The phrase 'artificial intelligence' was first coined by John McCarthy at a conference at Dartmouth College, New Hampshire, in 1956, but the concept of artificial, or machine, intelligence is in fact as old as the computer. The computer was, after all, initially developed during the Second World War to break codes that were too hard for humans and required high speed 'machine intelligence'.
It was one of the most celebrated of the Second World War code breakers, Alan Turing, a man who many would describe as the inventor of the first modern computer, who proposed in 1950 what has become known as the Turing Test. This simply said that we could consider a machine to be intelligent if its responses in some sort of conversation were indistinguishable from those of a human. It is this proposal that is seen by many not only as the definitive test of machine intelligence but also the point at which today's quest to develop artificial intelligence was born.
Three Laws of Robotics
In the early days of computing there had already been a great deal of optimism that machines could be created that would behave intelligently. In 1942 Isaac Asimov put forward his three laws of robotics in the short story Runaround, which was later republished as part of the short story collection, I, Robot. Not long after the book was published, one of the fathers of computing, John von Neumann said, "You insist that there is something that a machine can not do. If you tell me precisely what it is that a machine can not do, then I can always make a machine that can do just that."
This optimism was fuelled over the next few decades by the constantly increasing power and speed of computer hardware and by the success in applying computers to an ever-wider range of human endeavours. Many believed that as the computational power of machines increased they would soon be able to equal the intellectual power of a human being.
It is now over fifty years since the birth of artificial intelligence research, computing power is both fast and cheap, and yet today intelligent machines seem to as far in the future as they were half a century ago. According to those early researchers we should now be surrounded by intelligent machines, is this the case or are we still waiting?
A long road to intelligence
Work on machine intelligence started with chess, and Maniac 1, the first chess program to beat a human player, was demonstrated in 1956 by Stanislaw Ulam at Los Alamos National Laboratory in the US. This was an early success in the quest for machine intelligence that started a long sequence of work on chess-playing computers by many researchers around the world.
In 1966 Joseph Weizenbaum at MIT developed the first computer program capable of engaging in a conversation with a human — Eliza. This clever program was able to hold a seemingly intelligent conversation with a human, and many felt that given enough computer power and a large enough vocabulary these algorithms would make it possible for a machine to meet Turing's test for intelligence.
Shakey, the first robot capable of locomotion, perception and problem solving was built at Stanford Research Institute, California, in 1969. This was followed in 1979 by the Stanford Cart, a computer controlled autonomous robot designed by Hans Moravec of Stanford university that was capable of successfully navigating around a room filled with furniture without bumping into any.
The success of these and other similar experiments in artificial intelligence gave researchers during the 1960s and 1970s the confidence that given enough computing power, and sufficient research funds, they would quite soon be able to develop an algorithm for...
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Talkback
Greetings Nick Hampshire
In response to your ongoing 3-part article on AI, I am writing to
alert you to the newly issued U.S. patent concerning ethical artificial
intelligence titled: Inductive Inference Affective Language
Analyzer Simulating AI (patent # 6,587,846) which is relevant
to your present/future editions of your article.
It introduces the newly
proposed concept of the Ten Ethical Laws of Robotics: a system
which radically expands upon previous ethical-robotic systems. As
implied in its title, this patent represents the first AI system
incorporating ethical/motivational terms: enabling a computer to
reason and speak in an ethical fashion, serving in roles specifying
sound human judgement. These Ten Ethical Laws directly expand upon
Isaac Asimov's Three Laws of Robotics, an earlier Science Fiction
construct that aimed to rein in the potential conduct of a
futuristic AI robot as rules that prohibit harm to come to humans.
Indeed, Asimov's first two laws state that (1) a robot must not
harm a human (or through inaction allow a human to come to harm),
and (2) a robot must obey human orders (unless they conflict with
rule #1). Although this cursory system of safeguards proves
intriguing in a Sci-Fi sense, it nevertheless remains simplistic in
its dictates, leaving open the specific details for implementing
such a system. The newly patented Ten Ethical Laws fortunately
remedy such a shortcoming, representing a general overview of the
enduring conflict pitting virtue against vice: the virtues of which
are initially partially listed below:
Glory/Prudence Honor/Justice
Providence/Faith Liberty/Hope
Grace/Beauty Free-will/Truth
Tranquility/Ecstasy Equality/Bliss
Dignity/Temperance Integrity/Fortitude
Civility/Charity Austerity/Decency
Magnanim./Goodness Equanimity/Wisdom
Love/Joy Peace/Harmony
The Ten Ethical Laws are written in a positive style of formal
mandate, focusing on the virtues to the necessary exclusion of the
corresponding vices. The purely virtuous mode (by definition) is
fully cognizant of the contrasting realm of the vices, without
necessarily responding in kind. Furthermore, the corresponding
hierarchy of the vices listed below contrasts point-for-point with
the respective virtuous mode (the overall patented system is
actually composed of 320 individual terms).
