Navigating Data's Next Great Shift
summary
Core claim: messy pipelines remain the big bottleneck — clean data as foundation — while teams that invest in hygiene unlock GenAI and vision models faster. Concrete wins include building a job‑matching engine to help veterans that scales and generates revenue, and rapid COVID efforts like setting up testing centers and feeding the Co‑Tracking datasets. Proposed practices: treat data like a loved one for privacy and security, put real people at the table, join public service channels such as US Digital Response or Code for America, and rebuild norms of cross‑company sharing.
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chapters (11)
- 0:00Data at scale
- 1:07Data infrastructure
- 3:37Foundational problems
- 5:41Generative AI impact
- 8:04Treating data like loved ones' information
- 10:33AI problem selection
- 14:05Public service skills
- 19:01Data scientists as Spock
- 23:13Community in data science
- 24:18AI collaboration
- 26:45Closing remarks
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