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KMi Seminars
Explainable Systems
This event took place on Monday 09 May 2005 at 10:00

 
Dr. Paulo Pinheiro da Silva

When most current applications return answers, many users do not know what information sources were used, when they were updated, how reliable the source was, or what information was looked up versus derived. Many users also do not know how answers were derived. In this talk, we first show examples of explanations helping users to understand and trust system answers. Then we introduce the Inference Web (IW), our solution that enables explainable systems. IW aims to take opaque query answers and make the answers more transparent by providing infrastructure for presenting and managing explanations. The explanations include information concerning where answers came from (knowledge provenance) and how they were derived (or retrieved). The infrastructure includes:
  • IWBase: an extensible web-based registry containing details
    about information sources, reasoners, languages, and rewrite rules;

  • PML: the Proof Markup Language, an interlingua representation
    for justifications of results produced by software systems; and

  • a comprehensive tool suite for browsing, checking and
    abstracting proofs, and explaining answers through dialogues with users.
Finally, we report on current Inference Web applications including details about two of these applications: explaining extraction as inference in support of IBM's Unstructured Information Management Architecture (UIMA) effort, and explaining task processing as inference in support of DARPA PAL's CALO personal assistant project.

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KMi Seminars
 

Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.