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Improving Intelligibility and Control in Ubicomp Environments Jo Vermeulen, Kris Luyten and Karin Coninx firstname.lastname@uhasselt.be Hasselt University – tUL – IBBT Expertise 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]
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 ,[object Object]
 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.…
Lack of intelligibility and control leads to … ?
Frustrated users
Our solution Our solution(s)
Our solution Why questions
Understanding What actually happens here?
Understanding Users formulate silentquestions.
Understanding Most common: Why & Why not
Relatedwork [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 implementationforUbicompyet [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]
Whyquestions: scenario
Whyquestions: intelligibility
Whyquestions: control Undo
Whynotquestions: scenario
Whynot: intelligibility and control Do
Whyquestions: user study
Our solution Making the invisible computer visible
Our solution Making the invisible computer visible
Our solution Intelligibility: Graphical Behavior Notation
Our solution Control: cancel command
Our solution Ambient projection system
Our solution Ambient projection system projector with wide-angle lens steerable projectors
Relatedwork [Rehman et al., Ubicomp’05] [Dey et al., CHI’03]
Our solution Real-time feedback
Our solution Visible Computer: user study
Acknowledgements Sketches: Daniel Teunkens Co-author: GeertVanderhulst Design:Karel Robert Co-author: Jonathan Slenders Movie: MiekeHaesen Photography:stock.xchng
Conclusions ,[object Object]
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.Undo 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]

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Improving Intelligibility and Control in Ubicomp Environments

  • 1. Improving Intelligibility and Control in Ubicomp Environments Jo Vermeulen, Kris Luyten and Karin Coninx firstname.lastname@uhasselt.be Hasselt University – tUL – IBBT Expertise Centre for Digital Media
  • 2. 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
  • 4. Why are intelligibility and control important? HAL 9000 from “2001: A Space Odyssey” (1968)
  • 5. Example: smart lighting application See also: http://ailab.wsu.edu/mavhome/
  • 6. 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]
  • 7. 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]
  • 8. 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]
  • 9. 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]
  • 10.
  • 11. W. K. Edwards and R. E. Grinter. At home with ubiquitous computing: Seven challenges. In Proc. UbiComp ’01, pages 256–272. Springer-Verlag, 2001
  • 12. K. Rehman, F. Stajano, and G. Coulouris. Interfacing with the invisible computer. In Proc. NordiCHI ’02, pp. 213–216. ACM, 2002.
  • 13. T. Erickson. Some problems with the notion of context-aware computing. Commun. ACM, 45(2):102–104, 2002
  • 14. 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.…
  • 15. Lack of intelligibility and control leads to … ?
  • 17. Our solution Our solution(s)
  • 18. Our solution Why questions
  • 20. Understanding Users formulate silentquestions.
  • 21. Understanding Most common: Why & Why not
  • 22. Relatedwork [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]
  • 23. No implementationforUbicompyet [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]
  • 30. Our solution Making the invisible computer visible
  • 31. Our solution Making the invisible computer visible
  • 32. Our solution Intelligibility: Graphical Behavior Notation
  • 33. Our solution Control: cancel command
  • 34. Our solution Ambient projection system
  • 35. Our solution Ambient projection system projector with wide-angle lens steerable projectors
  • 36. Relatedwork [Rehman et al., Ubicomp’05] [Dey et al., CHI’03]
  • 38. Our solution Visible Computer: user study
  • 39. Acknowledgements Sketches: Daniel Teunkens Co-author: GeertVanderhulst Design:Karel Robert Co-author: Jonathan Slenders Movie: MiekeHaesen Photography:stock.xchng
  • 40.
  • 41. 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.Undo http://www.jozilla.net/ http://www.edm.uhasselt.be/
  • 43. Example: smart lighting application See also: http://ailab.wsu.edu/mavhome/
  • 44. 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]
  • 45. 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]
  • 46. 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]
  • 47. 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]
  • 48.
  • 49. W. K. Edwards and R. E. Grinter. At home with ubiquitous computing: Seven challenges. In Proc. UbiComp ’01, pages 256–272. Springer-Verlag, 2001
  • 50. K. Rehman, F. Stajano, and G. Coulouris. Interfacing with the invisible computer. In Proc. NordiCHI ’02, pp. 213–216. ACM, 2002.
  • 51. T. Erickson. Some problems with the notion of context-aware computing. Commun. ACM, 45(2):102–104, 2002
  • 52. 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.…
  • 54. Our solution Ambient projection system
  • 55. Our solution Visible Computer: user study
  • 56. Our solution Relation to Stages of Action model
  • 57. Our solution Relation to Stages of Action model
  • 58. Our solution Relation to Stages of Action model future work