Infamy/Insurgency Dishonor/Vengeance
Prodigal/Betrayal Slavery/Despair
Wrath/Ugliness Tyranny/Hypocrisy
Anger/Abomination Prejudice/Perdition
Foolishness/Gluttony Caprice/Cowardice
Vulgarity/Avarice Cruelty/Antagonism
Oppression/Evil Persecution/Cunning
Hatred/Iniquity Belligerence/Turpitude
With such ethical safeguards firmly in place, the AI computer is
formally prohibited from expressing the corresponding vices,
allowing for a truly flawless simulation of virtue. Indeed, these
Ten Ethical Robotic Laws hold the potential for further
applications to a human sphere of influence.
www.angelfire.com/rnb/fairhaven/ethical-laws.html
Although only a cursory outline of applications is possible at this
juncture, a more detailed treatment is posted at:
www.ethicalvalues.com A direct USPTO link is also found at -
http://patft.uspto.gov/netacgi/nph-Parser?patentnumber=6587846
Sincerely
John E. LaMuth - M. S.
fax: 586-314-5960
P.O. Box 105 Lucerne Valley, CA 92356
http://www.charactervalues.com
A BREAKTHROUGH IN ETHICAL
ARTIFICIAL INTELLIGENCE
Announcing the newly issued U.S. patent
concerning ethical artificial intelligence entitled:
Inductive Inference Affective Language Analyzer
Simulating Artificial Intelligence (patent No. 6,587,846)
by inventor/author John E. LaMuth M. S.
As implied in its title, this innovation is the 1st affect-
ive language analyzer incorporating ethical/motivational
terms, serving in the role of int
"Artificial Intelligence" will always be just that: *Artificial*. The reason is simple: As magnificent as any computer might get, including those in the future which will drive walking, talking, synthetic flesh-bound robots, they will still have as their founding principle the creative work of a Conscious Agent, namely, a Human. A Human can "set off" a highly complex algorithm that does things far beyond that human's imagination or expectations -- like a gradeschooler firing off a nuclear weapon -- but the algorithm will only be doing what was inherent to its CREATED nature... No "artificial intelligence" will ever be a Conscious Agent, capable of Creating anything...
Reasoning Systems
In my opinion, the future of AI is dependent on the extension of the programming paradigm from today’s Boolean logic to incorporate “reasoning models”. Compsim’s KEEL® Technology offers one approach. Only when systems have the opportunity to exercise “reason” will they evolve to the next level (HAL-like). Reasoning is not a sequential process. It is an analog balancing process where inter-related alternatives need to be considered. It requires the production of relative answers and actions in dynamic environments.
I believe there are two competing mindsets driving the future:
First there are researchers with the “mechanism” mindset that use biological models as the foundation for their work in AI. They focus on neural nets and genetic algorithms that will allow applications to learn on their own and evolve on their own. They attempt to model how the human brain functions. Most of the research seems today seems to be focusing on this approach. The risk with these systems is that they may evolve in directions never before expected, even by their designers. If they create human-like reasoning engines, they can evolve in good ways and in bad ways. Just look at humans.
The other mindset assumes that there must be another way to create “reasoning systems”, with the added demand that they must be completely explainable and auditable. Humans must retain control. With this approach one is searching for a solution, but is not tied to the biological model. I call this the “process” mindset.
Without worrying about the technical details about how a human “reasons” or makes “judgmental decisions”, the reasoning process is commonly understood to take place in the human’s right brain. The left brain may focus on language and logic (the domain of most computers today). The right brain performs image processing and makes judgmental interpretation of those images. The images are not necessarily “pictures”, but can be feelings or impressions.
This suggests that text based programming languages do not satisfactorily provide a platform for “reasoning”. Similarly, I would suggest that it is difficult or impossible for humans to explain “exactly” how or why they make judgmental (subjective) decisions. Just watch the news broadcasters attempt to explain why humans do what they do. Or watch CEOs explain why they did what they did.
“Humans”, each perform their own “interpretation” of information. They provide their own weights to supporting and objecting arguments. They fuse the differing viewpoints in different ways. Human language does not allow this “reasoning model” to be effectively exchanged. It is for this reason that (industrial) machines are not commonly controlled with human language terms. They are controlled with numerical settings and formulas that tell machines exactly what to do.
Fuzzy logic is one design model that attempts to bridge human linguistic terms to the machine model. It starts to bring graphical constructs into the solution. Complex fuzzy logic systems, however, may be difficult to design and diagnose.
Creating solutions that can exercise reason is still the objective. Whether the market is for personal robots to take care of the aged, for automated medical treatment to reduce the cost of health care, or for robotic weapons to fight future battles, these systems must be able to exercise reason to be effective. New languages (like the KEEL dynamic graphical language) will be required to define the reasoning models. New engines (like those based on KEEL designs) will be required to process the reasoning models.
There is one thought that the future of AI requires larger and faster computers. I would suggest this is “nice”, but not necessarily required for “reasoning”. We don’t necessarily need millions of HALs running around (at least for the near term). The industry will evolve by building focused systems that exercise reason and address focused