Improving Intelligibility and Control in Ubicomp Environments

Jo Vermeulen, Kris Luyten and Karin Coninx

Hasselt University – tUL – IBBTExpertise Centre for Digital Media

firstname.lastname@uhasselt.be

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