Tailored Interactions
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Tailored Interactions

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

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

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Tailored Interactions Tailored Interactions Presentation Transcript

  • 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? 9
  • Data can be captured explicitly by asking people, but Raw 1 Material is more often collected implicitly in the background, as people use and make choices within a system. 10
  • Designers and the companies we work for have Raw 1 Material been intrigued by the possibility of a one-to-one relationship with our users for a long time. 11
  • Ordinary people have had a range of reactions Raw 1 Material to the capture and use of their personal data. Ignorance Fear Acceptance Overload 12
  • Raw 1 Material 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. 13
  • Raw 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. 14
  • Raw 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. 15
  • Raw 1 Material 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. 16
  • In this overloaded state people are accepting a type Raw 1 Material of ignorance in their desire for tailored experiences. Ignorance Overload Fear Acceptance 17
  • People are giving up their passwords to Raw 1 Material third-party systems for convenience. 18
  • Full access is given to even the most sensitive data Raw 1 Material because aggregation services are so desirable. 19
  • The demand for tailored interactions is bumping up Raw 1 Material against problems of privacy, security, and scalability. 20
  • 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. 21
  • 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. 22
  • 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. 23
  • 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 24
  • Office Docs, Finances, Schedule, Address Book, Medical Personal Data 2 Mashups Records, CRM, Shopping, To-dos, Travel, Photos, etc. 25
  • Office Docs, Finances, Schedule, Address Book, Medical Personal Data 2 Mashups Records, CRM, Shopping, To-dos, Travel, Photos, etc. 26
  • Office Docs, Finances, Schedule, Address Book, Medical Personal Data 2 Mashups Records, CRM, Shopping, To-dos, Travel, Photos, etc. 27
  • Office Docs, Finances, Schedule, Address Book, Medical Personal Data 2 Mashups Records, CRM, Shopping, To-dos, Travel, Photos, etc. 28
  • Office Docs, Finances, Schedule, Address Book, Medical Personal Data 2 Mashups Records, CRM, Shopping, To-dos, Travel, Photos, etc. 29
  • Office Docs, Finances, Schedule, Address Book, Medical Personal Data 2 Mashups Records, CRM, Shopping, To-dos, Travel, Photos, etc. 30
  • 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. 32
  • Office Docs, Finances, Schedule, Address Book, Medical Personal Data 2 Mashups Records, CRM, Shopping, To-dos, Travel, Photos, etc. 33
  • Office Docs, Finances, Schedule, Address Book, Medical Personal Data 2 Mashups Records, CRM, Shopping, To-dos, Travel, Photos, etc. 34
  • 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 35
  • Preferences, Relationships, Status, Location, Emotions, Personal Data 2 Mashups Time, Weight, Exercise, Sleep, Energy, Driving, Everything 36
  • Preferences, Relationships, Status, Location, Emotions, Personal Data 2 Mashups Time, Weight, Exercise, Sleep, Energy, Driving, Everything 37
  • Preferences, Relationships, Status, Location, Emotions, Personal Data 2 Mashups Time, Weight, Exercise, Sleep, Energy, Driving, Everything 38
  • Preferences, Relationships, Status, Location, Emotions, Personal Data 2 Mashups Time, Weight, Exercise, Sleep, Energy, Driving, Everything 39
  • 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. 48
  • 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. 49
  • 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. 50
  • There are two key technical capabilities that any Personal Data 2 Mashups system for sharing personal data requires: Identification Authorization 51
  • 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. 52
  • 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. 53
  • 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. 54
  • 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 55
  • 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 56
  • 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. 57
  • 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 58
  • 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). 59
  • 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) 60
  • 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) 61
  • Kevin Kelly, in Predicting the next 5,000 days Designing for 3 Control of the web, said that “Total personalization will require total transparency.” 62
  • This is a frightening vision, not unlike a panopticon Designing for 3 Control prison, where you can be constantly observed, without being able to tell if you really are. 63
  • The emergence of standards like OAuth gives me Designing for 3 Control 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? 64
  • Privacy is sometimes described in terms of Designing for 3 Control 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.” 65
  • This sense of control, over how personal data is used, Designing for 3 Control shared, and destroyed, should define the next step in people’s relationship to data collection and use. Control Ignorance Fear Acceptance Overload 66
  • How is my data used? Designing for 3 Control ◊ 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? 67
  • How is my data shared? Designing for 3 Control ◊ 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? 68
  • How can my data be destroyed? Designing for 3 Control ◊ 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? 69
  • Specific examples of how these questions can be Designing for 3 Control 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. 70
  • Additional principles: Designing for 3 Control ◊ 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. 71
  • Beyond this, we also need to get involved in Designing for 3 Control 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. 72
  • 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/