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Artificial Intelligence

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Introduction
I have always loved the robot takes over the world type movies. Ever since I was a child this subject has intrigued me and have pointed me in the direction of the career choice that I made for myself many years ago. I can remember when my friend's dad took us to see “Terminator 2” though we weren’t even old enough to get in to see it without having a parental guardian I understood all of the foreshadowing and plot of the movie at 9 years old. If you know anything about this awesome flick its set in the late 90’s and the dilemma the characters go through is trying to stop the creation of the supercomputer “Skynet” that spawns a robotic race of human eradicating beings that will eventually try to wipe out the human race if they don’t succeed in their mission. As we have all grown older now I see so many of the similarities of this movie and the potential for this fiction to shift towards a harsh reality that our society is very possibly going to witness one day. In the following pages, my research has shown me many mistakes, though ground breaking and very interesting, but in my opinion has already pushed us to a tipping point. After all of my research I must say, we the people, in order to create a more than perfect human, have just uncovered the next reason our race faces possible extinction from this planet one day.

The history of artificial intelligence
The term artificial intelligence or A.I. has been around since the fifties and was conceived by a group of scientists at the Dartmouth College in Hanover New Hampshire. They originally projected they would be able to build a computer that could simulate every feature of human intelligence within thirty years. This obviously has proven very difficult and to have done it in thirty years was impossible. Though we can explain many things about the human race, to explain how the brain comes to every cognitive decision, on a very limited power supply, is still a mystery. Many “what's” can be explained of human level intelligence, but it’s the “why’s” that still have scientists puzzled. (Norvig)
One of the biggest dilemmas of the A.I. science is the disagreement on what intelligence is. The term itself has proven very difficult to describe because it comes with so many different aspects. The list of rules that our brains recognize that allows us to do intelligent tasks is massive. The brain doesn’t start off as intelligent, it absorbs the environment around us, solves problems as time rolls on, and remembers solutions to perform later when needed. (Heaven)
From the fifties to mid-seventies, A.I. research became heavily funded and was the most sought after technology of the century. But in 1974, the so called A.I. Winter set in and funding was pulled from the branches and teams that dedicated their careers to finding the proper algorithms and execution techniques to simulate a human. In 1950, Alan Turing proposed to put a computer and a human in separate rooms with a judge that is allowed to ask the contestants any question he/she could conceive. If the computer is able to fool the judge into not knowing which of the two contestants is human or not it’s said to be intelligent. This imitation game has come to be called the “Turing test”. Then later in 65 a colleague of Turing’s, I.J. Good, proclaimed that the first ultra-intelligent machine man creates will be the last creation man need make. This statement again is flawed because we have yet to even be able to fully describe every aspect of intelligence. (Norvig)

