Scoping an AI Project: The Data, The Challenges, and The Black Box

April 3, 2017

Prerequisite: None

Jana Eggers


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IT and software dev projects were notoriously late and bloated. It isn't because we in the industry are idiots, incapable of sticking to schedules and scope, but rather because what we do is complex and we had to build tools and processes to support what we are doing. Now, along comes AI, and so much of the progress in delivering on time and on budget doesn't quite fit: AI projects are as amorphous as AI itself. In this session, I'm going to share my lessons learned after working over 30 years across research and industry in AI and software. I'll cover:

  • How to know if you have a problem that fits AI and machine learning
  • What's different about AI projects compared to other projects
  • Why data matters more for AI
  • Defining your goals, while you are searching for them
  • Overcoming the black box

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TDWI Accelerate Boston

The Boston Marriott® Copley Place
Boston, MA
April 3–5


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