2009 RiseoftheRobotsTheFutureofArtif

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Subject Headings: Human-level AI.

Notes

  • This article was originally printed in the 2008 Scientific American Special Report on Robots. It is being published on the Web as part of ScientificAmerican.com's In-Depth Report on Robots.

Cited By

Quotes

Abstract

By 2050 robot "brains" based on computers that execute 100 trillion instructions per second will start rivaling human intelligence

Introduction

Fast Replay

Plans are afoot to improve, extend and miniaturize our techniques so that they can be used in other applications. On the short list are consumer robot vacuum cleaners. Externally these may resemble the widely available Roomba machines from iRobot. The Roomba, however, is a simple beast that moves randomly, senses only its immediate obstacles and can get trapped in clutter. A Seegrid robot would see, explore and map its premises and would run unattended, with a cleaning schedule minimizing owner disturbances. It would remember its recharging locations, allowing for frequent recharges to run a powerful vacuum motor, and also would be able to frequently empty its dust load into a larger container]].

Commercial success will provoke competition and ac­celerate investment in manufacturing, engineering and research. Vacuuming robots ought to beget smarter cleaning robots with dusting, scrubbing and picking-up arms, followed by larger multifunction utility robots with stronger, more dexterous arms and better sensors. Programs will be written to make such machines pick up clutter, store, retrieve and deliver things, take inventory, guard homes, open doors, mow lawns, play games, and so on. New applications will expand the market and spur further advances when robots fall short in acuity, precision, strength, reach, dexterity, skill or processing power. Capability, numbers sold, engineering and manufacturing quality, and cost-effectiveness will increase in a mutually reinforcing spiral. Perhaps by 2010 the process will have produced the first broadly competent “universal robots,” as big as people but with lizard-like 20,000-MIPS minds that can be programmed for almost any simple chore.

Like competent but instinct-ruled reptiles, first-generation universal robots will handle only contingencies explicitly covered in their application programs. Unable to adapt to changing circumstances, they will often perform inefficiently or not at all. Still, so much physical work awaits them in businesses, streets, fields and homes that robotics could begin to overtake pure information technology commercially.

A second generation of universal robot with a mouselike 100,000 MIPS will adapt as the first generation does not and will even be trainable. Besides application programs, such robots would host a suite of software “conditioning modules” that would generate positive and negative reinforcement signals in pre­defined circumstances. For example, doing jobs fast and keeping its batteries charged will be positive; hitting or breaking something will be negative. There will be other ways to accomplish each stage of an application program, from the minutely specific (grasp the handle underhand or overhand) to the broadly general (work indoors or outdoors). As jobs are repeated, alternatives that result in positive reinforcement will be favored, those with negative outcomes shunned. Slowly but surely, second-generation robots will work increasingly well.

A monkey-like five million MIPS will permit a third generation of robots to learn very quickly from mental rehearsals in simulations that model physical, cultural and psychological factors. Physical properties include shape, weight, strength, texture and appearance of things, and ways to handle them. Cultural aspects include a thing’s name, value, proper location and purpose. Psychological factors, applied to humans and robots alike, include goals, beliefs, feelings and preferences. Developing the simulators will be a huge undertaking involving thousands of programmers and experience-gathering robots. The simulation would track external events and tune its models to keep them faithful to reality. It would let a robot learn a skill by imitation and afford a kind of consciousness. Asked why there are candles on the table, a third-generation robot might consult its simulation of house, owner and self to reply that it put them there because its owner likes candlelit dinners and it likes to please its owner. Further queries would elicit more details about a simple inner mental life concerned only with concrete situations and people in its work area.

Fourth-generation universal robots with a human-like 100 million MIPS will be able to abstraction task\abstract and generalize. They will result from melding powerful reasoning programs to third-generation machines. These reasoning programs will be the far more sophisticated descendants of today’s theorem provers and expert systems, which mimic human reasoning to make medical diagnoses, schedule routes, make financial decisions, con­figure computer systems, analyze seismic data to locate oil deposits, and so on.

Properly educated, the resulting robots will become quite formidable. In fact, I am sure they will outperform us in any conceivable area of endeavor, intellectual or physical. Inevitably, such a development will lead to a fundamental restructuring of our society. Entire corporations will exist without any human employees or investors at all. Humans will play a pivotal role in formulating the intricate complex of laws that will govern corporate behavior. Ultimately, though, it is likely that our descendants will cease to work in the sense that we do now. They will probably occupy their days with a variety of social, recreational and artistic pursuits, not unlike today’s comfortable retirees or the wealthy leisure classes.

The path I’ve outlined roughly recapitulates the evolution of human intelligence — but 10 million times more rapidly. It suggests that robot intelligence will surpass our own well before 2050. In that case, mass-produced, fully educated robot scientists working diligently, cheaply, rapidly and increasingly effectively will ensure that most of what science knows in 2050 will have been discovered by our artificial progeny!

References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2009 RiseoftheRobotsTheFutureofArtifHans MoravecRise of the Robots--The Future of Artificial Intelligence2009