Individuals most vulnerable to the misuse of private information include persons with disabilities (e.g., denial of insurance, jobs, services), persons who are aging (e.g., senior’s fraud) and other individuals who face discrimination, stereotyping, marginalization or exclusion. This diverse group also has the most to gain from smart services that respond to personal data. Any privacy strategy must consider this growing group of consumers.
The project provides individual privacy preference exploration, creation and editing tools, (co-designed by diverse community participants), to gain informed individual control over personal data. A community-generated list of possible personal privacy preferences is used to form the basis of a proposed International Standards Organization (ISO) privacy preference interoperability standard.
Goals of the Project
- Design an interface exemplar for discovering, exploring and choosing privacy and identity management preferences
- Leverage ISO 24751* (Access for All) to discover, assert, match and evaluate personal privacy and identity management preferences
- engage relevant stakeholders in developing a proposed privacy and identity management preference application profile as a New Work Item
*ISO 24751: a standard to support processes that match unique individual needs and preferences with resources that meet those needs and preferences
How it Will Work
- a single, personalized interface to understand and determine a privacy agreement that suits the function, risk level and personal preferences
- private sector companies would have a standardized process for communicating or translating privacy options to a diversity of consumers
- implement a transparent online workspace to recruit input from stakeholders
- hold facilitated group discussions, co-design sessions and test scenarios to map out potential plans and evaluate feasibility of the plans
- draft a New Work Item (NWI) proposal to attach to ISO 24751
- create a prototype user experience exemplar
Inclusive Design for Privacy - Working Doc (Google Doc)
Key Points for Tool Introduction/Animation
DEEP 2016 Privacy Discussion Summary (Google Doc)
Privacy and Sharing Preferences List (Google Doc)
Examples of Misuse of Personal Data (Google Doc)
PIPEDA and Privacy Preferences Design
Privacy Preferences Information Model (Google Doc)
Mar 28, 2017 Design Crit Notes (Privacy), based on the interactive prototype
Feb 17, 2017 Accessible Prototyping
Jan 31, 2017 Design Crit Notes (Privacy), based on these wireframes
Dec 21, 2016 Privacy Preferences Meeting
Dec 6, 2016 Design Crit Notes (Privacy), based on these wireframes
Nov 29, 2016 Design Crit Notes (Privacy), based on these wireframes
Sept 28, 2016 Privacy and Sharing Preferences Brainstorm
Sept 8 2016 Privacy Discussion Meeting Minutes
August 25, 2016 Brainstorm Session Notes
Deliverable 1: Feasibility Report
Deliverable 2: New Work Item
Deliverable 3: Co-designed Prototype
Deliverable 4: Risk, Security and PIPEDA Assessment
Deliverable 5: Proposal for Next Steps
Research and Resources
Building Consentful Tech - zine
Privacy by Design
Media Post April 26 2017 - Researchers say that a massive 47% of consumers are put off digital channels by privacy concerns.
Your Smartphone is a Civil Rights Issues - TED Talk
The Electronic Frontier Foundation
Me and My Shadow Project - Take Control of Your Data
Me and My Shadow - Tracking, So What?
Me and My Shadow - The 8-Day Data Detox Kit
The Glass Room NYC - Looking into Your Online Life
Office of the Privacy Commisioner of Canada - Web Tracking with Cookies
Understanding Cookies (Microsoft)
The Watchers augmented board game
The Platform for Privacy Preferences Project (W3C)
Designing a Privacy Preference Specification Interface - A Case Study. Cranor, L.F.
User Interfaces for Privacy Agents. Cranor, L.F., Guduru, P. and Arjula, M.
The Privacy Bird !
Anne Cavoukian U of T Alumni Presentation - Joseph's notes and link to Anne's slide deck
International Council on Global Privacy and Security by Design
Online security tips from Y Combinator
NYPR podcast: The Bookie, The Phonebooth, and the FBI
The Quantified Worker - Harvard University
Deceived by Design - How tech companies use dark patterns to discourage us from exercising our rights to privacy
The Internet of Things - Examples
Leon's - Project Smart Furniture
Amazon Echo Look
Examples of "Best Practices" for Protecting Users' Privacy
Questions (from initial brainstorming session)
We want to address the following three questions:
- What are the possible privacy preferences someone might have?
- How is private information being used currently?
- Who are vulnerable in this context?
As part of answering these questions, we want to discuss:
- what constitutes private information,
- what is being gathered and for what purpose,
- what are the conflicts between privacy requirements and what is actually being done today, and
- are there constraints in fulfilling privacy wishes.