Jerry Sheehan discusses the increasing pace of technological change and its effects. He notes that technology allows more complex systems to be created and for changes to have global impacts. However, it is unclear if systems are in place to deal with rapid, widespread technological change. Sheehan uses examples like cyberwarfare, artificial intelligence, and distracted learning to illustrate how technology is accelerating change in unpredictable ways.

1. Technology, Complexity & Change:
The Creative Frictions of the Present
Jerry Sheehan, Vice President and Chief Information Officer,
Montana State University
Sponsored Talk for Program for Learning and Community Engagement: Science and Technology, September 28, 2017

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Complicated and Complex
Complicated
Predictable
Complex
Unpredictable

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Agenda for Today
• Framework for Contemplating Technological Change
• How Fast is Fast, A Few Examples
• Case Studies of Accelerated Change and
Accompanying Complexity
• CyberWar
• Artificial Intelligence, Machine and Deep Learning
• The Distracted Mind and the iGeneration

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G-Forces and Speed
• G-Forces, where G stands for
gravitational is a measurement
of acceleration that causes a
perception of change of weight.
• You have likely often heard the
term before:
• 0G-no perception of weight
as in space.
• 3G space shuttle during
launch and reentry.
• Humans can only take so much
acceleration before our systems
fail.
Source: https://www.aviationcv.com/aviation-blog/2016/2721
Source: xkcd.com, https://what-if.xkcd.com/116/

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Thesis
• Technology is Increasing the Pace of Change and
Allowing More Complex Systems to Be Created
• Complex Systems Are Networked, This Allows
Technological Changes to Have Global Impact
• It Isn’t Clear We Have Developed Systems in Place to
Deal with Rapid Change and Global Breadth of
Technologically Inspired Change
• Could, Should We Be Thinking About a Change-Force,
How Quickly Can Humans Change?

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Computational Processing Power
Source: Experts Exchange, http://pages.experts-exchange.com/processing-power-compared/

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Technology Enabled Explosion in Content
Data assembled by PresentationLoad, https://www.presentationload.com

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The Speed of Technology Diffusion Has Accelerated

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How Much Do We Use Technology

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The Pace of Change is Different Now

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Example One: CyberWar

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CyberWar Definitions
• Cyber Warfare: Cyber warfare involves the actions by a nation-state or international
organization to attack and attempt to damage another nation's computers or
information networks through, for example, computer viruses or denial-of-service
attacks.
• [Source: Rand Corporation]
• Plausible Deniability-”n. Polit. (the possibility of) denying a fact (esp. a discreditable
action) without arousing suspicion; the method of achieving this.
• [Source: Oxford English Dictionary]
• Distributed Denial of Service (DDOS) Attack-”A Distributed Denial of Service
(DDoS) attack is an attempt to make an online service unavailable by overwhelming it
with traffic from multiple sources.”
• [Source: Arbor Networks]
• BotNet-”A botnet is an interconnected network of computers infected with malware
without the user's knowledge and controlled by cybercriminals.”
• [Source: Kaspersky.Lab]

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Web War 1: Estonia, 2007
Source: http://www.dailydot.com/layer8/web-war-cyberattack-russia-estonia

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Botnets
Source: Infographic from PresentationLoad, 2016

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The Estonian Ping of Death
Source: Infographic from GlobalDots

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The Fear of a More Nuclearized Middle East
1981 Operation Opera

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StuxNet
Source: http://www.nytimes.com/interactive/2012/06/01/world/middleeast/how-a-secret-cyberwar-program-worked.html

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Retaliation from StuxNet?

19. Image from Robohut: http://robohub.org/wp-content/uploads/2017/02/grid-AI.jpg
Example Two: Artificial Intelligence (AI)

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Artificial Intelligence, Machine Learning, Deep Learning
Artificial Intelligence
Deep Learning
Machine Learning
Source: https://www.qualcomm.com/news/onq/2017/09/01/whats-difference-between-artificial-intelligence-machine-learning-and-deep?cmpid=brfyus1735082

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Eras of Artificial Intelligence, Machine Learning, and
Deep Learning
Source: What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning, July 29, 2016, Michael Copeland
https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/

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The Smile Algorithm
Javier Movellan, University of California, San Diego

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AI Saves A Life: One Machine, 20 Million Studies

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Machines Are Better Than Man @ Pattern Recognition

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AI Detects Suicidal Ideation

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AI Will Save Lives on American Highways

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AI Beats Us At Our Own Games

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AI Learns to Talk

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Humans Have Biases

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What If We Don’t Know How AI Works?

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Training Data Can Bias AI

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What if Machine Bias Kept You In Jail?

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AI and Faking the Future
https://www.facebook.com/verge/videos/1569064539796550/

34. And One More Thing…
Image courtesy of JazJaz at Flickr, https://www.flickr.com/groups/jazjaz/pool

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We Have Been Developing For A While

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Let’s Think about a Watering Hole for a Moment

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Humans Don’t Multitask
Source: https://i1.wp.com/www.learningspy.co.uk/wp-
content/uploads/2017/01/Screen-Shot-2017-01-23-at-12.32.20.png

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Are Our Minds Able to Deal with Our Technologies?

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The iGeneration

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Higher Education Isn’t Sure What to Do

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Logging In and Zoning Out in the Classroom

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Washington State, e-DUI Law
Source: http://getsafeharbor.com/new-driving-law-coming-to-wa-july-23/