Mindless Intelligence
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www.computer.org/intelligent Mindless Intelligence Jordan B. Pollack Vol. 21, No. 3 May/June 2006 This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. For more information, please see www.ieee.org/portal/pages/about/documentation/copyright/polilink.html. The Future of AI Mindless Intelligence Jordan B. Pollack, Brandeis University ost of my 25 years of professional involvement in AI have been focused on M research far from its mainstream, not because of any antisocial tendencies on my part, but because of certain dilemmas inherent in the field. The first dilemma con- fronting AI is that both single-celled and multicelled animals survive and reproduce very well without any nervous system at all, and “lower tems, animals, and humans and has spun out indus- animals,” even insects, organize into thriving soci- tries such as Lisp machines, expert systems, data AI has stalled because eties without any symbols, logic, or language, bee mining, and even Internet search. dancing and birdsong notwithstanding. These phe- of its preoccupation nomena led me to delve into nonsymbolic models Don’t promise the practically and ask how complex hierarchal representations and impossible with simulating the sustained state-changing procedures might naturally We all agree on AI’s fundamental hypothesis, that emerge from iterative numeric systems such as asso- physical machines have the capacity for intelligence. human mind. By ciative or connectionist neural networks. Unfortunately, this hypothesis can neither be proven The second dilemma is that the kind of mind we nor refuted scientifically, but realized only by studying intelligence in AI seek to discover, one that “runs” on the human demonstration. And until it has been convincingly brain yet might be portable to another universal demonstrated, it must remain in scientific limbo. in natural systems, machine, wouldn’t even exist without having co- Ordinary citizens and funding bureaucrats don’t evolved with the brain—a chicken-and-egg problem. know whether AI is tardy, like mechanical flight, outside the mind, we So, while many of my connectionist colleagues which emerged from limbo after several hundred migrated with US National Institutes of Health fund- years of failure, or magical, like ESP or the can reinvigorate the ing into cognitive or computational neuroscience, alchemists’quest to turn lead into gold. Perhaps there trying to understand how the human brain works, I is even an impossibility proof waiting around the cor- field. focused instead on what natural process could design ner, as has put to rest quixotic notions such as time and fabricate machinery as complex as the brain. travel (Einstein) and perpetual motion (Ludwig I ended up working closer to the field of artificial Boltzmann). Who wants to fund a field that might be life, seeking to understand how evolution, a mind- proven impossible tomorrow? less iterative reproduction system, could eventually So AI, which represents one of the greatest intel- lead to machines whose complexity and reliability lectual and engineering challenges in human his- dwarfs the product of the largest teams of human tory—and should command the same fiscal re- engineers. sources as efforts to cure cancer or colonize Mars—is On this 50th birthday of artificial intelligence, I sometimes relegated to a laughingstock, because we would like to reflect on what I feel has been its great can’t prevent bogus claims from cropping up in mistake, and propose a corrective course for the next newspapers and books. We cannot seem to convince 50 years. But before analyzing this mistake, I want the public that humanoids and Terminators are just to say that AI is a great human endeavor with a col- Hollywood special effects, as science-fictional as the orful cast and many partial successes. It has provided little green men from Mars! frameworks for formally studying biological sys- Still, some want to keep pursuing the same old AI 50 1541-1672/06/$20.00 © 2006 IEEE IEEE INTELLIGENT SYSTEMS Published by the IEEE Computer Society goals: “What are the missing pieces neces- associative and matrix models of mathemat- cognitive structures such as verb conjuga- sary to achieving human-level common ical psychology, to Markovian models, to tion. Why is simulating the human mind sense?” “Let’s do a project to gain human- both game and decision theories, to early more important than simulating cellular level performance in a (nonchess) domain.” neural networks (the perceptron disaster), to metabolisms, insect or animal intelligence, “We will build natural language software simulations of evolution and organic self- complex pattern formation, or distributed that’s human-level in ability.” “Soon