AI & Security: The Model Is the Target
By Joel Leslie
Season 4, Episode 10
Duration: 00:27:57
Episode summary
AI security is no longer just about firewalls, passwords and patches. In this episode of Decoded: AI for Everyone, we explore why advanced AI systems are becoming strategic assets and why the model, the data it can see, the instructions it follows and the tools it can use all need to be protected. For frontier AI companies, the model itself may be the prize... the weights, training pipeline, safety methods and unreleased capabilities. But for most organisations, the risk is different. They may not own the model, but they may connect AI to internal documents, emails, workflows, customer records, policies, finance systems and decision processes. That is where the danger changes. The more useful an AI system becomes, the more valuable it may be to someone trying to misuse it. An attacker may not need to break every lock if they can manipulate the AI into using the access it already has. This episode looks at prompt injection, red team testing, hallucinations, silent failures, model security and why AI systems need an additional layer of assurance beyond normal software testing and cybersecurity. The useful habit is to ask three questions before connecting AI to anything important: What can it see? What can it do? What happens when it is wrong? Because the model is valuable because it can help. It is risky for the same reason. Show resources: Decoded-Podcast.com/resources/s4e10 More AI resources: PromptEngineeringCookbook.com
About Decoded: AI for Everyone
Decoded: AI for Everyone is Joel Leslie's non-technical podcast about artificial intelligence and its impact on work, creativity, decision-making, trust and everyday life. The series helps listeners understand AI without hype, jargon or fear, connecting practical examples to broader questions about technology, people and society.
Joel Leslie is an Australian AI, data and digital transformation leader specialising in safe AI adoption, AI governance, AI ethics and data governance.
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