In our modern information society, people need to manage ever-increasing numbers of personal devices and conduct more of their work and activities online, often making use of heterogeneous services. The amount of information to be processed by each individual is constantly growing, making it increasingly difficult to control, channel, share and make constructive use of it. To mitigate this, computing needs to become much more human-centered, e.g. by presenting personalised information to users and by respecting personal preferences in controlling multiple devices or invoking various services. Appropriate representation of the semantics of the information and functionality of devices and services will be critical to such personalised computing. Symbolic artificial intelligence (AI) techniques provide the method of choice for the required semantic representation and reasoning capabilities. The challenge for symbolic AI is to be able to support large-scale, distributed, dynamic knowledge bases enabling highly adaptive and evolving systems. AI must also look to specific application contexts and develop real-world solutions for problems in those domains. Below, we present some examples of such application contexts.
& Hitzler, P.
(2006). A Semantic Future for AI. IEEE Intelligent Systems, 21, 8-9.