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Artificial Intelligence & BusinessPresentation to: Analytics & Technology Summit, Wilmington, DERod.Wallace@Design-Economics.netSeptember 22, 2016

Copyright Design Economics, llc 2016. All rights reserved.

Special thanks to Dr. Steve Omohundro Chris Vaughn, Ruth Fisher, Lloyd Nirenberg, and Melanie Swan for comments, insight and perspective. Any mistakes remain my own.

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Illustration: Artificial Intelligent Diagnosis(Stylized)

US Medical SchoolRead JournalsAnalyze DataDiagnose

OncologistUS Medical School

Diagnose

OncologistSloan Kettering Hospital

Read JournalsAnalyze DataDiagnose

Artificial Intelligence

Diagnose

Oncologist

(US AI model)

Artificial Intelligence

Thai Hospital

Past Present

Sent To

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Artificial IntelligenceThe science of building machines able to take actions in an environment that will achieve desired outcomes using scarce resources.

Steve Omohundro, Ph.D.

What is Artificial Intelligence

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• 1/3 of Software, IT firms; >$10 billion invested

Google Microsoft IBM Baidu Facebook Intel Amazon Others

• All Auto Companies, Most Agriculture services, misc.

• Most other industries:mainly

leaders (1% of companies) GE Siemens American Express Bloomberg …

Leading Companies Investing in AI

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1,000 Artificial Intelligence Startups

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• What’s Going On?

• Noteworthy Artificial Intelligence Technologies

• Business Implications

Agenda

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Sample Application: Automated Anesthesiologist

Characteristics: Model Built of Sub-Models More / less-detailed variants Parameterized (Leverages ‘IOT’)

An Implicit or Explicit Part of Every Quantitative Analysis

AI: An Inherently Systematic Set of ToolsA Model of the ‘World’: Explicit or Implicit Core of Any Analysis

Applied Mathematical Models in Human Physiology,

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‘What Does a Leaf Look Like?’• Concept is Complex• Different Perspectives• Exceptions• Complicating Factors

Limited human:• Data Entry• Model Building• Data Processing

Develop equations equivalent to human ‘concepts’

AI: Generally Includes Neural Net Approaches Conceptual Handling of High-dimension problems & Automated Modeling

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Neural Networks Basics

0

1

S

Xi = Input from Neuron i

wi = Weight

Do Neurons Fire?

S = 1 is ‘fire’

Learning Data

NeuronsNeuron

Neuron

Neuron

Neuron

Neuron

NeuronNeuron

Neuron

Initial layers respond to sub-elements

Later layers respond to refined concepts

Neuron

Click to Play

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Image Recognition:

• Facebook People• Check, Form Processing• People’s Backs• Series of objects• Recognize Nudity• ID Objects Around Cars• ‘Bin-picking’ > 90% accurate• Catching Liars (better than

humans)• Cancer Detection (ID’ed new

approach)• Create Sound Basis Visual

What Can Neural Networks Do? Image Recognition

Click to PlaySee 10:46

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Natural Language: • Google Translator• Digital Assistants• Legal Research• Academic/ Tech Research• Teaching Assistant• Poetry Writing• Fiction Writing• Movie Script Writing• Writing Tone Improver

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What Can Neural Networks Do? Natural Language

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General Pattern Recognition:

Financial Trading Product Recommending NIH Data Music Development Product System Design, Rec Manage complex physics Winning Conceptual ‘Go’* Design Artwork Jazz Jams ID Embryonic Cell State Generating Speech Brainwaves to Human Faces

Click to Play1:50

What Can Neural Networks Do? MUCH MORE!

* Illustrates ability for computers to think creatively & conceptually

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Clippy the Microsoft Assistant

Seemless Human-Machine Interaction (Driving)

• Cost of Interruption• Response Time• Cost of non-interruption• Surprising Information

Health System Understanding (Not AI)• Reconstruct Metabolic Paths• Cigarette Smoke Exposure• Intra-Cell Biologic Pathways• Decoding the Genome

Diagnosis / Treatment (AI):• Personalized Lung Cancer

Survival and Treatment• Fraud Detection• Psychiatric Illness Diagnosis• Online Self-Diagnostic Tool• Automated Image Annotation• Automated Image Text Rerieval

• Patient-specific drug prescription

AI: Frequently Leverages Statistical & Logical ToolsFor Lower-Dimension Problems (with Uncertainty)

