improving intelligibility and control in ubicomp environments
DESCRIPTION
Talk at the first SIGCHI.be conference in Affligem at October 19, 2009.TRANSCRIPT
Improving Intelligibility and Control in Ubicomp Environments
Jo Vermeulen, Kris Luyten and Karin Coninx
Hasselt University – tUL – IBBTExpertise Centre for Digital Media
in tel li gi bil i ty:⋅ ⋅ ⋅ ⋅ ⋅ ⋅the quality or condition of being intelligible; capability of being understood
con trol:⋅to exercise restraint or direction over; dominate; command
Ubicomp?
Source: http://luci.ics.uci.edu/blog/archives/2009/02/6_words_16_grad.html
Why are intelligibility and control important?
HAL 9000 from “2001: A Space Odyssey” (1968)
Example: smart lighting application
See also: http://ailab.wsu.edu/mavhome/
Example: MavHome
“With inhabitant three, we noticed a new phenomenon in the course of our experimentation — the system did more training of the inhabitant than the inhabitant did to the system. There seemed to be a reluctance to give prompt feedback on the inhabitant end. On interview, the inhabitant said that they were learning to live in the dark because it was too bothersome to correct the system. This is probably human nature. We also observed a few fights between the system and the inhabitant over control that ultimately was won by the inhabitant when feedback caused the system to change behavior, but for a short duration the system caused some duress to the inhabitant—not a desired effect.”
[Youngblood et al., PERCOM’05]
Example: MavHome
“With inhabitant three, we noticed a new phenomenon in the course of our experimentation — the system did more training of the inhabitant than the inhabitant did to the system. There seemed to be a reluctance to give prompt feedback on the inhabitant end. On interview, the inhabitant said that they were learning to live in the dark because it was too bothersome to correct the system. This is probably human nature. We also observed a few fights between the system and the inhabitant over control that ultimately was won by the inhabitant when feedback caused the system to change behavior, but for a short duration the system caused some duress to the inhabitant—not a desired effect.”
[Youngblood et al., PERCOM’05]
Example: MavHome
“With inhabitant three, we noticed a new phenomenon in the course of our experimentation — the system did more training of the inhabitant than the inhabitant did to the system. There seemed to be a reluctance to give prompt feedback on the inhabitant end. On interview, the inhabitant said that they were learning to live in the dark because it was too bothersome to correct the system. This is probably human nature. We also observed a few fights between the system and the inhabitant over control that ultimately was won by the inhabitant when feedback caused the system to change behavior, but for a short duration the system caused some duress to the inhabitant—not a desired effect.”
[Youngblood et al., PERCOM’05]
Lack of intelligibility and control leads to …
?
Frustrated users
Our solutionOur solution(s)
Our solutionWhy questions
Understanding
What actually happens here?
Understanding
Users formulate silent questions.
Understanding
Most common: Why & Why not
Related work
[Ko et al., CHI’04] [Ko et al., CHI’09] [Myers et al., CHI’04]
[Lim et al., CHI’09] [Lim et al., Ubicomp’09]
[Ko et al., CHI’04] [Ko et al., CHI’09] [Myers et al., CHI’04]
[Lim et al., CHI’09] [Lim et al., Ubicomp’09]
No implementation for Ubicomp yet
Why questions: scenario
Why questions: intelligibility
Why questions: control
Undo
Why not questions: scenario
Why not: intelligibility and control
Do
Our solutionMaking the invisible computer visible
Our solutionMaking the invisible computer visible
Our solutionIntelligibility: Graphical Behavior Notation
Our solutionControl: cancel command
Our solutionAmbient projection system
steerable projectors
projector withwide-angle lens
Related work
[Rehman et al., Ubicomp’05] [Dey et al., CHI’03]
Our solutionReal-time feedback
Acknowledgements
Sketches: Daniel TeunkensCo-author: Geert Vanderhulst
Design: Karel RobertCo-author: Jonathan SlendersMovie: Mieke Haesen
Photography: stock.xchng
Conclusions
Undo
• Jo Vermeulen, Geert Vanderhulst, Kris Luyten, and Karin Coninx. Answering Why and Why Not Questions in Ubiquitous Computing. In Ubicomp ‘09 Supplemental Proceedings (Poster), pp. 210-213.
