Towards a "Perfect" Digital Assistant. Is a change in the personal computing paradigm in the offing?
In the late 80's the concept of "personal digital assistant" and "the knowledge navigator" were introduced. The PDA, however, was at best a set of applications: calendar, note pad, to do's and addresses, that worked well for the narrow percentage of people who are organized, schedule things anyway and can tolerate filling in forms.
The knowledge navigator was an imaginary Apple vision of what a PDA might be when it grew up: something that would actively blend awareness of personal and public data to provide support for the human operator. It could compare stats from papers and other sources, handle phone calls in the background all the while providing a conversational experience of engagement with its human.
Recently we've been looking at what it might take to bring the current state of information management tools away from their current application/form filling state and towards the vision of the knowledge navigator, or what we've been calling the "perfect digital assistant."
We are exploring the first part of this process towards the new PDA in a project called Jourknow between MIT and Southampton. Here, we're investigating different desktop models for data representation and storage. Fundamentally we have also been looking at new ways to capture the structure of information but in a form free way. We have then been exploring how this information can be enriched for retrieval by automatically associating it with what we can know about the context of the information at the time of capture - what we were doing; who we might be with; where we were; any applications/documents open. This project has very much captured on improving personal information management by improving capture and retrieval contexts. While we hope the approach is better than current ap/form PIM models, it is not the knowledge navigator. The active assistance component is missing.
In a new project, Idoru, we have just begun to look at how we might blend public data sources like rss feeds and other mineable Web resources, with ubiquitous sensor or data feeds, and these with our personal data in order to begin to see how this might be purposeable for active support: if our knowledge navigator is watching sources of data for things we care about, and also knows our schedule, can it find a whole in our schedule to alert us to an opportunity for a new gallery opening for instance, and then book the tickets on approval? Could it likewise, knowing we've been pulling all-nighters for a CHI deadline, recommend something we should have for dinner to help replenish our health?
In this talk, i will go over the work informing these projects and our findings to date, with an eye towards exploring with you shared interests and possible collaborations in this space.
Speaker Bio mc schraefel is a Senior Lecturer in Electronics and Computer Science at the University of Southampton where she leads the Interaction Theme in the Intelligence Agents and Multimedia Group. For the past year she has been on sabbatical at the University of Maryland and MIT as the first Web Science Research Initiative Fellow (http://webscience.org), working with Ben Shneiderman, Tim Berners-Lee, Jim Hendler, Danny Weitzner and David Karger to explore how/where user interaction research and semantic web technology research may blend to support new models for exploring web-scale information, metadata and provenance/policy information around that data.