Conversational Architecture, CAVE Language, Data Stewardship

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Hello. Conversational Architecture on the Internet

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 of Conversational Architecture, CAVE Language, Data Stewardship

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Hello.Conversational Architecture on the Internet

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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

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Who’s Loren?

• @LorenDavie on Twitter

[email protected]

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Phase 1: Internet in a Box

www

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Tipping Point: Introduction of the iPhone

2007

“Scrolls Like Butter”

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Phase 2: Cloud + Devices

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Another Tipping Point

???

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Phase 3: Ubiquitous Internet

?♫

www

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Adaptive, Personalized, Contextual

Here’s your coffee, just the way you like it.

www

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Five Forces

• Mobile Devices

• Social Media

• Data

• Sensors

• Location

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Problems

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Problem 1: No Language

?

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Problem 2: Privacy Issues

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Solving Problem #1

Enter the

Metaphor

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The Conversation

• Multi-directional

• Multi-modal

• Multi-channel

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From Metaphor to Design Language

Conversational Architecture Visual Expression

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Metaphor to Design Language

CAVE languagecavelanguage.org

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CAVE Language

• Whiteboard / Napkin / Presentation -Friendly

• Methodology Neutral

• Scales Up, Scales Down

• Useful Across Disciplines

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Structure of CAVE language

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DataThe Foundation of Context

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Data Origins: Devices and Sensors

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Data Origins: External Data Sources

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Data Processing

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User Input

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Data In a Contextual App

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User ContextPAGES Analysis

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Personas

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Affinity

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Goals

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Environment

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Sentiment

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InferencesConverts Data to User Context

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Inferences

An Inference is made from data

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Inferences

Usually there is a condition that must be met

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Inferences

If the condition is met, the user is associated with the context element.

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Inferences in a Contextual App

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Application ModesDynamic Response to User Context

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Switch

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Modal Switch for a Contextual App

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Modal Switch for a Contextual App

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cavelanguage.org

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Solving Problem #2

• Contextual Apps require User Data

• User Data is sensitive, and can be abused

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Privacy Debate: All or Nothing

Surrender all control of your personal data

Completely opt out of contextual

appsvs

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Data StewardshipA Framework for Responsible Use of Personal Data

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Most Problems Come From Third-Party Access to Data

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Roles in the Data Ecosystem

Data Producer Data Consumer

Data Citizen

DataUses

is the subject of

Acquires or Creates

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Data PolicyThe Citizen’s Rules for Their Data

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Contents of Data Policies

• A Default Rule

• Rules Tied to Letter Grades

• Rules About Specific Data Categories

• Whitelists / Blacklists

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How do you know data users will follow the rules?

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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

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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

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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.

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TellTrail: A Data Policy Repository

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Thanks!@LorenDavie

[email protected]

cavelanguage.org telltrail.me

www.axilent.com