University of Chicago
Type of paper: Thesis/Dissertation Chapter
The Rise of Artificial Intelligence Machines
Today, we’ve become highly dependent on computer intelligence. If all the computers stopped today, essentially everything would grind to halt. Just imagine yourself in a world without computers. Isn’t that miserable? Instead of writing a long composition, you’ll just have to encode, print the composition, and tadah! There it is, clean and well-made product of A.I.
Artificial Intelligence (A.I.) is the area of computer science focusing on creating intelligent. The ability to create intelligent machines has intrigued humans since ancient times and today with the advent of computer (which is one of A.I. machine) and 50 years of research into A.I. programming techniques, the dream of smart machines is becoming a reality. Researchers are creating systems which can mimic human thought, understand speech, beat the best human chess player, and countless other feats never before possible. (http://library.thinkquest.org/2705/) Researchers are confident that technology will soon be able to track every waking moment of our life.
Whatever we see and hear, plus all that we say and write, can be recorded, analyzed and automatically indexed, and added to our personal chronicles. By the 2030s, it may be possible to capture your nervous system’s electrical activity, which would also preserve your thoughts and emotions in a form that will allow your great-great-great grandchildren to quiz a virtual you. (http://www.businessweek.com/1999/99_35/b3644012.htm)
They’re going to put some machines into our bodies and into our brains. They’ll be using nanobots to expand human intelligence, and over time, the bulk of our thinking will be done in the nonbiological parts of our brains, because that part of our brain will continue to grow as technology advances. But the biological part is not growing. It is more powerful than the human brain, in terms of computing capacity. That raw computing capacity is a necessary but not sufficient condition to achieve human-level intelligence in a machine. With microscopic nanobots, we’ll be able to send millions or billions [of them] into our brain. They would take up key positions inside our brains and detect what’s going on in our brains. They would be communicating with each other, via a wireless local-area network, which would be linked to the wireless Web and intelligent machines, and they could cause particular neurons to fire, or suppress them.
But remember, this will be emerging gradually from within our own civilization. It’s the next phase of our own evolution. It’s only a threat if you believe things should always stay the same as they are today. (http://www.businessweek.com/1999/99_35/b3644022.htm)
This paper will tell you about the power of Artificial Intelligence in changing our lives, about how they have the power to excel the human Intelligence Quotient, and about their strengths to reign in the human world.
The human aspiration to create intelligent machines has appeared in myth and
literature for thousands of years, from stories of Pygmalion to the tales of the Jewish Golem (http://a-i.com/show_tree.asp?id=3&level=2&root=1). The Greek myth of Pygmalion is the story of a statue brought to life for the love of her sculptor. The Greek god Hephaestus’ robot Talos guarded Crete from attackers, running the circumference of the island 3 times a day. The Greek Oracle at Delphi was history’s first chatbot and expert system (http://a-i.com/show_tree.asp?id=44&level=3&root=1). After thousands of years of fantasy, the appearance of the digital computer, with its native, human-like ability to process symbols, made it seem that the myth of the man-made intelligence would finally become reality (http://a-i.com/show_tree.asp?id=3&level=2&root=1).
The desire to breathe life into sculpted clay – or today, into silicon – has been with us for thousands of years. When the computer first appeared in the 1950s, we seemed closer than ever to creating an “electronic brain.” Today, the field of artificial intelligence can be described as a global primordial soup of cognitive and computer science, psychology, linguistics, and mathematics, waiting for that flash of lightning – an interdisciplinary effort bringing together researchers and resources, developing new approaches, utilizing the world’s storehouse of knowledge, to generate the spark that will create a new form of life. (http://a-i.com/show_tree.asp?id=1) The computer’s memory was a purely symbolic landscape, and the perfect place to bring together the philosophy and the engineering of the last 2000 years. The pioneer of this synthesis was the British logician and computer Scientist Alan Turing (http://a-i.com/show_tree.asp?id=44&level=3&root=1). Turing was a founding father of modern cognitive science and a leading early exponent of the hypothesis that the human brain is in large part a digital computing machine. He theorized that the cortex at birth is an “unorganized machine” that through “training” becomes organized “into a universal machine or something like it.” A pioneer of artificial intelligence, Turing proposed what subsequently became known as the Turing test (http://www.britannica.com/EBchecked/topic/609757/Turing-test#). The test called “The Imitation Game” that might finally settle the issue of machine intelligence.
The first version of the game he explained involved no computer intelligence whatsoever. Imagine three rooms, each connected via computer screen and keyboard to the others. In one room sits a man, in the second a woman, and in the third sits a person – call him or her the “judge”. The judge’s job is to decide which of the two people talking to him through the computer is the man. The man will attempt to help the judge, offering whatever evidence he can (the computer terminals are used so that physical clues cannot be used) to prove his man-hood. The woman’s job is to trick the judge, so she will attempt to deceive him, and counteract her opponent’s claims, in hopes that the judge will erroneously identify her as the male. What does any of this have to do with machine intelligence? Turing then proposed a modification of the game, in which instead of a man and a woman as contestants, there was a human, of either gender, and a computer at the other terminal.
Now the judge’s job is to decide which of the contestants is human, and which the machine. Turing proposed that if, under these conditions, a judge were less than 50% accurate, that is, if a judge is as likely to pick either human or computer, then the computer must be a passable simulation of a human being and hence, intelligent. The game has been recently modified so that there is only one contestant, and the judge’s job is not to choose between two contestants, but simply to decide whether the single contestant is human or machine. (http://www.psych.utoronto.ca/users/reingold/courses/ai/turing.html) Yet, the major goal of artificial intelligence research – to create a machine that can communicate like a person – has yet to be achieved. Artificial intelligence has given us everything from PARRY, the paranoid chatbot, to Japanese fuzzy logic rice cookers, but it hasn’t yet produced a computer that can carry on a conversation.
