Artificial intelligence algorithms are designed to make decisions, often using real-time data they are unlike passive machines that are capable only of machanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data with massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decision making.
AI systems have the ability to learn and adapt as they make decisions. In the transportation area for example semi-autonomous vechicle have tools that let drivers and vehicles know about upcoming congestion, potholes, highway construction or other vehicles on the road without human involvement and the entire corpus of their achieved "experience" is immediately and fully transferable to other similarly configured vehicles their advanced algorithms, sensors and cameras incorporate experience in current operations and use dashboards and visual displays to present information in real time human drivers are able to make sense of ongoing traffic and vehicular conditions and in the case of fully autonomous vehicular coditions and in the case of fully autonomous vehicles, advanced systems can completely control the car or truck and make all the navigational decisions.
A prominent example of this is taking place in stock exchanges, where high-frequency trading by machines has replaced much of human decision making. People submit buy and sell orders, and computers match them in the blink of an eye without human intervention. Machines can spot trading inefficiencies or market differentials on a very small scale and execute trades that make money according to investor instructions. Powered in some places by advanced computing, these tools have much greater capacities for storing information because of their emphasis not on a zero or a one, but on “quantum bits” that can store multiple values in each location. Fraud detection represents another way AI is helpful in financial systems. It sometimes is difficult to discern fraudulent activities in large organizations, but AI can identify abnormalities, outliers, or deviant cases requiring additional investigation. That helps managers find problems early in the cycle, before they reach dangerous levels.
The big data analytics associated with AI will profoundly affect intelligence analysis, as massive amounts of data are sifted in near real time—if not eventually in real time—thereby providing commanders and their staffs a level of intelligence analysis and productivity heretofore unseen. Command and control will similarly be affected as human commanders delegate certain routine, and in special circumstances, key decisions to AI platforms, reducing dramatically the time associated with the decision and subsequent action. In the end, warfare is a time competitive process, where the side able to decide the fastest and move most quickly to execution will generally prevail. Indeed, artificially intelligent intelligence systems, tied to AI-assisted command and control systems, can move decision support and decision making to a speed vastly superior to the speeds of the traditional means of waging war. So fast will be this process, especially if coupled to automatic decisions to launch artificially intelligent autonomous weapons systems capable of lethal outcomes, that a new term has been coined specifically to embrace the speed at which war will be waged hyperwar.
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