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‘Lights’ for Black Box Models

Emotion Technology

Persuasive Technology

Statistics + Machine Learning

Methods for Volatile Process

Re-application Approaches

Maximizing Outcome Value Objective Function Design Objective Maximization

End-to-end Networks, Focus

Structuring Memory, Info

Anticipation

Select Development Areas

RAPID Ongoing AI Capability Growth

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Artificial Intelligence Limitations

Must Have Engaged, Understanding, Org.Limited to data available Data Quality, Comparability Weak in low-data pockets Over-generalize False-correlations Unclear what is ‘right’ if humans are unclear (NN)Can Break rules & lawsAre Integrated, Static (NN) 1 Change, Changes ALL Unclear change in model vs w/in model uncertainty Miss Reactions to UsTechnical Limitations

Uncertain what they’ll do Problem is shrinking (NN) Re-applyication is challenging Problem is shrinking (NN) Replicable, trickable

(NN) Neural Network Limits

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Artificial Intelligence StrengthsNO incremental cost

Alternate creativity

Customize every output

Fast (can be)

Work anywhere (no body)

Know all we know

Alternate Creativity

Excellent Pattern Recognition

Not Afraid of New / Complex

Leverage computer process, memory improvements

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• What’s Going On?

• Noteworthy Artificial Intelligence Technologies

• Business & Social Implications

Agenda

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Automation

Personnel Strategies becomePersonnel + Machine HR & IT Close Partners

Empower less-skilled;‘Rock stars’ created

Computational Thinking Everywhere Math / Logic critical Interpersonal skills ever more important… for now

Humans and Computers Together: Case of The Movie Industry

Annotated Scene Review

• Analyze Compositions: visual, audio• Recommend 10 trailer scenes probabilistically

• Development time reduction: 10-30 days 3 days

Trailer Production Support

IBM WatsonGoogle Deep Mind

+ Evaluate new projects (accept, reject, budget)+ Identifies screenwriter’s deficiencies

Pacific Aurora Project

(Developer Interview)

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Business Planning and Artificial Intelligence: Case of The Auto Industry

Confusion with Fleet Management• Spent $0.5- 2 BB for Uber, etc. minority shares• Now experimenting w/ internal ‘fleet business’• Fleet economics may be unattractive for many

Massive Autonomous Driving Investment• ‘80%’ is simple; massive, overlapping investment Auto industry, tech industry, entrepreneurs• Commercial ~2020, adjusted by infrastructure, laws

Re-imagining rider & driver entertainment• Apple spent $5 BB on ‘cars’ R&D• Virtual Reality, augmented reality, & furniture

At stake:3.8 MM Driving Jobs$1 TR / yr people time

At stake:>1 MM auto man. jobsUrban (parking)

At stake:$3-60 BB / Yr Mkting

Revolutionary technology shifts + AI-Sourced (+ others) + Challenging to foresee

Re-defining other industry dynamics Critical to forecast Challenging to forecast

Potentially reversing, dynamic patterns

Require new AI methods & approaches

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Irreplaceable strategic perspective– not just a ‘strategic partner’

Proactive data stewards key to automation plans

Machine Learning / AI algorithm sourcing : Packaged with cloud service? 3rd Party Markets? Internally Developed?

Information Technology: Strategic Data and Service Selection

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Know All We Know, Dream Deep Customer, Business, Competitor Understanding Fully Leveraged

Developing IP Neural Net Techniques Training Data Trained Nets Other ‘Big Data’ Models

Collaborate, Jointly Develop Update ‘Firm’s Meaning

Custom Production ‘Anywhere’ ‘Neural Netted’ Production Specs Generalized Machinery, Robots 3D Printed

Innovation, IP, & Efficiency Re-Defined

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1. Industry leaders and startups driving AI forward

2. Rapid AI progress, using neural nets & other tools + Leveraging growing computer power to learn features + Incredible capabilities– concerning limitations + Need the right data, complementary techniques

3. Key Business Function Thinking is Evolving + Personnel Strategies become People + Machine Plans + Business Planning impacted by New Technology Wave + IT the Source of Strategic Insights + Data, Algorithms require re-defining ‘the firm’ & innovation

Summary

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What Can Neural Networks Do? PredictionAdversarial Networks Create Video from Single Photos

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