Talking AI: Leveraging LLMs for Cultural Insights with Ramona Daniel
In this Talking AI episode, Ray Poynter welcomes Ramona Daniel—an independent cultural insights consultant with over 25 years in research—to discuss how generative AI has transformed her workflow. Ramona recounts her journey from telephone interviewer at Ipsos to leading a 79-market media study at Group M, and finally to striking out on her own in 2024. Facing the challenges of solo consulting, she turned to LLMs to replicate the role of missing team members, ask critical questions, and uncover patterns in cross-cultural data.
What You'll Learn
Ramona’s AI Onboarding Story
Why she began experimenting with ChatGPT, Claude, Gemini, DeepSeek, Copala, and Perplexity
How she evaluated outputs, compared platforms, and found which tools delivered the best insights
Practical AI Experiments
Turning raw PCA outputs from jamovi into interpretable narratives via ChatGPT or Claude
Using Perplexity as a natural-language search engine instead of traditional keyword Google searches
Converting dense research papers into audio “podcasts” with NotebookLM to quickly grasp key themes and cultural implications
Lessons Learned & Pitfalls to Avoid
Why off-the-shelf LLM outputs can feel “middle of the road” and how to apply critical thinking to interrogate them
Which features (e.g., ChatGPT’s voice mode, Claude’s voice, Gemini’s latest modules) fell short and why
The temptation to shortcut learning—how to ensure AI tools complement rather than replace your own expertise
Opportunities & Threats for Cultural Research
How AI’s pattern-recognition capabilities can surface unseen cultural signals beyond English-only sources
Inherent biases in LLM training data and the importance of human validation when interpreting cultural context
Actionable Tips for Beginners
Experiment liberally: press buttons, type queries, see what happens, and fail fast
Don’t lock into one platform—test multiple LLMs (ChatGPT, Claude, Gemini, etc.) to find which voice aligns with your needs
Shape AI workflows to fit your unique process, rather than expecting plug-and-play solutions
Key Takeaways
AI as a Collaborative Partner—Use LLMs to fill gaps in your network, challenge your thinking, and highlight hidden data patterns, but always apply critical judgment.
Multimodal & Multilingual Research—Tools like NotebookLM let you transform PDFs, research papers, and non-English sources into digestible formats, expanding your cultural horizon.
Continuous Experimentation—AI platforms evolve rapidly; regularly revisit and compare ChatGPT, Claude, Gemini, Perplexity, and emerging tools to stay ahead.
Ireland