Information and Causal Inputs

Information, in a broad sense, is simply processed, structured and organised data. It gives context to previously processed data and allows decision making to be made. For instance, a single consumer’s sale in a restaurant is data this becomes information when the company is able to pinpoint the highest or lowest priced dish. Decision making is based on previous decision data and knowledge of what works or doesn’t work. A business that can make informed decisions based on this sort of information is likely to thrive.

An information system is a tool that enables users to gain access to and process vast amounts of data over time. This is called continuous data processing (CDPC). CDPC allows users to build large and complex algorithms that can search through huge amounts of data and identify patterns. In essence this is what sets event-triggered or opt-in email campaigns apart from other marketing applications.

In the past, most telemarketing campaigns relied on pre-written mail shots or script that included multiple generic email messages. These scripts were called information processing scripts. The email messages would then perform a pre-determined set of generic actions such as opening, saving, opening with a confirmation link and so forth. However, as companies have started to realise the benefits of using artificial intelligence to process large amounts of data naturally, these artificial intelligence (AI) systems have been designed to act just like a human “bride” who is out to find a suitable partner. The scripts would act on pre-written generic emails and respond to customer’s queries and requests for more information.

Artificial intelligence systems are able to adapt to various situations and they use historical information, previous activity and “on-going” patterns of interaction to make inferences and form their own opinions. This may sound a lot like the theory of mental cooking where cookery enthusiasts can predict what will be eaten next based on past evidence about what foods go well with one another. The difference is that the cookery theory applies to the information processing stage of an artificial intelligent system. A good example of the application of this theory is the way many online search engines work.

Information may enter an online search engine via a user’s keystrokes, typed in text or by browsing a web page. Once the information has entered the search engine, it is stored and analyzed according to the different criteria specified by the user, all of which are stored and processed in the form of causal inputs (such as keywords used to search and categorize the site). For instance, the information in the above example could be used to categorize websites according to categories (such as pet grooming sites or dog training sites), which would in turn give rise to different web pages. In the case of the above example, the information-processing step in the information processing chain was triggered by typing in the keyword “pet grooming”, which was then passed on to the category list on the website, which was then in turn processed by a program that determined the best out of the available categories. This is a form of information processing in the form of an online causal input, and in fact all information processed in this fashion is a form of information processing.

Information is not neutral; it either comes from external stimuli such as the words typed into a search engine or the information gathered by the classification system for classification purposes in the above example. It can also come from internal sources such as the knowledge stored in the brain, which may be referred to as the information processing in the conscious mind. In essence, information is both a sensory and a cognitive information source, and in order for information to be usable and actionable it must be categorized and understood in terms of both sources.