Facial recognition software is most commonly known as a tool to help police identify a suspected criminal by using machine learning algorithms to analyze his or her face against a database of thousands or millions of other faces. The larger the database, with a greater variety of facial features, the smarter and more successful the software becomes – effectively learning from its mistakes to improve its accuracy.
Now, this type of artificial intelligence is starting to be used in fighting a specific but pervasive type of crime – illegal fishing. Rather than picking out faces, the software tracks the movement of fishing boats to root out illegal behavior. And soon, using a twist on facial recognition, it may be able to recognize when a boat’s haul includes endangered and protected fish.
The latest effort to use artificial intelligence to fight illegal fishing is coming from Virginia-based The Nature Conservancy (TNC), which launched a contest on Kaggle – a crowdsourcing site based in San Francisco that uses competitions to advance data science –earlier this week. TNC hopes the winning team will write software to identify specific species of fish. The program will run on cameras, called electronic monitors, which are installed on fishing boats and used for documenting the catch. The software will put a marker at each point in the video when a protected fish is hauled in. Inspectors, who currently spend up to six hours manually reviewing a single 10-hour fishing day, will then be able to go directly to those moments and check a fishing crew’s subsequent actions to determine whether they handled the bycatch legally – by making best efforts to return it to the sea unharmed.