Automated knowledge-acquisition systems have focused on embedding a cognitive model of a key knowledge worker in their software that allows the system to acquire a knowledge base by interviewing domain experts just as the knowledge worker would. Two sets of research questions arise: (1) What theories, strategies, and approaches will let the modeling process be facilitated; accelerated; and, possibly, automated? If automated knowledge-acquisition systems reduce the bottleneck associated with acquiring knowledge bases, how can the bottleneck of building the automated knowledge-acquisition system itself be broken? That is, humans are known to be subject to errors and cognitive biases in their judgment processes. How can an automated system critique and influence such biases in a positive fashion, what common patterns exist across applications, and can models of influencing behavior be described and standardized?
Knowledge engineering is the process of creating rules that apply to data in order to imitate the way a human thinks and approaches problems. A task and its solution are broken down to their structure, and based on that information, AI determines how the solution was reached. Often, a library of problem-solving methods and knowledge to solve a particular set of problems is fed into a system as raw data. Then, the system can diagnose the problem and find the solution without further human input. The result can be used as a self-help troubleshooting software, or as a support module to a human agent.
If there is a place where human knowledge in its all-out complexity can be argued, learned and shared, it must be, without any doubt, the University. Universities can be understood not just as a place where this knowledge is passed on to new young generations but a place where knowledge is indeed created. A place which surpasses business and money-making-driven schemes, and rather embrassing everything that has to do with knowledge, and where knowledge can be born and transmitted. From politics and arts, history and science, architecture and education, all human knowledge is well preserved and developed within the different colleges that makes up an University. Although all branches are crucial for a healthy growth of the society itself, there are few of them that are getting higher demand on the outside world: the likes of IT and computing related.