Daniel Faggella is Head of Research at Emerj. Called upon by the United Nations, World Bank, INTERPOL, and leading enterprises, Daniel is a globally sought-after expert on the competitive strategy implications of AI for business and government leaders. Companies and cities all over world are experimenting with using artificial intelligence to reduce and prevent crime, and to more quickly respond to crimes in progress. The ideas behind many of these projects is that crimes are relatively predictable; it just requires being able to sort through a massive volume of data to find patterns that are useful to law enforcement. This kind of data analysis was technologically impossible a few decades ago, but the hope is that recent developments in machine learning are up to the task.

Well, what do you know, some science-fiction media and literature are starting to become realities now. If you have ever seen the movie "Minority Report" then your excitement has probably doubled. An artificial intelligence (AI) that can predict and detect crime is now in the works, by none other than Japan, of all countries. Despite the crime rate in Japan being relatively low compared to countries like the U.S. or U.K., the Asian country's military and police are still intent on developing such a technology. They also intend to apply it against maritime vessels which could pose a security threat to Japan.

Companies are using AI to prevent and detect everything from routine employee theft to insider trading. Many banks and large corporations employ artificial intelligence to detect and prevent fraud and money laundering. Social media companies use machine learning to block illicit content such as child pornography. Businesses are constantly experimenting with new ways to use artificial intelligence for better risk management and faster, more responsive fraud detection -- and even to predict and prevent crimes. While today's basic technology is not necessarily revolutionary, the algorithms it uses and the results they can produce are.

Twitter has repeatedly proven itself as an invaluable platform for information sharing during social crises. Now new research has shown its ability to detect serious incidents much faster than police reports -- up to an hour faster, in fact. By analysing data from the London riots in 2011, researchers at Cardiff University showed that computer systems could automatically scan through Twitter and identify potentially dangerous occurrences, such as windows being broken and cars being set on fire, long before they were reported to the Metropolitan Police Service. The system could also identify Twitter rumors about where riots were likely to take place, as well real-time information about areas where people were gathering. The researchers used a series of machine-learning algorithms to analyze each of the tweets from the dataset of 1.6 million tweets, taking into account a number of key features such as the time they were posted, the location where they were posted and the content of the tweet itself.