com- organization. The early success of low-hang- control of complex ecologies? It must be puters will be fast enough to supply human- ing symbolic fruit through Lisp program- because, as a mirror of our own intelli- level intelligence to humanoid robots.” ming led to the pursuit of the “mythical man gence, the mindless iterative and numeric AI won’t be a gift of more CPU time. If it module,” a computer program that has the computing we scientifically uncover in were, we would have already glimpsed real “look and feel” of human cognition yet is nature doesn’t compare to the perfectly log- AI on supercomputers or large clusters, yet something more than an Eliza. ical indefatigable mind of Hollywood char- nothing of the kind has occurred. We don’t John Searle’s “Chinese Room” argument5 acters such as Mr. Spock and Commander need faster chips to make robots smarter, is hateful because, in fact, he’s correct. Nei- Data, NP-completeness notwithstanding. since we can link a robot’s body to its super- ther the room nor the guy in it pushing sym- To repair this mistake and move forward computer brain over wireless broadband. As bols “understands” Chinese. But this isn’t as a scientific field, we must recognize that the joke goes, even if AI requires an infinite really a problem, because nobody actually many intelligent processes in Nature perform loop, it should run in only five seconds on a “understands” Chinese! We only think we more powerfully than human symbolic rea- supercomputer. soning, even though they lack any of the The issue isn’t the speed of running a mind- mind-like mechanisms long believed neces- like program; it is the size and quality of the sary for human “competence.” Once we rec- program itself. Because we routinely underes- The scientific evidence ognize this and start to work out these timate the complexity of evolved biological scaleable representations and algorithms with- systems, and because Moore’s law doesn’t lead coming in all around us is clear: out anthropomorphizing them, we should be to a doubling of the quality of human-written able to produce the kind of results that will software,1 the same old goals are red herrings Symbolic conscious reasoning, get our work funded to the level necessary for that promise the practically impossible! growth and deliver beneficial applications to which is extracted through society, without promising the intelligent Take Mind off its pedestal English-speaking humanoid robot slaves and AI’s great mistake is its assumption that protocol analysis from serial soldiers of science fiction. human-level intelligence is the greatest intel- ligence that exists, and thus, that our com- Defining mindless intelligence putational intelligences should operate “like” verbal introspection, is a myth. I define “mindless intelligence” as intelli- human cognition. Because of this mistake, gent behavior ascribed (by an observer) to most AI research has focused on “cognitive any process lacking a mind-brain. Suppose models” of intelligence, on programs that run understand it. As anyone—even a native some black-box process (for example, math- like people think. But it turns out that we speaker—drives further down into an expla- ematical, numerical, or mechanical) exhibits don’t think the way we think we think! nation of his or her knowledge or behavior, behavior that appears to require intelligence. The scientific evidence coming in all instead of gaining sharper insights (as we However, when we scientifically study it, we around us is clear: Symbolic conscious rea- might expect in a reductionist physical sci- find no Lisp interpreter, no symbols, no soning, which is extracted through protocol ence with a better microscope), the explana- grammars, no logic or inference engine—in analysis from serial verbal introspection, is tions get blurrier and blurrier. fact, we realize that it works without any of a myth. From Michael Gazzaniga’s famous By assuming that intelligences based on the accoutrements of cognition. We can say split-brain experiments, where a patient asso- human-centric cognitive architectures such that this process is mindlessly intelligent. ciated a snow shovel with a chicken,2 through as grammars or production systems are the Now we can begin to seriously study intel- Daniel Dennett’s demolition of conscious- zenith, are the most powerful intelligences ligent performance by ness,3 through the unconscious intelligence in the world, our field has made the same described most recently by Malcolm Glad- kind of embarrassing mistake as today’s • feedback-driven systems such as ther- well,4 it’s entirely clear that the “symbolic cryptocreationists, the proponents of Intelli- mostats and steam governors; mind” that AI has tried for 50 years to simu- gent Design.