DataFramed #248 Effective Product Management for AI with Marily Nika, Gen AI Product Lead at Google Assistant
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Sep 30, 2024 In this engaging discussion, Marily Nika, Generative AI Product Lead at Google Assistant and founder of AI Product Academy, delves into the complexities of AI product management. She shares insights on the ethical considerations in using user data and the need for adaptability in a rapidly evolving field. The conversation highlights key skills for aspiring AI product managers and underscores the importance of balancing personalization with user privacy. Marily also discusses effective collaboration strategies and the challenges of transitioning AI models to real-world applications.
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AI PM vs Traditional PM
- AI product management differs from traditional product management due to the probabilistic nature of AI and the iterative experimentation it requires.
- Success in AI PM means validating hypotheses and pivoting based on results, not just user numbers.
AI Keyboard App Example
- Marily Nika describes a hypothetical keyboard app that learns from user behavior and improves its prediction capabilities.
- This example illustrates the iterative nature of AI product development and A/B testing.
Ethics in AI PM
- Always consider the ethical implications of AI products, asking "should we?" not just "can we?".
- Stay informed about AI regulations and prioritize user empathy and responsible data practices.