Hugo Liu and Push Singh.

Graphical visualization has demonstrated enormous power in helping people to understand complexity in many branches of science. But, curiously, AI has been slow to pick up on the power of visualization. Alar is a visualization system intended to help people understand and control symbolic inference. Alar presents dynamically controllable node-and-arc graphs of concepts, and of assertions both supplied to the system and inferred. Alar is useful in quality assurance of knowledge bases (finding false, vague, or misleading statements; or missing assertions). It is also useful in tuning parameters of inference, especially how "liberal vs. conservative" the inference is Figure 1. An Alar visualization, centered on the assertion (trading off the desire to maximize the power of inference versus the risk of making incorrect inferences). We present "Orange is a food". Inferred assertions (green) use related a typical scenario of using Alar to debug a knowledge base.

Since the expert systems movement of the 1980s and 1990s, - Joint inference between expert knowledge and general AI has had the dream of reproducing expert behavior in specialized Commonsense background knowledge; domains of knowledge, such as medicine or engineering, - Efficient inference, both forward and backward, of plausible by collecting knowledge from human experts. But assertions. the first generations of expert systems suffered from two problems -- first, the difficulty of knowledge engineering

The 2000 Association of Computing Machinery Conference on Intelligent User Interfaces (IUI -- 2000) was held in New Orleans, Louisiana, from 9-12 January. This conference occupies the currently hot area that lies midway between the traditional fields of AI and computer-human interaction (CHI). For AI practitioners, this conference represents a good venue for learning about both how to design user interfaces for AI applications and how to use AI techniques to improve the user experience with more conventional applications. This year's conference drew the largest audience yet for an IUI conference, but the conference still remains at a manageable, single-track size. A wide range of high-quality presentations, tutorials, demonstrations, and invited speakers provided a bridge between the AI and CHI communities.