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Economics of Economics of A.I. A.I. Robin Hanson George Mason University

Economics of A.I. Robin Hanson George Mason University

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Page 1: Economics of A.I. Robin Hanson George Mason University

Economics of A.I.Economics of A.I.

Robin Hanson

George Mason University

Page 2: Economics of A.I. Robin Hanson George Mason University

A Fog of Future Possibilities

To Deal With:• Focus on big, robust,

sharp changes• Combine expert

knowledge from several fields

• Beware: experts in A with newspaper level knowledge of B.

Page 3: Economics of A.I. Robin Hanson George Mason University

Types of Views

Page 4: Economics of A.I. Robin Hanson George Mason University

A.I.-Econ View Combos

A.I.A.I.

Amateur

Amateur

Expert

Expert

Page 5: Economics of A.I. Robin Hanson George Mason University

Social Science Exists!!

Once Express Tech in Econ Terms, Can Say

• Tech’s social implications– Given weak regulation – Given particular strong regulation

• Likely regulations, given political climate– Likely political climates

• Social support of tech innovations

• Tech innovations given social support

✔✔✔

✔✔✔✔✔

✔✔✔

✔✔✔

Page 6: Economics of A.I. Robin Hanson George Mason University

Econ Terms

• Utility Functions – what folks want– Like outputs, e.g. ,products, services– Dislike give up inputs, e.g., effort, time

• Production Functions - outputs from inputs

• Endowments – base inputs, e.g. abilities

• Info - who knows how much about what

• Deals - trades allowed, contracts enforced

Page 7: Economics of A.I. Robin Hanson George Mason University

Economics of Robots

• Staple of fiction – ancient legends to TV now• If have more of X, do you want Y more (complement)

or less (substitute)?• Machine as Substitute to human labor

– Predicts wages fall to machine cost– Ricardo 1821, most science fiction

• Automation as Complement to human labor– Predicts wages rise as automation costs fall– Wicksell 1923, modern economics consensus

• So are robots a substitute or complement?

Page 8: Economics of A.I. Robin Hanson George Mason University

Robots Substitute On Task, But Tasks Are Complements

Hum

an A

dvan

tage

Useful Mental Tasks

SubstituteFor Task

HumansDo These

MachinesDo These

Tasks AreComplements

Page 9: Economics of A.I. Robin Hanson George Mason University

A Rising Tide

Hum

an A

dvan

tage

Useful Mental Tasks

Page 10: Economics of A.I. Robin Hanson George Mason University

A Rising Tide

Hum

an A

dvan

tage

Useful Mental Tasks

Page 11: Economics of A.I. Robin Hanson George Mason University

A Simple Robot Growth Model

PgIIYRHHL

RMPKCHMKLAY

PK )( Y, ,ˆ

)(ˆ

M

Igggg YPAH ,,,,Assume constant:

HMKLAY gggggg )1(

PYYML

HYYML

gggRYY

gggRYY

ML

L

,0 ,

,0 ,

Y

Y

g

g

ˆSeekThese

Page 12: Economics of A.I. Robin Hanson George Mason University

Switch Between Growth Modes

1

) ( ˆ

1

)(

PHAY

PHAY

gggg

gggg

tt

ssMbtPssYatA d )()( ,d)()(

)1/()(1

)1/(1

H

H

g

g

Exogenous Tech Endogenous Tech

Learning by doing:

Pre-Robot

Post-Robot

Page 13: Economics of A.I. Robin Hanson George Mason University

100x Faster Growth Isn’t Crazy

000 DT LateTech All Endog.00148. DT LateTech Genl. Endog.261.27.222.7 DT LateTech Exogenous

9.143.157.17Time nguct DoubliEarly Prod35.35.35.)(- FallriceComputer PEarly 01.015.025.)( Growth Tech GeneralEarly 015.015.02.)( Growth Annual Population015.015.025.)( Share Human005.01.005.)( ShareComputer 64.5.25.)(Share Capital31.2.1.)( ShareLabor

P

A

H

gg

g

Slow FastMid

Page 14: Economics of A.I. Robin Hanson George Mason University

Error9.6%

2.0%

1.7%

Page 15: Economics of A.I. Robin Hanson George Mason University

1.E-8

1.E-7

1.E-6

1.E-5

1.E-4

1.E-3

1.E-2

1.E-1

1.E+0

1.E+1

1.E+2

1.E+01.E+11.E+21.E+31.E+41.E+51.E+61.E+71.E+81.E+9

Years before 2050

Annu

al G

row

th R

ate

World Product Growth Rate

Could It Happen Again?

Brains

Hunting

Farming

Industry

Page 16: Economics of A.I. Robin Hanson George Mason University

Growth Mode Statistics

Page 17: Economics of A.I. Robin Hanson George Mason University

Forecasting The Next Mode

2039 2040 2041 2042 2043 2044 2045 2046 20476.1% 6.1% 6.6% 8.0% 14.0% 40.5% 147.3% 476.2% 1023.2%

Sample growth rate transition

DateRate

Page 18: Economics of A.I. Robin Hanson George Mason University

Industry Shares of US GDP

Construction

Communications

Wholesale trade

Retail trade

ManufacturingFinance, insurance, real

estate

Services

Government Transportation

Electric, gas, trash

Mining

Farming, forestry, f ishing

Page 19: Economics of A.I. Robin Hanson George Mason University

Factor Shares of Income

Labor

Human Capital

Other Non-Human Capital

Stock Dividends Natural Resources

Page 20: Economics of A.I. Robin Hanson George Mason University

Cheap For Robots

• Immortality (even so, most can’t afford)• Travel – transmit to new body• Nature – don’t need ecosystems• Wildly differing bodies• Widely varying mental abilities – e.g., run speed• Survive in severe environments

– Backups insure against severe events

• Labor – work gets less tool intensive

Page 21: Economics of A.I. Robin Hanson George Mason University

Copies Become Cheap

• Malthusian population explosion– Makes rapid economic growth

• Robot wages fall to hardware cost– And hardware costs fall fast too– Human wages may fall to robot wages

• Depends on human-robot task landscape shape• Not matter if robots slave or free

– Only Draconian population or wage laws could stop

Page 22: Economics of A.I. Robin Hanson George Mason University

Humans Eclipsed

• Wages well below human subsistence– Though some humans may find servant jobs

• But rich if held non-wage assets– Investments double as fast as economy!

