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Dublin Tech Summit 2022 : Turning Theory into Practice : Cassie Kozyrkov, Google
Join Cassie Kozyrkov, Google, as she discusses the importance of writing, decision-making, and explainable AI in data science, emphasizing the need for skilled experts, diverse teams, and reliable systems to turn theory into practice.
- Data is an extension of writing, and assumptions are crucial when working with it.
- Better decision-makers are needed, and data should start with the decision-maker.
- Writing well is hard, and we need to focus on decision skills.
- We should embrace and lean into making better tools.
- Explainable AI is important, and machines sometimes produce garbage.
- It’s not about how clunky your typewriter is, but about how you use it.
- Magical thinking is not helpful in data science.
- We need people who are skilled experts specifically in areas like data science.
- Decision-making is a team sport that requires a diversity of skills.
- Data is memories, and we need to be more welcoming.
- Reality is not just about outputs, but about processes.
- Many organizations are trying to improve their data science.
- Reliability engineers are needed to keep systems running.
- We need to focus on decision skills.
- We should stop trying to come up with recipes and focus on capturing reality.
- We need people who can contribute in wonderful ways to projects.
- Program managers will need a whole cast of characters to succeed.
- AI and machine learning are different ways of writing down information.
- Writing is hard, and explainable AI is important.