Evolution of A.I.
Though creating a single machine that looks like something we see in the movies and is able to interact with human life hasn’t been created yet that’s not to say the science has been unsuccessful. Many different machines dating all the way back to the 40’s have been created that can perform certain tasks, but are limited to a defined set of rules. In 1948, Gary Walter built a set of autonomous turtles, one of which adapted to her environment by decreasing its sensitivity to light as its battery drained. Not something that was initially programmed and led him to believe this made the robot turtle animal like. (Norvig)
Later a long way down the road IBM creates the computer named Deep Blue. Deep Blue was a chess playing machine that could evaluate the possibilities equivalent to 200 million chess moves and outcomes per second. The human brain, though very proficient in the strategy to play the game is only able to evaluate a dozen per second, and the best of human players possibly a few dozen per second. In 1997 when Deep Blue was set against the chess champion Gary Kasparov, victory for the computer was inevitable. Even though these machines could perform very intelligent tasks they couldn’t explain the logic or strategy used to win or save battery power, they just did. They couldn’t by any means be described as A.I. (Norvig)
If you’re a product of the 90’s such as myself, surely you remember the sweet little gremlin looking big eyed robot named Furby. This toy was A.I.’s first mainstream example of a simulation of emotions, responses and adaptation by a robot. Its appearance alone would not strike anyone as intelligence, but it could be trained to play childlike games, had a sensitivity to lights being turned off if it wasn’t bedtime per say, and would simulate a sort of affection when hugged or bet on certain points of its body. Though again a good stride for the A.I. world, it wasn’t enough. All of these examples were built on a set of defined programmed rules that limited its abilities. The solution to human intelligence hadn’t been found and discouraged scientists began to give up. Nelly Cristianini says that’s when they had a breakthrough. (Heaven)
A.I.’s of Today
Whether you realize it or not, most of us use several forms of A.I. every day. Take Siri for example, Apple’s digital assistant that you can ask almost anything and will get an answer or minimally the response of “I don’t understand what you’re asking”. The software can be used to create reminders, make phone calls, or type your text message as you speak to the iPhone or iPad your using. (Brynjlfsson) This technology works off of a branch of A.I. called probabilistic reasoning. Siri will first analyze the sound waves of your voice and come up with the most probable words matching what you said, then using a connection to the internet it pools, mountains of data very quickly to come up with the solution or action to what you asked of it. This may not be what Turing had envisioned completely in designing the Turing Test, but it’s definitely a huge step closer. (Norvig) Another major contributor that has had many of the advancements in the A.I. field is Google. The breakthroughs that Google has encountered come from the indexed mountains of data it has developed from its initial search engine. This “big data” approach to A.I.’s biggest challenges have spawned a translator that in a day translates more languages than every human translator combined can decipher in a year. Its ability to translate 65 languages, bi-directionally, a total of over 4000 possibilities in seconds is nothing short of amazing. Currently they are working on an app for your smart phones that will allow you to speak into the device and output speech in whatever language you choose. (Kedmy) The next and biggest controversial creation of Googles is the birth of their autonomous cars. Relying on a slew of sensors, software, and Googles massive mapping database these cars have been navigating our public roads for quite some time now. Though you could pick out these cars and may have even seen one yourself, you probably didn’t take a second look and notice the person in the driver's seat clearly didn’t have their hands on the wheel. These autonomous vehicles and their creators/owners are able to apply for one year permits in California, Nevada, Michigan and Florida. This is a huge step for A.I. and is completely on a testing ground basis, but successfully executed could potentially mean saving lives, reducing the amount of fossil fuels, we utilize, and creating the next level world we’ve always seen and dreamt about from the movies. (Norvig) Which leads me to my final example and most extraordinary advancement for A.I. of today. Even though IBM’s creation of Deep Blue was looked at as a huge step in machine evolution, they really floored futurists with the creation of the amazing “Watson” computer. Watson is a whole new kind of computer entity and could definitely pass the aspects of the Turing test. The things that set Watson apart from any other A.I. attempt is its ability to do 3 things. First, it can understand natural language, second, it can generate and evaluate hypothesis used to provide evidence based responses confidently, and last, it can be trained and has an extreme learning capability. This super computer can process 500 gigabytes of information per second due to the extensive grouping of hardware. The unity combining in a total of 2,880 Power 7 processor cores and a massive 16 terabytes of RAM, created an entity that when put up against two reigning champions of the hit game show jeopardy won the contest. This may be an amazing computer and has several benefits in the future other than a game show, but I must ask, have we taken it too far? (IBM)
Conclusion
Through the advancements of big data, machine learning and neural networking we have stumbled on to uncharted territory. The human brain is a network of 100 trillion synapses that connect 100 billion neurons and can change their state between 10 and 100 times a second. A supercomputer such as Watson on the other hand has 100 trillion bytes of memory and can perform calculations 100 million times faster than a human brain. (Norvig) These machines are beginning a similar evolution that can be seen as similar to our own only faster. It took humans around 100,000 years to transition to the beginnings of the digital age, we shifted to only a mere 60 years ago. If it took us that long with our low power consumption minds to transition how long will it take the machine world to do the same? (Mcbain)
We are at an irreversible age that needs to be delicately handled. The problem is that we stopped being able to explain the why’s of how a machine comes to the conclusion or performs its tasks. By allowing the machines we initially created start to evolve themselves by teaching itself and using probabilistic reasoning to come up with answers what's to stop them from eventually seeing the human race as a problem and stop being tools and turning to our enemies. Possibilities of there being an intelligence behind our internet searches building profiles for us are extremely likely. For example Latanya Sweeny of Harvard University was appalled when her Google searches were returning Google ads that included questions like “Have you ever been arrested?”. The ads for her Caucasian colleagues on the same searches from their own pcs did not return the same ads. This has sparked the idea that the machine learning capability behind Google’s search engine was inadvertently racist. Further studies would show that the chances of criminal related ads were returned far more frequently when a name that is considered to be African American was searched rather than that of names from white descent. (Heaven)
The logic that machines are learning today is alien in nature to us and is furthermore unexplainable in terms of our level of intelligence. (Heaven) In the hit film IRobot an ultra-intelligent computer named V.I.K.I. comes to the realization that humanity isn’t suited for the task of ensuring their own survival. All though the initial programming of the personal assistants was to protect us from robots ever harming humanity, the computer evolved and after so many failed attempts to help humans seeing that we come up with new ways and due to the brutal nature continued to ensure our own extinction. The computer took control of people’s personal assistant robots and proceeded to pursue a takeover of our world. (Proyas) Even though this is just an example from a movie, it is portraying many realities in machines we see today. The logic that A.I. are learning today is alien in nature to us and is furthermore unexplainable in terms of our level of intelligence. Without careful planning and a deep understanding of the future A.I.’s all of the machine takeover movies many of us have seen may become very true. An idea of machine ethics, and designing future machines with a sense of morality should be considered essential. (Brynjlfsson) We are hoping since the birth of A.I. that one day we will be able to meet the machine world as an equal on the path of life, but examples such as Latanya Sweeny raise the question if that’s possible. (Heaven) Human ethics and logic are not always based on probabilistic reasoning nor should it be. They are from a more philosophical origin that also takes from human emotions that influence the decisions we make. These computers were creating do not have compassion, love, or any other emotion that could always lead to the best answer. From this point it wouldn’t take much more too accidentally stumble onto the singularity and the possible extinction of the human race. We have already had so many possibilities of our demise through overpopulation, and the destruction of our atmosphere, do we really need another one such as spawning the next superior race? (Muehlhauser)