• Robot-Human war unlikely if integrated– E.g., lefties don’t war against righties

Page 23: Economics of A.I. Robin Hanson George Mason University

Human Level Robots Require

• Sensors/Actuators (arms/eyes) ~now

• Processors <~2040

• Software ??

– Direct code it? Hard!

– Learn from brain organization? Eventually?

– Simulate particular human brain? Can Do!

Page 24: Economics of A.I. Robin Hanson George Mason University

Needed To Emulate Brains

1. Model each brain cell type

2. Scan – freeze, slice, 2D scan

3. Computer (very parallel task)

Page 25: Economics of A.I. Robin Hanson George Mason University

Simulating Dominos

• Wave speed, energy are robust

• Only a few details matter

• Brains seem similar

Page 26: Economics of A.I. Robin Hanson George Mason University

Emulations Feel Human

• Most emulations are of few best humans– First mover advantage to show quality

• Remember human life, retain human tendencies– love, gossip, argue, sing, violate, play, work, innovate

• More alienated worlds - as farms, factories were– Office work in virtual reality, – Physical work in android bodies

• Many humans won’t believe conscious, “is me”– But same social implications, few dozen is plenty

Page 27: Economics of A.I. Robin Hanson George Mason University

More Implications

• Copies rent bodies, or own on loan– Evicted if can’t pay!!

• To recoup training investment, copy cabal limit copy wage– Security to prevent bootleg copies

• Fast growth discourages transport, encourages local production

• Laws hold copies co-responsible

• <1cm robots seem feasible– Mind/body sped up with size reduction– 0.2in. tall => Subjective year/day in 24hr/4min

• One skyscraper holds billions - is megacity– City radius now is hour travel distance =>

10sec

Page 28: Economics of A.I. Robin Hanson George Mason University

Time Line

• IP rights secure?• Regulation fears?• Second mover better? • Secrets leak fast?• What products drive?

• Rights of Emulation• Govt. Slow or Speed?• What tech ready last?

– Computer –> gradual– Sim/Model –> sudden

For-Profit ResearchAnd Development

Sell, Maintain, UseNon-Profit Research

Page 29: Economics of A.I. Robin Hanson George Mason University

World Product, 10K BC-2K AD

0.001

0.010

0.100

1.000

10.000

100.000

1,000.000

-10000 -8000 -6000 -4000 -2000 0 2000

Year

Wo

rld

Pro

du

ct (

su

bs

iste

nce

bill

ion

s) Singularities!

Page 30: Economics of A.I. Robin Hanson George Mason University

10,000

100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

10,000,000,000

100,000,000,000

1,000,000,000,000

-2000000 -1500000 -1000000 -500000 0 500000

Year

Wor

ld P

rodu

ct (s

ubsi

sten

ce h

uman

s)

World Product, 2 Million BC+

Page 31: Economics of A.I. Robin Hanson George Mason University

0.001

0.01

0.1

1

10

-600 -500 -400 -300 -200 -100 0

Re

lati

ve

Bra

in S

ize

Millions of Years

Bigger Brains

Page 32: Economics of A.I. Robin Hanson George Mason University

Modeling Exponential Sequences

iii

i

aai

aii

tii

tMtYtY

tYtYctM/1

1

/

))()(()(

)()( 2)(

)(/)(

)()(:

1 /

11

1

1

iiii

iiiii

ii

dYdY

dMdMd

ExponentialModes

CES Combined

Doubling Time Factor

1st Date Mode Biggest

World Product Factor

Method: Min2))log())((log( j

jj YtY

Page 33: Economics of A.I. Robin Hanson George Mason University

Outline

• Economic capacity drives tech, wartech

• World long-term econ trend mostly steady– Now doubles in ~15 years

• So far have seen 2-4 “singularities” when– World econ growth rate increased x150-250– In much less than a previous doubling time

• Next?: by 2100, takes 5 yr, double monthly

• Candidate driver: whole brain emulation

Page 34: Economics of A.I. Robin Hanson George Mason University

Emulation Supply & Demand

Quantity

PriceNow

Value

Cost

Quantity

PriceLater?

Net

CostValue

Page 35: Economics of A.I. Robin Hanson George Mason University

Kinds of Costs

• Design• Build• Maintain• Repair• Security

• Material• Energy• Capital• Labor• Time Delay

• Any brain• Per brain• Per copy• Scale• Scope

Kinds of Strategy• Lockin• Standards

• Price Discrim.• Bundle

• Lease/Buy• Differentiate

Page 36: Economics of A.I. Robin Hanson George Mason University

Kinds of Quality

• Speed

• Weight

• Portability

• Reliability

• Durability

• Power needs

• Environs handle

• Security

• Nearness to human behavior, feeling

• Improve: memory, interface range, bandwidth