By Topic

Dealing with ghosts: Managing the user experience of autonomic computing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Russell, D.M. ; IBM Research Division, Almaden Research Center, 650 Harry Road, San Jose, California 95120, USA ; Maglio, P.P. ; Dordick, R. ; Neti, C.

Although the goal of autonomic computing is to make systems that work continuously, robustly, and simply, no one imagines that people can be excluded entirely. Whether it is end-users getting their jobs done by interacting with autonomic systems or system administrators maintaining, monitoring, and debugging large-scale systems with autonomic components, humans will always be part of the computational process. As autonomic systems become part of the computing infrastructure, new demands will be placed on all users. How do users understand what autonomic systems are trying to do? How should systems portray themselves to users? How can we design the experience of autonomic computing to amplify user capabilities? This paper presents an analysis of the user experience (UE) challenges of autonomic computing and discusses design requirements for user interaction. Our main point is that autonomic computing makes effective design of the user experience even more challenging and critical than it is now. This is because autonomic actions taken by the system must be understandable by the user, and capable of review, revision, and alteration. Because such actions are often made autonomously, this places a heavy burden on the ability of the system to explain what it is doing and why.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Systems Journal  (Volume:42 ,  Issue: 1 )