Works Cited
Allen, Paul G., and Mark Greaves. "The Singularity Isn't Near." MIT Technology Review 12 Oct. 2011: Rpt. in Robotic Technology. Ed. Louise Gerdes. Farmington Hills, MI: Greenhaven, 2014. Opposing Viewpoints. Opposing Viewpoints in Context. Web. 21 Nov. 2014.
Brynjolfsson, Erik, and Andrew McAfee. "Robots Cannot Duplicate All Human Skills." Atlantic 24 Oct. 2011: Robotic Technology. Ed. Louise Gerdes. Farmington Hills, MI: Greenhaven, 2014. Opposing Viewpoints. Opposing Viewpoints in Context. Web. 22 Nov. 2014.
Heaven, Douglas. "Higher State of Mind. (Cover Story)." New Scientist 219.2929 (2013): 32-35. Web. 17 Nov. 2014.
"IBM and the Watson Ecosystem." Mechanical Engineering 136.9 (2014): 33. Business Source Premier. Web. 18 Nov. 2014.
Kedmey, Dan. "Brain Builder." Time 184.15 (2014): B1-B2. Web. 21 Nov. 2014.
Mcbain, Sophie. "Apocalypse Soon." New Statesman 143.5228 (2014): 44-51. Web. 17 Nov. 2014.
Muehlhauser, Luke. "Artificial Intelligence Will Exceed Human Intelligence." 2013: Robotic Technology. Ed. Louise Gerdes. Farmington Hills, MI: Greenhaven, 2014. Opposing Viewpoints. Opposing Viewpoints in Context. Web. 22 Nov. 2014.
Norvig, Peter. "Artificial Intelligence." New Scientist 216.2889 (2012): I-8. Web. 17 Nov. 2014.
IRobot. Dir. Alex Proyas. Perf. Will Smith, James Cromwell. Twentieth Century Fox Film Corporation, 2004. DVD.
Terminator 2. Dir. James Cameron. Perf. Arnold Schwarzenegger, Edward Furlong and Linda Hamilton. 1991. DVD. 18 Novemeber 2014.

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