About this episode

Emanuel Rose discusses the challenges and implications of local AI models with cognitive scientist Arshavir Blackwell.

Episode Overview: As AI becomes more powerful and more accessible, many leaders are discovering that the biggest challenge isn't the technology itself—it's understanding where it fits, how it works, and what risks come with it. In this episode of Marketing in the Age of AI, Emanuel Rose sits down with cognitive scientist and AI researcher Arshavir Blackwell to explore local AI models, mechanistic interpretability, workflow integration, brand voice consistency, compliance challenges, and the growing problem of "fluency theater." The conversation examines why AI-generated content can sound convincing while still being wrong, why local models may become increasingly important, and how organizations can move beyond experimentation toward practical implementation. What You'll Learn: ✅ What mechanistic interpretability reveals about AI systems ✅ Why testing AI outputs alone isn't enough ✅ The advantages of local AI models versus cloud-based tools ✅ How local models can improve brand voice consistency ✅ Security and privacy considerations when using AI ✅ Why many AI projects fail inside organizations ✅ The importance of workflow integration and process mapping ✅ What…

People in this episode

Host: Emanuel Rose

Guest: Arshavir Blackwell

Topics covered

• local AI models
• mechanistic interpretability
• workflow integration
• brand voice consistency
• compliance challenges
• fluency theater
• AI-generated content

Keywords

• AI technology
• local models
• content generation
• security
• privacy
• institutional knowledge
• workflow mapping

Mentioned in this episode

Organizations: UC San Diego

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