The above is one of many case studies that will be provided in subsequent chapters. In each, the reader will be shown how data mining technologies are being used by innovative investigators, criminalists, and analysts to detect and deter crime and terrorism. These case studies will demonstrate first-hand how link analysis, software agents, text mining, neural networks, and machine-learning are being used for everything from signature detection of illegal drugs to alerts of bio-terrorist attacks. As we said in the beginning of the chapter, the world has changed and so have the weapons, expanding the application of AI technologies for detecting and deterring criminals.
In the aftermath of 9/11, the director of the FBI, Robert S. Mueller, acknowledged that the bureau might have prevented the attacks. "Putting all the pieces together, who is to say?" Mueller said, noting that warning signs amounted to "snippets in a veritable river of information." As part of a major reorganization, the director announced, "The Bureau needs to do a better job of analyzing data and put prevention ahead of all else." With that the FBI took a new strategic focus and a key near-term action to "substantially enhance analytical capabilities with personnel and technology and expand the use of data mining, financial record analysis, and communications analysis to combat terrorism." The future, it appears, has arrived.