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Shadows of the emerging worlds: Designing for XR Trust [AWE2021]

Shadows of the emerging worlds: Designing for XR Trust [AWE2021]

Today we see advancement in practical applications of emerging technologies in our homes and at work. As these solutions grow towards ubiquity, so do the possible harms and obstacles towards the world in which we all want to live.

In this talk Noble Ackerson, talks about trust and ethics in XR specifically:
Dark patterns in XR - impact, example, opportunity;
AI fairness & bias - impact, example, opportunity;
Data privacy/trust and security - impact, example, opportunity.
He presents practical examples on principles to avoid wading in dark patterns within the shadows of the emerging world and how you optimize for trust through explainability, context, control, choice.

Noble Ackerson

November 23, 2021
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Transcript

  1. SHADOWS
    OF THE
    EMERGING WORLD
    TRUST & ETHICS IN XR
    XR Safety & Security Track curated by XRSI

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  2. Hi,I’m Noble!
    Find me at the intersection
    of product leadership, data
    governance, and emergent
    technology.

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  3. QUICK STORY
    A glasshole’s
    journey to data
    privacy awareness

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  4. 404 user consent missing

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  5. The mixture of the real
    world and virtual worlds
    so that one understands
    the other.
    XR

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  6. Privacy?
    context
    choice
    control
    +
    Respect

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  7. Trust?
    data transparency +
    value delivery +
    consequence acceptance

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  8. XR a practice of
    systemizing, defending, and
    recommending right or wrong
    practices in extended
    reality, in effort to reduce
    experiential harm.
    XR Ethics

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  9. Image credit: NY Times Wirecutter | The State of Consumer Data Privacy Laws in the US

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  10. Disparate
    treatment
    Procedural fairness
    Disparate
    impact
    Distributive justice, minimize
    difference in outcomes

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  11. Building for people requires
    collaboration
    SDKs & Documentation
    Localization
    Internationalization,
    Safety, Security, Diversity,
    Privacy
    DEVICE
    MANUFACTURERS
    Context, Choice, Controls
    Ethics, Localization
    Internationalization, Safety,
    Security, Diversity, Privacy
    CONTENT
    DEVELOPERS
    Proactive Governance
    Data stewardship,
    Governance, Procedural
    Fairness, Distributive
    Justice
    REGULATORY
    BODIES
    Informed consumer/creator
    Feedback, consent, drive XR
    economy
    END
    USERS

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  12. RITY
    PRIVACY
    SAFETY
    LOCALIZATION
    DIV
    SECURITY
    SPONSIBILITY
    ETHICS
    DIVERSITY
    S
    PRIVACY
    SAFETY
    PRIVA
    ETHICS
    ACCESSIBILITY

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  13. RITY
    PRIVACY
    SAFETY
    LOCALIZATION
    DIV
    SECURITY
    ESPONSIBILITY
    ETHICS
    DIVERSITY
    S
    PRIVACY
    SAFETY
    PRIVA
    ETHICS
    ACCESSIBILITY

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  14. RITY
    PRIVACY
    SAFETY
    LOCALIZATION
    DIV
    SECURITY
    ESPONSIBILITY
    ETHICS
    DIVERSITY
    S
    PRIVACY
    SAFETY
    PRIVA
    ETHICS
    ACCESSIBILITY

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  15. “if your algorithm results in credit
    discrimination against a protected
    class, you could find yourself
    facing a complaint alleging
    violations of the FTC Act and ECOA.”
    Safety

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  16. RITY
    PRIVACY
    SAFETY
    LOCALIZATION
    ACCESSIBILITY DIV
    SECURITY
    ESPONSIBILITY
    ETHICS
    DIVERSITY
    S
    PRIVACY
    SAFETY
    PRIVA
    ETHICS

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  17. Keep people and data secure
    Security

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  18. RITY
    PRIVACY
    SAFETY
    LOCALIZATION
    ACCESSIBILITY DIV
    SECURITY
    ESPONSIBILITY
    ETHICS
    DIVERSITY
    S
    PRIVACY
    SAFETY
    PRIVA
    ETHICS

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  19. Success for XR experiences means
    understanding your demographics, and
    implementing solutions that are
    objectively inclusive for all users.
    Diversity

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  20. RITY
    PRIVACY
    SAFETY
    LOCALIZATION
    ACCESSIBILITY DIV
    SECURITY
    ESPONSIBILITY
    ETHICS
    DIVERSITY
    S
    PRIVACY
    SAFETY
    PRIVA
    ETHICS

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  21. Emergent classes of data to protect privacy
    Proprioception, Hearing,
    Sight, Touch, Preferences,
    and Interests
    Biometrically
    Inferred Data
    Place of birth
    Mother's maiden name
    Scanned people places or
    things, Race
    Sensitive
    Information
    Demographic info,
    Medical histories
    Lab results
    Insurance information
    Protected
    Health Info
    Names
    Email addresses
    Location data, In-world
    activity, Banking info
    Personally
    Identifiable Info

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  22. Emergent classes of data to protect privacy
    Proprioception, Hearing,
    Sight, Touch, Preferences,
    and Interests
    Biometrically
    Inferred Data
    Place of birth
    Mother's maiden name
    Scanned people places or
    things, Race
    Sensitive
    Information
    Demographic info,
    Medical histories
    Lab results
    Insurance information
    Protected
    Health Info
    Names
    Email addresses
    Location data, In-world
    activity, Banking info
    Personally
    Identifiable Info

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  23. “We shape our tools
    and thereafter our
    tools shape us”
    ~Father John Culkin (1964), SJ, Professor of Communication, Fordham University

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  24. Tools can be
    used for
    evil

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  25. ...they can
    also be used
    for good

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  26. 03.
    02.
    01.
    ACKNOWLEDGEMENTS
    Assets and
    Resources
    XRSI Privacy Framework
    Icons by Flaticon
    Adapted template from SlidesGo
    Standards and
    regulations
    2002 EU ePrivacy Directive
    General Data Protection Regulation
    NIST Privacy Framework
    Individuals
    who inspire
    Dr. Ann Cavoukian
    Mike Alger - Google/Youtube
    Kent Bye - Voices Of VR Podcast
    Kavya Perlman,
    Marco Magnano,
    Alina Kadlubsky, and team!

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  27. THANKS!
    @nobleackerson
    @nobleackerson
    @stigsfoot
    /c/nobleackerson
    3 C's for Privacy and Trust by Noble Ackerson is licensed under a
    Creative Commons Attribution-NonCommercial 4.0 International License.

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