conversational architecture, cave language, data stewardship
DESCRIPTION
These are the slides from the presentation I gave at the Semiotics Web meetup group on Nov 1st 2014. In this talk I discussed the emergency of the ubiquitous Internet, how to discuss the design of contextual apps, and presented an approach to privacy concerns that are inherently connected.TRANSCRIPT
Hello.Conversational Architecture on the Internet
Who’s Loren?• Founder / CEO of Axilent
• Makes ACE - the Adaptive Context Engine
• User Profiling and Dynamic, Personalized Content Targeting
• Former Director of Technology at digital agencies HUGE and Alexander Interactive
• Python hacker
Phase 1: Internet in a Box
www
Tipping Point: Introduction of the iPhone
2007
“Scrolls Like Butter”
Phase 2: Cloud + Devices
Another Tipping Point
???
Phase 3: Ubiquitous Internet
?♫
www
Adaptive, Personalized, Contextual
Here’s your coffee, just the way you like it.
www
Five Forces
• Mobile Devices
• Social Media
• Data
• Sensors
• Location
Problems
Problem 1: No Language
?
Problem 2: Privacy Issues
Solving Problem #1
Enter the
Metaphor
The Conversation
• Multi-directional
• Multi-modal
• Multi-channel
From Metaphor to Design Language
Conversational Architecture Visual Expression
CAVE Language
• Whiteboard / Napkin / Presentation -Friendly
• Methodology Neutral
• Scales Up, Scales Down
• Useful Across Disciplines
Structure of CAVE language
DataThe Foundation of Context
Data Origins: Devices and Sensors
Data Origins: External Data Sources
Data Processing
User Input
Data In a Contextual App
User ContextPAGES Analysis
Personas
Affinity
Goals
Environment
Sentiment
InferencesConverts Data to User Context
Inferences
An Inference is made from data
Inferences
Usually there is a condition that must be met
Inferences
If the condition is met, the user is associated with the context element.
Inferences in a Contextual App
Application ModesDynamic Response to User Context
Switch
Modal Switch for a Contextual App
Modal Switch for a Contextual App
Solving Problem #2
• Contextual Apps require User Data
• User Data is sensitive, and can be abused
Privacy Debate: All or Nothing
Surrender all control of your personal data
Completely opt out of contextual
appsvs
Data StewardshipA Framework for Responsible Use of Personal Data
Most Problems Come From Third-Party Access to Data
Roles in the Data Ecosystem
Data Producer Data Consumer
Data Citizen
DataUses
is the subject of
Acquires or Creates
Data PolicyThe Citizen’s Rules for Their Data
Contents of Data Policies
• A Default Rule
• Rules Tied to Letter Grades
• Rules About Specific Data Categories
• Whitelists / Blacklists
How do you know data users will follow the rules?
telltrail.me
• A kind of “Better Business Bureau” for data users
• Holds repositories of citizen data policies
• Provides certification marks for compliant data users (letter grades) to let citizens know they are trustworthy
Letter Grades
• Like NYC Restaurant health letter grades
• Indicates the level of compliance of the data user organization
• Lets citizens know the data user organization is trustworthy
Letter Grades• A: Audited and Verified adherence to Data Polices
for both internally created and externally sourced data.
• B: Adherence to Data Policies for both internally created and externally sourced data.
• C: Adherence to Data Policies for just externally sourced data.
TellTrail: A Data Policy Repository
Thanks!@LorenDavie
cavelanguage.org telltrail.me
www.axilent.com