to protect data privacy and ensure the responsible use of AI. What are your thoughts on this issue? Share your insights and join the discussion! #AIsecurity #dataprivacy #CybersecurityDiscussion

When we talk about AI compliance, we're not just discussing regulations—we're defining the principles that will guide the future of technology. 🛡️🤖 Prioritizing security and privacy in AI development ensures that we are not only advancing but doing so responsibly. This commitment to ethical AI deployment sets the standard for innovation, ensuring that we harness the power of AI without compromising the fundamental values of trust and integrity. As leaders in tech and business, how are you embedding ethical principles in your AI initiatives? Let's discuss the steps we're taking to ensure our innovations are both groundbreaking and responsible. #AICompliance #EthicalAI #DataPrivacy #CyberSecurity #ResponsibleInnovation #TrustInTech #AI #TechnologyLeadership #DigitalEthics #FutureOfTech

🌟 Navigating the New Terrain of AI Security with NIST's Groundbreaking Insights With NIST's latest report, we're witnessing a paradigm shift in our approach to AI security. It's not just about safeguarding data; it's about understanding and mitigating the potential for abuse in Generative AI systems. 🔍 This report illuminates how Generative AI can be exploited, adding a new dimension to the traditional CIA triad. These AI systems, capable of generating new content, could be manipulated to produce misleading or harmful information, challenging the very integrity and authenticity we rely on in the digital world. 💡 What sets this document apart is its clarity in navigating these complex issues. It categorizes attacks by their impact, providing a lens to view AI threats not just through data breaches, but as potential avenues for spreading misinformation or unauthorized content creation. 📚 As a cybersecurity and GRC expert, I see this report as a vital tool for anyone involved in AI. It's a clarion call for us to evolve our security strategies and policies to address these advanced threats, while still upholding the core principles of confidentiality, integrity, and availability. 🤝 Let’s collaborate on understanding and fortifying our AI systems against these novel threats. Whether you are a policy maker, a data scientist, or simply intrigued by AI security, I welcome your thoughts and insights on this critical topic. #CyberSecurity #AI #NIST #Governance #RiskManagement