Eran Aharonson's talk on "Intuitive User-Interface" at UPA Israel's 2011 event

1. Eran Aharonson
UPA Israel 2011
Intuitive User Interfaces

2. Topics
 Introduction to Intuitive User Interfaces
 What is one touch ?
 Use case – integrating one touch into smartphones
 Underlying technology
 Challenges
 Overcoming
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3. Intuitive User Interfaces
 Established 1 January 2009
 The company’s mission is to simplify the use of devices
(mobile phones first) via One Touch Experience
 Founded by industry veterans and experts in the fields
of Mobile, Machine learning and User Experience
 Patent pending:
 “System and Method for intuitive User Interaction”
 Priority date: 26 June 2008
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4. Evolution of Complexity
Simplicity Complexity
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5. Vision
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6. What went wrong?
 Endless applications....
 Endless information....
 Screens away...
 Manus away…
 Fun…
Endless scrolls and touches…
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7. Quiz: How many clicks to setup
your alarm Clock ?
Set alarm to
7AM

8. Persistent changes – are hard to use
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9. Mobile User Experience Challenges
Complexity:
• More features and applications
high and with deeper menu trees
increasing
• To ‘call John Smith’ you need to
“Silos” of open contacts, search
activities contact, select location, place
call
Small screen • Current solutions (predictive
and text, speech recognition) don’t
limited data help
entry • Mobile is not PC
Impersonal • The user interface does not
adapt according to location,
and Static UI status, usage history etc.
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10. ‹#›

11. NTT DoCoMo Eye-Controlled Phones
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12. One Touch – the vision
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13. The Vision:
What you need, when you need it
Situation
• Adaptive to • Options
the user • Time • Fast, simple
• Location • Intuitive
• Past events
Personal One Touch
…One Touch Away
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14. One Touch in action (Android)
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15. One Touch Experience
Text Debra
Go to VVM
Call Ron
Set Alarm Clock
Open a network
connection
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16. One Touch Calls & SMS Examp;e
Intuitive: Touch
one touch contact icon
Standard Scroll for Select home /
Click ‘phone’
Android name contact mobile
Intuitive: Click Scroll for Select home /
Click ‘Home’
fallback ‘phone’ name contact mobile
In most cases: the action is there, saves the user many touches
If the action is not there: 1 more touch than Standard Android
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17. Dynamic UI: One Touch for any
application
Intuitive: Touch
one touch application
Standard Click Scroll for
Select
Android ‘Applications’ app
Intuitive: Click Scroll for
fallback Select
‘Applications’ app
In most cases: application is there, saves the user many touches
If the application is not there: same as Standard Android
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18. One Touch - the
Technology
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19. Solution flow
Log – Black Box Learn One Touch
• Calls, SMS, web, • Patterns • Personal and
applications • Habits situation based
• Time, location, • Situations and prediction
network info scenarios • Simple and
• Phone events and Intuitive 3D UI
sensors
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20. Black Box Event Logger
Situation
Events
Information
• Calls, SMS, IM, Email
Contact • Incoming/outgoing Time
• Web page, Playlist,
Items Destination
Location
Virtual
Apps • Games, Camera, ...
Event
Connectivity Log
Social • Facebook, twitter
Sensors
System • Settings, General/Silent
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21. Learning Engine
Virtual Learning Statistical
Event
Log
Engine Prediction
Model
Creating statistical model from events
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22. Prediction Engine
Time
Location
Connectivity  Call Ron’s mobile
Sensors
 SMS to Inbal
Current Situation Information
Prediction
Engine
 Start the alarm clock
Statistical  Start service
Actions
Last
Model
Actions
Generating personalized, situation based actions
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23. Android User Experience
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24. Challenges
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25. Challenges
 Black Box approach
 Existing predictors
 Multiple channels of communication
 Different roles
 User Expectations
 Not enough data / Boot strapping
 User Interfaces
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26. Black Box
 Device “senses” the world
 Many sensors
 Time / Location
 Connectivity
 Device status
…
 Correlation to reality
 Silence ~ meeting
 BT ~ car
 …
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27. Why known predictors work?
 Last call  Returning a call
Probability
Probability
Incoming
Missed
Outgoing
Calls distance Hours
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28. Frequent actions - contact prediction
 Prediction of contacts based
on frequency
 Usually one very strong
contact
Probability
 A few contacts that always
have high probability to be
used (usually 3 to 5)
Random
Different Contacts
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29. Uneven distribution
Web
Morning
Night 10%
23%
Applications
Calls
Afternoon
34%
Evening
33%
SMS
Action type Time of day
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30. Communication channels
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31. Usage pattern (Roles)
 Personal
 Incoming ~ outgoing calls
 Most from address book
 Last calls a good predictor
 VC
 Incoming >> outgoing calls
 Many unknown – used once
 Lot of meetings – many missed
 Most calls are done in the car (other device)
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32. Expectations
 I always call my mom in the morning
 Well not always …
 I never spoke to that person
 What about yesterday ?
 Why this person does not appear?
 Well… because last communication was e-mail checked on
other device
 Those are all last calls….
 But only 60% is last
 No one can read my mind…
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33. Data - missing
 Average ~ 50 per day
 Texting is mostly ping-
pong chats
 Very few are beyond
last or frequent
 Takes time to learn –
what we do in the
evening at home …
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34. User Interfaces
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35. Guideline to
Solution
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36. Think positive
 Learn from first appearance
 Users know the value – we don’t …
 Forget fast
 Compensate the fast learning
 Find the reason with time
 Location
 Time
 Missed call
 Compare to other options
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37. Use the person brain …
 Present enough options ~ 10
 Miller – short memory < 7
 In web people can do more
 Build a graphic language
 Images
 Icons
 Selection is fast
 We know what we look for …
 Reminder
 Magic / Fun
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38. Summary
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39. One Touch - highlights
 Actions are predicted based on various probabilistic criteria
 Above “black box” sensors
 Normalization is performed on received data
 Data is part of conversation or usage pattern
 User behavior shows:
 Strong tendency for the short period history (i.e. last calls)
 Few frequent actions with high probability – usually also inside the last
actions history
 It takes long time to learn behavior of non frequent actions
 Using Intuitive UI saves clicks
 There is still work to do
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40. ‹#›

41. Thank you
Eran Aharonson
eran.aharonson@intuitiveui.com