Practical AI Machine learning at small organizations
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Jan 17, 2023 Kirsten Lum, Co-founder and CPO of Storytellers AI, shares her insights on the unique challenges small organizations face in implementing machine learning. She highlights that underutilization often stems from mismanagement, not a lack of data. Kirsten discusses the importance of adaptable data scientists and effective project management in driving successful ML practices. Additionally, she emphasizes the shift towards valuing real-world outcomes over mere model accuracy, advocating for a cultural change in data-driven decision-making.
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Be a Generalist
- Data scientists at smaller companies must be generalists, handling diverse tasks.
- Focus on practical application across the ML workflow, not deep specialization.
Project Management for Data Science
- Develop strong project management skills and use a clear framework.
- Prioritize delivering multiple impactful models over perfecting a single one.
Prioritization and Communication
- Focus on delivering impactful results to avoid becoming an Excel replacement.
- Use clear prioritization frameworks and communicate cost trade-offs with management.