In very early January, my newsroom, the Overseas Consortium of Investigative Journalists, and Re’s Stanford lab launched a collaboration that seeks to improve the investigative reporting procedure. To honor the “nothing unnecessarily fancy” principle, it is called by us machine Learning for Investigations.
For journalists, the selling point of collaborating with academics is twofold: usage of tools and methods that may assist our reporting, while the lack of commercial function when you look at the college environment. For academics, the appeal may be the “real globe” issues and datasets journalists bring towards the dining dining table and, possibly, brand brand new technical challenges.
Listed below are classes we learned up to now within our partnership:
Choose a lab that is ai “real world” applications history.
Chris Rй’s lab, as an example, is a component of the consortium of federal federal government and personal sector organizations that developed a collection of tools built to “light up” the black internet. Making use of device learning, police force agencies had the ability to draw out and visualize information — sometimes hidden inside pictures — that helped them pursue individual trafficking companies that thrive in the Internet. “Make certain you can find incentives on both edges.” の続きを読む