Cultural Challenges in Data Science

Cultural Challenges in Data Science

In her previous post, Technical Challenges in Data Science, Amanda Andrei discussed the need for technical vigilance and with experts Dr. Elizabeth Hohman, statistician and group leader within MITRE’s Department of Data Analytics, and Dr. Eric Bloedorn, senior principal artificial intelligence engineer. Tools and models, however carefully managed, tell, of course, only part of the story. Data scientists are people, and they and the tools they use reside within organizational cultures, which may require as much training as the data to hand.—Editor

Hand Models

Hand Models

How much fun are you going to have with Howard Gershen’s second post on counting and reasoning? Innumerable amounts. Don’t expect any new rules of thumb, but he does offer some insights where it really counts.—Editor

Down for the Count

Down for the Count

When I read Howard Gershen’s riff on counting with his fingers, what came to mind instantly was theory of mind in the way that I heard Alan Alda explain it at George Washington University as a guest speaker for the Smithsonian. We know that words and pictures work...
Managing Language Chaos

Managing Language Chaos

Echoing Lewis Carroll, a colleague reminded me once that words mean whatever we choose to have them mean—a practice that might work if we lived in isolation from one another and if nothing that we said or did mattered. Alas, language, like personal devices, seems to...

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