tailored interactions

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Presentation from the IxDA Interaction '09 conference in Vancouver, BC, Canada on Feb. 7, 2009.

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Introduction Tailored Interactions

Simon King

IxDA Interaction ‘09 | February 7th, 2009 | Vancouver, BC, Canada

Introduction 1. People are increasingly finding value 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.

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

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

These are “smart” systems, making choices on a person’s behalf.

Introduction Tailored interactions are personalized to an individual, 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.

Introduction Tailored interactions can take many forms:

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◊

Introduction The desire for companies to “know their users” and provide personalized services exists across industries:

Financial◊

Medical◊

Retail◊

Hospitality◊

Telecommunications◊

News/Information◊

Raw Material

Personal Data Mashups

Designing for Control

1

2

3

9

Raw Material1 The raw material that enables us to

design tailored interactions is data.

Profile/Personal◊

Preferences◊

Behavior◊

History◊

Relationships◊

Status◊

Anything?◊

10

Raw Material1 Data can be captured explicitly by asking people, but

is more often collected implicitly in the background, as people use and make choices within a system.

11

Raw Material1 Designers and the companies we work for have

been intrigued by the possibility of a one-to-one relationship with our users for a long time.

12

Raw Material1 Ordinary people have had a range of reactions

to the capture and use of their personal data.

Ignorance Fear Acceptance Overload

13

Raw Material1

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.

14

Raw Material1

Ignorance Fear

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.

15

Raw Material1

Ignorance Fear Acceptance

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.

16

Raw Material1

Ignorance Fear Acceptance Overload

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.

17

Raw Material1 In this overloaded state people are accepting a type

of ignorance in their desire for tailored experiences.

Ignorance

FearOverload

Acceptance

18

Raw Material1 People are giving up their passwords to

third-party systems for convenience.

19

Raw Material1 Full access is given to even the most sensitive data

because aggregation services are so desirable.

20

Raw Material1 The demand for tailored interactions is bumping up

against problems of privacy, security, and scalability.

21

Raw Material1 The demand for tailored interactions is bumping up

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.

22

Raw Material1 The demand for tailored interactions is bumping up

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.

23

Personal Data Mashups2 The transition from a web of pages to a

web of data is mature, with open APIs and application mashups now commonplace.

24

Personal Data Mashups2 With the rise of cloud computing and SaaS more

of our personal data that used to be locked up in local computer systems is coming online.

Office Docs◊

Finances◊

Schedule◊

Address Book◊

Medical Records◊

CRM◊

Shopping◊

To-dos◊

Travel◊

Photos◊

25

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

26

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

27

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

28

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

29

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

30

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

31

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

32

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

33

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

34

Personal Data Mashups2 Office Docs, Finances, Schedule, Address Book, Medical

Records, CRM, Shopping, To-dos, Travel, Photos, etc.

35

Personal Data Mashups2 People are recording moments of their lives that were

never before captured with the help of services that live on the web, devices, and in their environments.

Preferences◊

Relationships◊

Status◊

Location◊

Emotions◊

Time◊

Weight ◊

Exercise◊

Sleep◊

Energy◊

Driving◊

Everything◊

36

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

37

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

38

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

39

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

40

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

41

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

42

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

43

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

44

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

45

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

46

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

47

Personal Data Mashups2 Preferences, Relationships, Status, Location, Emotions,

Time, Weight, Exercise, Sleep, Energy, Driving, Everything

48

Personal Data Mashups2 The amount of raw material for designing tailored

interactions has increased, potentially enabling new types of personal data mashups.

49

Personal Data Mashups2 The amount of raw material for designing tailored

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.

50

Personal Data Mashups2 The amount of raw material for designing tailored

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.

51

Personal Data Mashups2 There are two key technical capabilities that any

system for sharing personal data requires:

Identification

Authorization

52

Personal Data Mashups2 Identification is the fundamental link needed to correlate

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.

53

Personal Data Mashups2 OpenID

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.

54

Personal Data Mashups2 The next step in the process is authorization,

or granting of access to personal data.

OAuthhandles authorization of protected data between two services. It acts like a digital valet key, allowing partial, rather than blanket access.

55

Personal Data Mashups2 Handing over a username and password is blanket

authorization. Service A impersonates the user and gets complete access to Service B.

u/p

ServiceA

ServiceB

56

Personal Data Mashups2 OAuth allows for partial authorization and control.

Service A asks for permission to use a subset of data from Service B, with particular restrictions.

ServiceA

ServiceB

? ok

57

Personal Data Mashups2 OAuth will be a catalyst for widespread

sharing of protected personal data.

It is showing up first in web applications, but can apply to desktop, mobile, or any Internet connected device.

58

Personal Data Mashups2 Over the last few months all the major players

have launched their own Distributed Social Networking platforms for personal data sharing:

Facebook Connect◊

Google Friend Connect◊

MySpaceID◊

Yahoo! Open Strategy◊

59

Personal Data Mashups2 Each of these companies wants to be the trusted

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).

60

Personal Data Mashups2 There are two fundamentally differing viewpoints.

Centralized You

Adapted from diagram by Chris Saad (dataportability.org)

3rd Party

3rd Party

3rd Party

3rd Party

3rd Party

3rd Party

3rd Party

3rd Party

FacebookVia FB Connect

61

Personal Data Mashups2 There are two fundamentally differing viewpoints.

Decentralized You

Adapted from diagram by Chris Saad (dataportability.org)

Service

Service

Service

Service

Service

Service

ServiceServiceService

Service

62

Designing for Control3 Kevin Kelly, in Predicting the next 5,000 days

of the web, said that “Total personalization will require total transparency.”

63

Designing for Control3 This is a frightening vision, not unlike a panopticon

prison, where you can be constantly observed, without being able to tell if you really are.

64

Designing for Control3 The emergence of standards like OAuth gives me

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?

65

Designing for Control3 Privacy is sometimes described in terms of

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.”

66

Designing for Control3 This sense of control, over how personal data is used,

shared, and destroyed, should define the next step in people’s relationship to data collection and use.

Ignorance Fear ControlAcceptance Overload

67

Designing for Control3 How is my data used?

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?◊

68

Designing for Control3 How is my data shared?

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?

69

Designing for Control3 How can my data be destroyed?

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?

70

Designing for Control3 Specific examples of how these questions can be

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.

71

Designing for Control3 Additional principles:

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.

72

Designing for Control3 Beyond this, we also need to get involved in

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.

Conclusion 1. New possibilities for tailored interactions are 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.

Conclusion Thanks. Questions + Contact:sking@ideo.com

Image credit: http://www.flickr.com/photos/sojamo/1343606031/

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