cacrltech/Publications/annreps/annrep92/schutt.html

1. The Economics of Brain Simulations Robin Hanson Dept. Economics George Mason U. http://www.cacr.caltech.edu/Publications/annreps/annrep92/schutt.html

2. World Product, 1930-2000

3. World Product, 1-2000

4. World Product, 10K BC-2K AD

5. World Product, 2 Million BC+

6. Bigger Brains Millions of Years

7. World Product Growth Rate Could It Happen Again? Industry Farming Hunting Brains

8. Growth Mode Statistics Sample transition Year Growth

9. Space

10. Fusion

11. Nanotechnology

12. Artificial Intelligence

13. Human Intelligence

14. Industry Shares of US GDP

15. Factor Shares of Income

16. Economics of Robots • Staple of fiction – ancient legends to TV now • Sloppy social analysis • Machine as Substitute (Ricardo 1821) • Wages fall to machine cost • Automation as Complement (Wicksell 1923) • Wages have risen as automation cost have fallen • Both: tasks complement, agents task-compete

17. Human Advantage Useful Mental Tasks A Rising Tide

18. Human Advantage Various Mental Tasks A Rising Tide

19. Human Level Robots Require • Sensors/Actuators (arms, eyes, etc.) now • Processors <~2040 • Software ?? • Direct code it? Hard! • Learn from brain organization? Eventually? • Simulate particular human brain? Can forsee!

20. What Need To Simulate Brains • Computer (very parallel task) • Scan - freeze, slice, 2D scan • Model each brain cell type

21. Brain Simulation Implications • Concerns: • “Is it conscious; is it me?” (enough will volunteer) • Alienation & identity theft • Huge inequality in body abilities, mental speed • Cheap: immortality, travel, tech transfer • Cheap: copies • Wages may fall to (fast-falling) simulation cost • Malthusian population explosion of simulations • Very fast economic growth – a hyper Moore’s Law • Ordinary humans rich if have non-wage wealth

22. World Product Growth Rate Could It Happen Again? Industry Farming Hunting Brains

23. A Fog of Future Possibilities To Deal With: • Seek big, robust, sharp change • Combine expert knowledge of economics, neurology, computers • Beware: experts in A with newspaper level knowledge of B.

24. Expert Assessments to Combine • Many: a mind is the behavior of a brain • Neurology: brains are robust signal processors • Computer science: robust signal processors can be effectively simulated on computers • Artificial Intelligence: Eventually, but progress slow, revolution unlikely, collect knowledge key • Economics: cheap brain substitutes lower wages, raise growth rates, are net benefit, huge change • Ethics (?): what mostly matters is how many minds are happy, get what they want

25. PaleoDemography • DeLong 98 follows Kremer 93 in using Deevey 60 est. • I substitute Hawks et al. 00, who posit exp. pop. growth from ~10K 2MYA. • Based on Multi-regional model (vs. Out of Africa) • 2MYA - simul., signif. new size, pelvis, brain, teeth, … • DNA says inbreeding pop ~10K, before 1.5MYA

26. Error 9.6% 2.0% 1.7%

28. Forecasting The Next Mode Sample growth rate transition Transition date

29. A Simple Robot Growth Model Assume constant: Seek These

30. Switch Between Growth Modes Exogenous Tech Endogenous Tech Pre-Robot Post-Robot Learning by doing:

31. 100x Faster Growth Isn’t Crazy Slow Mid Fast

32. Simulating Dominos • Wave speed, energy are robust • Only a few details matter • Devices, brains similar