Making AI algorithms show their work, an expansion to Google's AI Ethics research team, and more!

Last Week in AI #116

Mini Briefs

Making AI algorithms show their work

One of the main draws of machine learning algorithms is their ability to perform tasks without being explicitly programmed with rules to accomplish those tasks. In the process of learning to perform those tasks, these algorithms notice patterns and develop "rules" of their own, however, and the developers of those algorithms don't always know what those rules are. Cold Spring Harbor Laboratory Assistant Professor Peter Koo, who developed a neural network to look for patterns in RNA that increase a protein's ability to bind to them, wanted to know whether his algorithm was focusing on short sequences of RNA letters or secondary characteristics of RNA strands. Koo and his team developed a method called Global Importance Analysis to test which rules their algorithm generated to make its predictions.

Google Plans to Double AI Ethics Research Staff

After a number of departures and re-organizations, Google's AI Ethics research team has found itself at the center of a great deal of coverage. These same occurrences have also caused Google to lose credibility in the area and frayed its relationship with external groups. VP of Engineering Marian Croak (pictured), who was recently tapped to lead the team, has said that the team will double its size to 200 members. CEO Sundar Pichai has also said the team will receive a boost to its operating budget.


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