Talk at the first SIGCHI.be conference in Affligem at October 19, 2009.

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

3. Ubicomp? Source: http://luci.ics.uci.edu/blog/archives/2009/02/6_words_16_grad.html

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]

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 … ?

16. Frustrated users

17. Our solution Our solution(s)

18. Our solution Why questions

19. Understanding What actually happens here?

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]

24. Whyquestions: scenario

25. Whyquestions: intelligibility

26. Whyquestions: control Undo

27. Whynotquestions: scenario

28. Whynot: intelligibility and control Do

29. Whyquestions: user study

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]

37. Our solution Real-time feedback

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

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/

42. Backup slides

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]

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.…

53. Whyquestions: user study

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