Facebook wants to use artificial intelligence to automatically recognize and block offensive content like videos contain violent images. The news comes from Joaquin Candle head of machine learning Facebook. The goal, then, is to use artificial intelligence algorithms to eradicate the phenomenon of content inappropriate, including false news, phenomena for which the social network is over, in recent months, accused by many.
Until now, in fact, Facebook has always relied on its users and their reports to fight the scourge of inappropriate content that are then verified by a team of employees of the social network. But now, Facebook is increasingly rely artificial intelligence to detect inappropriate as nude photos, violence and everything that goes against the policy of the social network. As reported by Reuters who spread the news, Facebook had already used a similar system last June to capture video of extremists but now would be testing the application of the algorithms within Live Video that users use to transmit Venetians live.
Joaquin candle shows that the use of artificial intelligence for these purposes involves two main challenges. The first that the automatic intervention of the social network for blocking inappropriate content must be [19459003quickandimmediate] . The algorithm must therefore recognize quickly what works and what does not fit. The second challenge, and perhaps the most important is that the algorithm individuals with Precision content to block, that is, those would also be blocked by human intervention.
The risk, in fact, is that the algorithm also blocks content, however, adequate. The still, objective fact, is that to stop the fast-growing phenomena related to false news and violence, the social network will increasingly rely on to ‘ Artificial Intelligence to respond to the problems relatively quickly. These algorithms, however, must be properly adjusted for not going to stop, however, also contained in fact correct. An ambitious challenge but if conducted on track could solve many of the problems of the last times of the social network.