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The growing need to optimize for machines

The growing need to optimize for machines

~10 mins. Presented at John Hopkins University Innovation Factory Summit 2017

Noble Ackerson

March 25, 2017
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  1. Optimizing for machines
    in a Ubiquitous Computing World

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  2. Hi, I am Noble.
    Publicity chair Ubicomp & International Symposium on Wearable Computers (ISWC)
    Award winning startup founder, LynxFit
    Product Executive @ Dublabs

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  3. Overview
    ● Optimizing for Ubicomp: Human Interfaces, Security, & Data
    ○ Definitions
    ○ HCI principles: Simplicity, Contextual, Timely
    ● The promise of ubiquitous computing
    ○ Example benefit: how sensors helps first responders
    ○ Example risk: mirai & vulnerable connected devices
    ● Interoperability, Security, & Privacy
    ○ Security/privacy first approach to development
    ● Big Data Integrity, Statistical Modeling & Algorithms
    ○ Shoutout: Weapons of Math Destruction by Cathy O'Neil
    ● Conclusions/Lessons learned

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  4. Definitions
    Ubiquitous computing (or "ubicomp") is a concept where
    computing is made to appear anytime and everywhere.
    Falls to the background and only available when you need it.

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  5. Optimize for the human first
    “Start with the problem and work back to the technology”
    ~ Steve Jobs

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  6. Key principles when optimizing for humans (HCI)
    Simple

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  7. Key principles when optimizing for humans (HCI)
    Simple Contextual

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  8. Key principles when optimizing for humans (HCI)
    Simple Contextual Timely

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  9. First responders & IOT
    Sensors sending context aware, timely
    information in an intuitive way in a mission
    critical situation.

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  10. Risks, & where
    we are today
    ● Guidance, legal, and the
    role of government
    ● Uber example
    ● Mirai example

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  11. Key principles when optimizing for machines
    Interoperability

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  12. Key principles when optimizing for machines
    Interoperability Security & Privacy

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  13. Key principles when optimizing for machines
    Interoperability Security & Privacy Data integrity

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  14. Conclusions
    “How do we start to regulate the
    mathematical models that run more
    and more of our lives? I would suggest
    that the process begin with the
    modelers themselves. Like doctors,
    data scientists should pledge a
    Hippocratic Oath, one that focuses on
    the possible misuses and
    misinterpretations of their models.”
    Weapons of Math Destruction
    Cathy O'Neil

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  15. medium.com/@nobleackerson
    twitter.com/nobleackerson

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