Without communication, machine learning for data science goes nowhere

When looking at machine learning for data science, the important question to ask of the data is the same one 2-year-olds persistently ask their parents: Why? Although a simple question, it is not asked or answered often enough as industry goes full-tilt toward machine learning and artificial intelligence (AI), according to Milind Kamkolkar, chief data officer at French pharmaceutical company Sanofi, speaking at last week's MIT Chief Data Officer and Information Quality Symposium. "There's a lot of stuff missing in data science today," Kamkolkar said, suggesting one of the main things missing in machine learning for data science is communication. Teams must be able to convey what predictive results mean and why they matter, he said. Now, more than ever, data analytics groups must get closer to the users of their products, Kamkolkar told attendees at the event's session on machine learning and advanced analytics.