You don't need AI; You need to know what your data is.
Speaker: Jade Abbott
Track: Data Science
93% of data science projects never make it into production (MIT Sloan Management Review). Many of us in the field of AI feel the impact of this - the sheer futility of all our efforts.
First we're going to talk about how we ended up in this mess: Spoiler Alert: We were misled. Next, we're going to figure out how to get OUT of it.
It's time to put down those neural networks, and pick up some data governance tools. It's time to stop hiring data scientists and instead hire data engineers. Join me on a journey to go back and rework some of the foundations so that our Data Science efforts can begin to make impact.
Audience: Anyone who works in data science or runs a data science team
What will they get out of it:
- Increased Skepticism on what the tech zeitgeist proposes
- A list of many of the practices we follow in Data Science which are ill advised
- What we can change to ensure we actually make an impact