Tailored
Introduction
Interactions
Simon King
IxDA Interaction ‘09 | February 7th, 2009 | Vancouver, BC, Canada

1. People are increasingly finding value
Introduction
in tailored interactions, built on top of
personal data.
2. Trends point towards a near future of
data portability between services, providing
new possibilities for personalization.
3. Designers should focus on empowering
people with control over their data.

Tailored interactions are personalized to an individual,
Introduction
based on knowledge about them and their context.

Tailored interactions are personalized to an individual,
Introduction
based on knowledge about them and their context.
These are “smart” systems, making
choices on a person’s behalf.

Tailored interactions are personalized to an individual,
Introduction
based on knowledge about them and their context.
These are “smart” systems, making
choices on a person’s behalf.
This is different from customization, where
a person makes an explicit choice to alter
something within a given set of options.

Tailored interactions can take many forms:
Introduction
◊ Recommendation systems
◊ Filtering of relevant options
◊ Triggering of alerts and actions
◊ Changes to information focus
◊ Intelligent defaults
◊ Specifically withheld or available options
◊ Auto-filled choices
◊ Adaptive navigation

The desire for companies to “know their users” and
Introduction
provide personalized services exists across industries:
◊ Financial
◊ Medical
◊ Retail
◊ Hospitality
◊ Telecommunications
◊ News/Information

1 Raw Material
Personal Data Mashups
2
Designing for Control
3

The raw material that enables us to
Raw
1 Material
design tailored interactions is data.
◊ Profile/Personal
◊ Preferences
◊ Behavior
◊ History
◊ Relationships
◊ Status
◊ Anything?
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Data can be captured explicitly by asking people, but
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1 Material
is more often collected implicitly in the background,
as people use and make choices within a system.
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Designers and the companies we work for have
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1 Material
been intrigued by the possibility of a one-to-one
relationship with our users for a long time.
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Ordinary people have had a range of reactions
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to the capture and use of their personal data.
Ignorance Fear Acceptance Overload
12

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Ignorance
In the early days of the web the public was
largely unaware of what was being captured.
Some companies stored personal data,
but it was rarely put to much use.
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1 Material
Fear
Ignorance
Cookies, spam, phishing, and the FBI’s Carnivore led to
increased uncertainty about personal data collection.
At the same time companies began capturing and using
personal data more, primarily for targeted advertising.
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1 Material
Acceptance
Ignorance Fear
Web 2.0 often required or encouraged posting
and capture of personal information.
Data became a valuable asset for businesses and
services offered greater user value beyond advertising.
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Overload
Ignorance Fear Acceptance
Today, people must manage their data on
multiple services and actively monitor what
information about them is shared or public.
Companies are hungry for personal data as the services it
powers become increasingly important in people’s lives.
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In this overloaded state people are accepting a type
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of ignorance in their desire for tailored experiences.
Ignorance
Overload Fear
Acceptance
17

People are giving up their passwords to
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third-party systems for convenience.
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Full access is given to even the most sensitive data
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because aggregation services are so desirable.
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The demand for tailored interactions is bumping up
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against problems of privacy, security, and scalability.
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The demand for tailored interactions is bumping up
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1 Material
against problems of privacy, security, and scalability.
In this world of design driven by personal data
it is the designer’s job to balance the pillars
of people, technology, and business.
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The demand for tailored interactions is bumping up
Raw
1 Material
against problems of privacy, security, and scalability.
In this world of design driven by personal data
it is the designer’s job to balance the pillars
of people, technology, and business.
Recent trends point towards how we can improve people’s
control over their data while connecting products,
services, and devices to create new opportunities.
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The transition from a web of pages to a
Personal Data
2 Mashups
web of data is mature, with open APIs and
application mashups now commonplace.
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With the rise of cloud computing and SaaS more
Personal Data
2 Mashups
of our personal data that used to be locked up
in local computer systems is coming online.
◊ Office Docs ◊ CRM
◊ Finances ◊ Shopping
◊ Schedule ◊ To-dos
◊ Address Book ◊ Travel
◊ Medical Records ◊ Photos
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
31

Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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Office Docs, Finances, Schedule, Address Book, Medical
Personal Data
2 Mashups
Records, CRM, Shopping, To-dos, Travel, Photos, etc.
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People are recording moments of their lives that were
Personal Data
2 Mashups
never before captured with the help of services that
live on the web, devices, and in their environments.
◊ Preferences ◊ Weight
◊ Relationships ◊ Exercise
◊ Status ◊ Sleep
◊ Location ◊ Energy
◊ Emotions ◊ Driving
◊ Time ◊ Everything
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Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
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Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
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Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
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Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
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Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
40

Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
41

Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
42

Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
43

Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
44

Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
45

Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
46

Preferences, Relationships, Status, Location, Emotions,
Personal Data
2 Mashups
Time, Weight, Exercise, Sleep, Energy, Driving, Everything
47

