The document discusses smart user experiences and the importance of context. It describes how machine learning and big data can provide contextual information to enable more intelligent and automated experiences. Context refers to the circumstances and environment that provide a frame of reference for understanding information. While technologies like machine learning and natural language processing are important, context itself is a design approach rather than a specific implementation. The key lessons are that context should be respected, experiences should be device-independent, and jobs may change but workers will still be needed.

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Context is King
Smart User Experiences
in the World of Work
What they are,
What they aren’t,
And why they’re important.
Ultan O’Broin, Senior Director, Oracle Applications Cloud

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gratefully acknowledged

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What I Do (@localization)
• Sales enablement: deal support online and
in person – EMEA and APAC – with User
Experience must-haves
• Oracle PartnerNetwork enablement
with User Experience resources
• User Experience innovation demos and
market feedback
• Increase Oracle Cloud value using User
Experience Differentiator

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con·text
/ˈkäntekst/
noun
The circumstances that form the setting for an event,
statement, or idea, and in terms of which it can be
fully understood and assessed.
Context is the essence of user experience
We have come a long way

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ContextSmartA More Human
Way of Working

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From glimpses to fear

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● Descriptions
● Derived
● User control
● Application level
o domain
o modes/roles
o settings and preferences
● YYMV on success
● Manual QA
context in software localization: “it depends”

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enter machine intelligence

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machine learning and big data
• Machine learning: computers learn without explicit programming
• Big Data: very large data set analysis to reveal subtle but significant
patterns and trends
• Statistical Machine Translation(MT) versus Rule-Based MT analogy
• MT Hybrids
• Machine learning technology recognizes, classifies, analyzes the world
around us

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● Increase in availability, quantity and diversity of data
o Enhanced computational, networking, and storage resources
o Mobile and wearable computing
● Enables context at the task and micro task level: a “closer fit”
● Promise of lasting UX relationship if you APIs
the cloud and context

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cool UX, but it is usable?
• Beauty ≠ usable, usable = beauty
• Smart UX independent of technology
and devices ≠ gadgetry
• Analogy
– Notepads versus iPads?
– CAT versus Microsoft Excel?
• Technology versus interaction and ritual

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human part of the context equation: that fit with your
day
● User information
o habits and history
o emotional and biophysical state
● Social environment
o co-location of others
o social interaction and group dynamics
● Tasks
o spontaneous/opportunistic
o directed

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environmental part of the context equation
● Context of Use
(the hidden third rail of adoption)
● Location
o absolute and relative position
● Infrastructure
o surrounding resources
o Provided
o ubiquitous
● Physical conditions
o light, noise, pressure, temperature, etc.

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sources of contextual information...
● Mobile devices
o geolocation (GPS) and orientation (compass,
accelerometer)
● Beacons & sensors
● Wearable tech
o biometrics, eye tracking
o Heart rate monitors
o Emotional state
● Smart interconnected devices (IoT)
● Digital footprints
o social networks, buying habits, check-ins,
travel itineraries, web visit
patterns, internet history

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3 smart ux impacts on daily lives
automation
advice
discovery

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automation: #everyonespeaksfood
• Filling in order forms
• Sending notifications just-in-time
• Prioritizing events and actions
• Performing tasks
• Audience: Which jobs will be automated
first? Which will never be?
• Which GILT jobs will change?
• “Those who own robots and those who
work for them” (Marc Andreessen)
• Menus vs Cooks and Google Translate

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advice: beyond #uncannyvalley
• What to buy?
• Which route to take?
• More complex future options:
– Talent fit to job role
– Impact of financial decisions
– Store layouts (#VR)
• Global branding
• Statutory localization requirements
• Cultural and social convention

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discovery: #parseymcparseface = fugeddaboutit
• Boundless possibilities
– Social media: disease prevention, workforce changes
– Fintech: market movements
– Promising locations for oil and gas exploration
– Drug discovery (big pharma and friends)
– Legal duedil (Ross, Watson lawyer)
– Global climate change (models)
• Machine intelligence heavy lift of variables
across terrabytes in the cloud
• Digestible results, invite discovery, do more
• More productivity, business opportunities
• Biggest ROI on smart UX?
• Alters work/life balance in new ways

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machine learning, big data and human translation

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cooking up the human machine dialog
• Essential: user requirements (context of
use)
• Interdependent relationship: human versus
machine?
• Smart UX recognizes a highly nuanced
dialog: sensitive to cultural conventions of
work, life, society
• Smart UX? Natural, intuitive, seamless.
Transparent

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big data theory...

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mobile capture and NLP: challenges
• machine learning to parse
NLP, identify keywords &
relationships
• So translation is not a
context problem per se, but
NLP
• classifiers needed post-NLP
• data and linguist intensive
• colloquial phrases as native
speaker would use them
needed
• trainable and personalizable

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capture: what is context again?
● provides a frame-of-reference
o orientation within a ‘world
model’
o allows us to measure
relevance to things around us
o informs our decisions about
what to do next
o make that sale?

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but context is not...
● data discovery
o context is not data analysis per se, but provides a perspective on the
data
● machine learning
o context provides data to machine learning algorithms, but it is not
machine learning
● NLP
o NLP can both help determine context and can use context, but it is not
context

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context facilitates intelligent UXs
● transparent software where the ‘right thing just happens’
● free users from mundane tasks to focus on what they love doing
● relevant-only notification
● decision augmentation

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So, ‘Context’ is a design
approach,
not a specific
implementation!

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main smart UX lessons for GILT industry
● GILT industry must stay current with Cloud and tech innovation,
AI, ML, VR, AR…
● Stay focused on user experience as “smart UX”
● Be independent of technology (device neutral, etc)
● Context should be generated
● Context of use must be respected
● You won’t be out of a job, but “it depends”
(cooking, translation, painting, writing tests)
● You may end up doing a job that doesn’t exist now

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We’re done.
Questions?
QUESTIONS?