The natural, artificial, and social domains of intelligence: a triune approach

A “triune approach” to the three main domains of intelligence is advocated. It would be the most cogent way to understand the uses and impact of artificial intelligence in its intrinsic relation with human nature and social structures. The enormous technological success of artificial intelligence and the widespread social applications, impinging both in individual lives and in multiple economic and social structures, are making necessary a reflection on the wider dynamics of intelligence, interconnecting the artificial information pathways with the natural information flows and the social structural substrates. As a telling instance, the traditional poor understanding and management of “social emotions” is dangerously amplified in today’s social networks, contributing to unrest, polarization, and widespread desocialization processes. In contemporary societies, the essential link between intelligence and life has to be plainly revealed as a counterpoint to the link between artificial intelligence and computation

Robust Processing of Natural Language

Previous approaches to robustness in natural language processing usually treat deviant input by relaxing grammatical constraints whenever a successful analysis cannot be provided by ``normal'' means. This schema implies, that error detection always comes prior to error handling, a behaviour which hardly can compete with its human model, where many erroneous situations are treated without even noticing them. The paper analyses the necessary preconditions for achieving a higher degree of robustness in natural language processing and suggests a quite different approach based on a procedure for structural disambiguation. It not only offers the possibility to cope with robustness issues in a more natural way but eventually might be suited to accommodate quite different aspects of robust behaviour within a single framework.Comment: 16 pages, LaTeX, uses pstricks.sty, pstricks.tex, pstricks.pro, pst-node.sty, pst-node.tex, pst-node.pro. To appear in: Proc. KI-95, 19th German Conference on Artificial Intelligence, Bielefeld (Germany), Lecture Notes in Computer Science, Springer 199