Perspectives on the Digital Transformation

Preston McAfee Perspectives on the Digital Transformation • Former Microsoft Chief Economist • Exec at Yahoo!, Google • PhD Purdue 1980, BA U FL 1976 • Co-Designer, US spectrum auctions • Author, 100+ articles • Auctions, pricing, strategy, CS, antitrust

• Editing: Am. Econ. Rev., JET, TEAC, Econ. Inquiry • Free text: Introduction to Economic Analysis • Professor at CalTech, UTexas, Chicago, MIT, UWO • Testimony: Exxon-Mobil, BP-Arco, Rambus, Peoplesoft-Oracle, US Congress

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Digital Transformation Cheap Sensors

Cheap Data Storage

Wireless

= Ubiquitous Automation

Machine Intelligence

Vignettes • Sensors in fields direct irrigation, pesticides • X-Ray, MRI analyzed by machines • Melanoma app available now

• Deep Fakes produce convincing, false video • Driving behavior, alertness monitored by OBD2 • Insurance rates determined by behavior

• Police dispatched to warehouse by video monitoring

Technological Acceleration 1.

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Mobility (devices, data, intelligence) IoT (ubiquitous comms, cheap chips) Cloud (VLS computing) Machine intelligence Big data Mobile payment systems Personalization Voice control, conversational Virtual reality Silicon photonics Software writing software 3-D printing Wearables & quantified self Cyber attacks

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Online markets Lightweight, low altitude satellites Drones Native advertising Driverless vehicles Robotics, industrial automation Adaptive, gamified education Near-instant product delivery Freelance employment model Assetless company Nano-machines Genomics Economical solar, wind, tidal power Blockchain Quantum computing

What is Coming?

• New markets • Uber is just the beginning

• New organizations • Delve is just the beginning

• New contracting • Intelligent measurement

• New jobs

What is Coming?

• New markets • Uber is just the beginning

• New organizations • Delve is just the beginning

• New contracting • Intelligent measurement

• New jobs

New Markets • Energy • Spectrum/connectivity • Real time, on demand, imaging (drone, satellite) • Transportation • Education • Employment • Virtual companies • Professional services • Simple tasks (dog-walking) • Shopping

What is Coming?

• New markets • Uber is just the beginning

• New organizations • Delve is just the beginning

• New contracting • Intelligent measurement

• New jobs

Changing Employment to Non-Routine

http://www.dallasfed.org/assets/documents/research/eclett/2014/el1405.pdf

Human Supply Chain Optimization Change business practices much more quickly Change employee, resource assignments Create new, virtual teams or virtual companies Rapidly prototype new products Launch web-based channel and scale as needed

What is Coming?

• New markets • Uber is just the beginning

• New organizations • Delve is just the beginning

• New contracting • Intelligent measurement

• New jobs

New Contracting Methodologies • New signals and measurement • Insurance rates depend on driving behavior

• AI • Predict salesperson success, determine compensation

• Auctions and bidding • e.g. crowd-sourced logo

• Price discrimination • Based on time of day, day of week • Geography • Other purchases • AI-based models

What is Coming?

• New markets • Uber is just the beginning

• New organizations • Delve is just the beginning

• New contracting • Intelligent measurement

• New jobs

Complements and Substitutes • A complement makes something more valuable • Xbox and controller

• One person with a bulldozer does the work of hundreds

with shovels • Initially reduces employment of diggers • Drives up wages: requires greater skill • Cost of earth-moving falls • More earthmoving • Employment may go up or down

Substitutes Cotton Gin Adding machine in restaurant • Substitutes for math skills • Reduces skill level • Wages fall, employment rises

Word processing • Reduced secretarial wages

Printing press • Substituted for calligraphy • But lowered cost of skill acquisition

Effects on Wages “Deskilling”

Machines complement skills

Machines substitute for skills

Is AI a substitute or complement?

1750-1900

1875-1980

1980-2010

2010-2050

• Machines + low skilled workers substituted for skilled artisans • Pin factory, Cotton gin • Wages flat or fall, increasing inequality

• Bulldozer, assembly line, services

• Wages flat for bottom 60%

• Middle-class wages rise, decreasing inequality

• Widening skill gap, “college premium,” increasing inequality • Increasing “underemployment”

AI: Substitute or Complement?

Complements – increase wages • Office automation • Design tools, 3-D printers,

Substitutes – decrease wages/increase inequality • Turbo-Tax • Medical diagnostics • Driverless shuttle bus

Technologies: Substitutes and Complements 1.

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Mobility (devices, data, intelligence) IoT (ubiquitous comms, cheap chips) Cloud (VLS computing) Machine intelligence Big data Mobile payment systems Personalization Voice control, conversational Virtual reality Silicon photonics Software writing software 3-D printing Wearables & quantified self Worsening cyber attacks

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Online markets Lightweight, low altitude satellites Drones Native advertising Driverless cars Robotics, industrial automation Adaptive, gamified education Near-instant product delivery Freelance employment model Assetless company Nano-machines Genomics Economical solar, wind, tidal power Blockchain Quantum computing

Strategic Technology?

• Chinese investing heavily at national level in AI, space technology,

green energy, high speed rail, and medical technology • The US has enjoyed a continuing advantage through federal funding of universities • NSF, NIH, DoD, NASA

• The advantage is deteriorating • China publishes 50% more cited AI papers

• Research undersupplied by markets

Thank You!