AI also aims at human-level intelligence. The ultimate effort is to make computer programs that can solve problems and achieve goals in the world as well as humans. (http://a-i.com/show_tree.asp?id=1) With artificial intelligence, computers could be trained to think like humans do. Artificial intelligence allows computers to learn from experience, recognize patterns in large amounts of complex data and make complex decisions based on human knowledge and reasoning skills (http://interests.caes.uga.edu/eai/ai.html). Just like the robots. Robots are made to make the owner’s life easier, and to that end, the robot should be able to perform tasks from day one, but should have the capability to learn new tasks and to improve its performance of preprogrammed tasks (which may mean performing those tasks in a way more pleasing to its owner as opposed to improvement in any objectively measurable way). (http://www.shakti-software.com/intelligence.htm) On the other hand, HAL: The Virtual Child, A software program capable of acquiring language likes a child. Through practice and training, trial and error, HAL was developed based on the principles established by Alan Turing over half a century ago, in line with Turing’s own recipe for true AI: Build a “child machine”, a learning algorithm capable of learning from experience, and teach it to speak along the same developmental milestones demonstrated in language acquisition by human infants. HAL is the product of the extensive research performed at Ai’s research facility over the last 8 years.
It consists of two basic components: The Brain and the Personality. The Brain is a sophisticated machine-learning algorithm, capable of acquiring conversational skills from experience – from its conversations with its trainer(s). While the Personality is the accumulated experience and knowledge possessed by an instance of a Brain, subjected to training by a particular trainer. Every Brain that has any prior experience, however minute, is a Personality. (http://www.a-i.com/show_tree.asp?id=97&level=2&root=115) Scientists can embody human thought processes in a nonbiological medium; it will necessarily soar past human intelligence — for several reasons. First, machines can share their knowledge electronically. With humans, you spend years teaching language to each child. [But] once any one machine has mastered something, it can share that knowledge instantly with millions of other machines over the global wireless Web, which we’ll have by then.
So a machine can become expert at any number of disciplines. Secondly, machines are far faster. Electronic circuits are 10 million times faster than neural connections, and machine memories can be far larger and much more accurate than human’s. However, machines do not yet have the depth of pattern recognition or the subtlety of human intelligence. They can’t deal with emotions and humor and other subtle qualities of human intelligence. Once their complexity matches that of humans and they are able to master the skills at which humans now excel, and those abilities are combined with the ways in which machines are already superior — that will be a very formidable combination. It’ll get to the point where the next generation of technology can only be designed by the machines themselves.
Finally, whilethe complexity of the biological computational circuitry in humans is essentially fixed, the density of machine circuitry will continue to grow exponentially. By 2030, a $1,000 computer system will have the power of 1,000 human brains; by 2050, 1 billion human brains. (http://www.businessweek.com/1999/99_35/b3644022.htm) Artificial Intelligence is beneficial in many real world applications because it is good at solving complex problems. The flexibility inherent in AI techniques makes the technology adaptable to fields as diverse as agriculture, business, and literature. Scientists have used artificial intelligence in many different ways: monitor and adjust the climate in greenhouses and poultry production houses help forecast weather and predict crop development determine when vegetables are ripe identify molecules by their “chemical fingerprints” candle eggs to determine which have cracks and other defects. (http://interests.caes.uga.edu/eai/ai.html)
Based on the gathered information, life with A.I. machines is easier, faster and more comfortable. You’ll never know, we’ll be traveling by flying cars soon. Isn’t that cool? Going to places like Paris, for example, and traveling in just a blink of an eye. Imagine, in just a day, you can travel around the world with the help, of course, of these A.I. machines. But that’s not the only thing A.I. machines can do – traveling around the world – they can also extend human intelligence. They can expand your memory and improve your pattern-recognition capabilities. I don’t know how will they do that – extending your intelligence but, see? They’re useful to humans. On the other hand, they still have bad effects on us. Just like the computers today, they give off radiation that can irritate body cells and when the body cells are too expose to these radiation, it can cause cancer (I think). The populations of these A.I. machines are now beginning to rise with the help of humans. But humans didn’t know that when these machines will develop, upgraded, and have minds of their own, they can and they will make humans to be their pets. “Invading”, some says but, don’t be afraid. By the time these machines will invade, we are no longer living in the human world.
“About Ai” http://www-formal.stanford.edu/jmc/whatisai/node1.html (January 29, 2010) “Ai” http://library.thinkquest.org/2705/ (January 29, 2010) “Ai” http://www.businessweek.com/1999/99_35/b3644012.htm (February 5, 2010) “Ai” http://www.businessweek.com/1999/99_35/b3644022.htm (February 5, 2010) “Alan Turing” http://www.britannica.com/EBchecked/topic/609757/Turing-test# (February 21, 2010) “Field of Ai” http://a-i.com/show_tree.asp?id=1 (February 6, 2010) “Greek Myth of Pygmalion” http://a-i.com/show_tree.asp?id=44&level=3&root=1 (February 6, 2010) “HAL: The Virtual Child” http://www.a-i.com/show_tree.asp?id=97&level=2&root=115 (February 6, 2010) “History of Ai” http://a-i.com/show_tree.asp?id=3&level=2&root=1 (February 6, 2010) “Machines can possibly do” http://interests.caes.uga.edu/eai/ai.html (February 6, 2010) “Robots” http://www.shakti-software.com/intelligence.htm (February 16, 2010) “Turing Test” http://www.psych.utoronto.ca/users/reingold/courses/ai/turing.html (February 6, 2010)