• Jo Vermeulen, Jonathan Slenders, Kris Luyten, and Karin Coninx. I Bet You Look Good on the Wall: Making the Invisible Computer Visible. To appear in Proc. of AmI '09, Springer LNCS, 10 pages.
http://www.jozilla.net/http://www.edm.uhasselt.be/
Backup slides
Example: smart lighting application
See also: http://ailab.wsu.edu/mavhome/
Example: MavHome
“With inhabitant three, we noticed a new phenomenon in the course of our experimentation — the system did more training of the inhabitant than the inhabitant did to the system. There seemed to be a reluctance to give prompt feedback on the inhabitant end. On interview, the inhabitant said that they were learning to live in the dark because it was too bothersome to correct the system. This is probably human nature. We also observed a few fights between the system and the inhabitant over control that ultimately was won by the inhabitant when feedback caused the system to change behavior, but for a short duration the system caused some duress to the inhabitant—not a desired effect.”
[Youngblood et al., PERCOM’05]
Example: MavHome
“With inhabitant three, we noticed a new phenomenon in the course of our experimentation — the system did more training of the inhabitant than the inhabitant did to the system. There seemed to be a reluctance to give prompt feedback on the inhabitant end. On interview, the inhabitant said that they were learning to live in the dark because it was too bothersome to correct the system. This is probably human nature. We also observed a few fights between the system and the inhabitant over control that ultimately was won by the inhabitant when feedback caused the system to change behavior, but for a short duration the system caused some duress to the inhabitant—not a desired effect.”
[Youngblood et al., PERCOM’05]
Example: MavHome
“With inhabitant three, we noticed a new phenomenon in the course of our experimentation — the system did more training of the inhabitant than the inhabitant did to the system. There seemed to be a reluctance to give prompt feedback on the inhabitant end. On interview, the inhabitant said that they were learning to live in the dark because it was too bothersome to correct the system. This is probably human nature. We also observed a few fights between the system and the inhabitant over control that ultimately was won by the inhabitant when feedback caused the system to change behavior, but for a short duration the system caused some duress to the inhabitant—not a desired effect.”
[Youngblood et al., PERCOM’05]
Example: MavHome
“With inhabitant three, we noticed a new phenomenon in the course of our experimentation — the system did more training of the inhabitant than the inhabitant did to the system. There seemed to be a reluctance to give prompt feedback on the inhabitant end. On interview, the inhabitant said that they were learning to live in the dark because it was too bothersome to correct the system. This is probably human nature. We also observed a few fights between the system and the inhabitant over control that ultimately was won by the inhabitant when feedback caused the system to change behavior, but for a short duration the system caused some duress to the inhabitant—not a desired effect.”
[Youngblood et al., PERCOM’05]
This observation is not new• V. Bellotti and W. K. Edwards. Intelligibility and accountability: human
considerations in context-aware systems. Hum.-Comput. Interact., 16(2):193–212, 2001.
• W. K. Edwards and R. E. Grinter. At home with ubiquitous computing: Seven challenges. In Proc. UbiComp ’01, pages 256–272. Springer-Verlag, 2001
• K. Rehman, F. Stajano, and G. Coulouris. Interfacing with the invisible computer. In Proc. NordiCHI ’02, pp. 213–216. ACM, 2002.
• T. Erickson. Some problems with the notion of context-aware computing. Commun. ACM, 45(2):102–104, 2002
• L. Barkhuus and A. K. Dey. Is context-aware computing taking control away from the user? Three levels of interactivity examined. In Proc. Ubicomp ’03, pp. 149–156. Springer, 2003.
…
Why questions: user studyQuestion Details Result Explanation
Q1 I understand how to use the Why feature. AAAAA Concept is easy to grasp
Q2I found the Why feature questions easy to use. AAAAN Easy to use
Q3The answers provided by the Why feature were easy to understand. NNNNA
Double negations, had to click through many follow-up questions, clutter, irrelevant (old)
questions
Q4The answers provided by the Why feature were what I wanted to know. AAAAN Easy to understand
Q5I understand how to use the control features (undo, do and "how can I …"). AAAND
Understandable in general, but "Do" is unclear, "how can I" sometimes understood as just
providing more information
Q6I found the control features (undo, do and "how can I …") easy to use. NNNAD
"Undo" and "do" too generic labels, not always both available (exploration)
Q7
I find these techniques useful to allow users to understand what happens in a smart environment, and to allow them to exert control over this behaviour. AAAAA Users felt more comfortable
Q8I was not confused by the questions or the events table. AADDN
Difference between events and actions is not clear, dual view is confusing (both why menu and
timeline/time table), clutter
Our solutionAmbient projection system
Our solutionVisible Computer: user study
Our solutionRelation to Stages of Action model
Our solutionRelation to Stages of Action model
Our solutionRelation to Stages of Action model
future work