Challenges of context-awareness
Via Mike Blackstock: Too Much Information ACM Queue vol. 4, no. 6 - July/August 2006 by Jim Christensen, Jeremy Sussman, Stephen Levy, William E. Bennett, Tracee Vetting Wolf, Wendy A. Kellogg, IBM Research. The article tackles context-awareness and its key challenges, with two examples of application (in new communication services that include the convergence of VoIP and traditional information technology). It starts by presenting the purpose of context-awareness and its relative difficulties:
"While the dream of intelligent devices has been alive for some time in the computer science community, it has not yet had a profound effect on the applications and services we use to get our jobs done. Why not? The simple answer is because it is hard to do well - or even well enough. The gap between what technology can "understand" as context and how people understand context is significant. Indeed, some critics have asserted that context-aware computing makes a fundamental error in trying to remove the human from the control loop in creating intelligent autonomous devices.2 A different tactic is to capture context but render its results unto humans to decide what actions to take"
The it presents the two applications ("The first, called Grapevine, helps a person communicate with another individual using an aggregated and filtered set of contextual information. The second, the IBM Rendezvous Service, helps people meet and talk on the telephone") and then draws some conclusions about their use. Here are some excerpts of the results I found pertinent to what I am doing:
A substantial semantic gap exists between the information that low-level sensors and programs can detect and the high-level ability and willingness of a person to communicate with someone else. What computer scientists commonly call context often has more to do with technology than with work situations, people, or frames of mind. While low-level information is useful, it is only a rough indicator of a user's social context. Such ambiguity can be socially useful; nevertheless, care must be taken in presenting and labeling sensor data in the interface. (...) Working out the problems and promise of context-aware applications and services depends on a complex interplay in a moving landscape of technical, organizational, social, and cultural factors. These include what is technically feasible in terms of the kinds of contextual information available; what is practically feasible in terms of assumptions that can be made about the distribution and nature of devices, bandwidth, and cost; what is possible within the constraints of our imaginations; and what will be perceived by users as valuable, as well as socially and culturally appropriate. For this reason, experience with deploying real applications and services at a realistic scale is essential.
Why do I blog this? because it clarifies the gap between context-awareness promises and current practices.