The amount of raw material for designing tailored
Personal Data
2 Mashups
interactions has increased, potentially enabling
new types of personal data mashups.
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The amount of raw material for designing tailored
Personal Data
2 Mashups
interactions has increased, potentially enabling
new types of personal data mashups.
These are more complicated than application mashups
because this data is online, but usually not public.
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The amount of raw material for designing tailored
Personal Data
2 Mashups
interactions has increased, potentially enabling
new types of personal data mashups.
These are more complicated than application mashups
because this data is online, but usually not public.
New standards are emerging that allow for
private data to be shared securely, opening the
floodgates for a new era of tailored interactions.
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There are two key technical capabilities that any
Personal Data
2 Mashups
system for sharing personal data requires:
Identification
Authorization
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Identification is the fundamental link needed to correlate
Personal Data
2 Mashups
personal data and use it to build tailored interactions.
But every service we use acts like we’re a
different person, leaving us to manage scores
of usernames, passwords, and profiles.
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OpenID
Personal Data
2 Mashups
is a method of managing your identity
in one place, and using that identity to
authenticate yourself with multiple services.
This is a step towards the web feeling
like one big system, rather than a
bunch of fragmented ones.
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The next step in the process is authorization,
Personal Data
2 Mashups
or granting of access to personal data.
OAuth
handles authorization of protected data between
two services. It acts like a digital valet key,
allowing partial, rather than blanket access.
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Handing over a username and password is blanket
Personal Data
2 Mashups
authorization. Service A impersonates the user
and gets complete access to Service B.
u/p
Service Service
A B
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OAuth allows for partial authorization and control.
Personal Data
2 Mashups
Service A asks for permission to use a subset of
data from Service B, with particular restrictions.
ok
?
Service Service
A B
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OAuth will be a catalyst for widespread
Personal Data
2 Mashups
sharing of protected personal data.
It is showing up first in web applications, but can apply
to desktop, mobile, or any Internet connected device.
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Over the last few months all the major players
Personal Data
2 Mashups
have launched their own Distributed Social
Networking platforms for personal data sharing:
◊ Facebook Connect
◊ Google Friend Connect
◊ MySpaceID
◊ Yahoo! Open Strategy
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Each of these companies wants to be the trusted
Personal Data
2 Mashups
gateway for your identification and authorization.
Most are approaching this goal from a standards-based
perspective, building on top of the “Open Stack.”
Others are closed, proprietary systems (Facebook).
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There are two fundamentally differing viewpoints.
Personal Data
2 Mashups
Centralized You
3rd Party
3rd Party 3rd Party
Facebook
3rd Party
3rd Party
Via FB Connect
3rd Party 3rd Party
3rd Party
Adapted from diagram by
Chris Saad (dataportability.org)
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There are two fundamentally differing viewpoints.
Personal Data
2 Mashups
Decentralized You
Service
Service Service
Service
Service
Service
Service
Service Service
Service
Adapted from diagram by
Chris Saad (dataportability.org)
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Kevin Kelly, in Predicting the next 5,000 days
Designing for
3 Control
of the web, said that “Total personalization
will require total transparency.”
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This is a frightening vision, not unlike a panopticon
Designing for
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prison, where you can be constantly observed,
without being able to tell if you really are.
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The emergence of standards like OAuth gives me
Designing for
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hope that Kelly’s future vision can be achieved
without such a complete collapse of privacy.
But beyond technical capabilities, how
can we create tailored interactions that
are ethical and human-centered?
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Privacy is sometimes described in terms of
Designing for
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anonymity, but data must be tied to a particular
person to be useful as a material for design.
A more relevant definition is “the choice
to reveal oneself selectively.”
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This sense of control, over how personal data is used,
Designing for
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shared, and destroyed, should define the next step
in people’s relationship to data collection and use.
Control
Ignorance Fear Acceptance Overload
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How is my data used?
Designing for
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◊ What do you know about me?
◊ How do you know it?
◊ How current is my data?
◊ How can I change it?
◊ How is it used to personalize my experience?
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How is my data shared?
Designing for
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◊ What do you know about me based on data from other places?
◊ What data is being collected about me that I could use elsewhere?
◊ What data is currently shared with other people or services?
Who?
With what restrictions?
When?
◊ Is data about me being included in an aggregate data set?
How is that being used?
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How can my data be destroyed?
Designing for
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◊ How can I change what you know about me?
◊ How can I stop sharing my data?
◊ How can I remove my data?
◊ When data is removed, does it still exist within
other services I previously shared it with?
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Specific examples of how these questions can be
Designing for
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answered are beyond the scope of this presentation,
but this is an area that is ripe for developing new
interaction design patterns and best practices.
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Additional principles:
Designing for
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◊ Fail gracefully
When an interaction relies on shared data, provide a
reasonable fallback if the data is no longer available.
◊ Don’t build bubbles
Let people choose between tailored interactions
and the collective (generic) experience.
◊ Share your toys
Don’t be only a consumer of personal data,
give back to the ecosystem.
◊ Provide an exit
People should be able to share, but also to pack up and leave.
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Beyond this, we also need to get involved in
Designing for
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policy discussions that are happening within
privacy and consumer advocacy groups.
Current lobbying tends to focus on anonymizing
data used for targeted advertising. We need
to join the conversation and expand it to
include tailored interactions and control.
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1. New possibilities for tailored interactions are
Conclusion
emerging through mashups of personal data.
2. It is our responsibility to empower our
users with control over their data.
3. We need to define the patterns and principles
that support this goal, and promote policy that
addresses data usage beyond advertising.

Thanks.
Conclusion
Questions + Contact:
sking@ideo.com
Image credit: http://www.flickr.com/photos/sojamo/1343606031/