Artificial intelligence research paper

20067817 Danny O’Leary Computer Forensics and Security Critical Thinking

Artificial Intelligence

Danny O’Leary

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Table of Contents 1. Table of Contents ..................................................................................................................... 2 2. Introduction ............................................................................................................................. 3 a) What is AI? ........................................................................................................................ 3 b) The history of AI ................................................................................................................ 4 3. The Goals of AI ......................................................................................................................... 5 c) Goals AI has already achieved ........................................................................................... 5 d) Expert Systems .................................................................................................................. 7 4. The Three Core Branches of AI ................................................................................................. 7 e) Symbolic AI ........................................................................................................................ 7 f)

Statistical AI ....................................................................................................................... 7

g) Computational Intelligence ............................................................................................... 8 5. Machine Learning .................................................................................................................... 8 6. How AI could change our World ............................................................................................ 10 7. Conclusion.............................................................................................................................. 11 8. Bibliography ........................................................................................................................... 12

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Introduction This essay aims to give a broad understanding of Artificial Intelligence where it will go through some of the most vital sections that make Artificial Intelligence possible. It will explain what Artificial Intelligence is, the history of Artificial Intelligence where it will show how much advancements have been made over a short period of time. It will also go through the goals that researchers have for Artificial Intelligence and will talk about what they think will be possible and will explain what is already possible. The next section that it will explain is the three core branches of Artificial Intelligence, these are the main sections of work for Artificial Intelligence even though there’s a lot more branches and as it evolves it is forever expanding. Another section of Artificial Intelligence that it will go through is Machine Learning which is a term used for computers actually learning like we do and it will also go through how Machine Learning and Artificial Intelligence could change the world how we know it. With Artificial Intelligence, a lot of people are sceptical about how safe it is and this essay will go through the dangers of it. This essay will also have a conclusion where it will show what I have learned personally and what kind of point’s people can come to from what I have read.

What is AI? AI (Artificial Intelligence) is the science behind making intelligent machines. One example of this would be to try make a machine like a computer simulate human intelligent where it can make independent decisions for itself (Www-formal.stanford.edu). Some of the research that goes into trying to make machines intelligent is in fields such as: 

Perception: This is the goal of trying to get a machine to recognize images, sound and touch (www.wiseGEEK.com). This has been advancing in computers over the last few years with the introduction of touch screen computers and also with speech recognition devices such as SIRI on the iPhone.

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Reasoning: This is getting a machine to figure things out instead of having to be told what to do by the user. An example of this would be telling the machine to get coffee, but not explaining every single step that it needs to carry out to get coffee (Artint.info).

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Learning: This is how a machine is able to take previous information and better itself from it.

It could do this by improving its performance by carrying it out quicker, it can better itself by learning different outcomes to get the best possible one (Artint.info). An example would be a chess program that learns by each moves it takes and it would note which moves are bad and which are good. Over time to chess program would keep improving and eventually it would make each move to near perfection.

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Communicating: This is the ability of a machine to understand the languages we speak. This is already a big field in Artificial Intelligence with applications like Siri already made. Another example of this combines learning with it:

(existor.com, 2015) This shows an example of how it can use learning by processing everyone who types or speaks to the machines information and then saying and typing back the most appropriate response.

The history of AI Even though Artificial Intelligence is considered a relatively new field of research, but in reality it has been around for a long time with people trying to see if machines can really think. In 1961 a man called Alan Turing produced a paper that described the idea that machines being able to simulate some sort of human behaviour as well as having the ability to have intelligence (Washington.edu, 2015). Even before this in 1948, Artificial Intelligence was used during World War 2. Norbert Wiener decided to carry out many different experiments to work out an anti-aircraft device that could be able to interpret enemy radar images (Computerhistory.org, 2015). In 1961, a robot known as “UNIMATE” was developed and was able to obey step by step commands to help General Motors with their production line. Then in 1963, the first robotic arm was developed in the Los Amigos Hospital (Computerhistory.org, 2015). In 1970 SRI International developed the first robot who was fully controlled by Artificial Intelligence and was able to find its way around corridors in the SRI building by using many different technologies such as: TV Camera, Laser Range Finder and bump sensors. An educational toy known as the speak and spell was developed in 1978 that was capable of taking an input of letters and attempting to know the word while also being able to speak the letter and the word (Computerhistory.org, 2015). In 1987, the fingerprint scanner was developed which used a database to compare fingerprints to ones that are already in the database which is still a technique used today (Timetoast, 1917). To show how far Artificial Intelligence has advanced since Danny O’Leary

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20067817 this time, it is now being used to help in surgeries so that it can diagnose a patient and also give decisions on what to do for these problems. Most devices today use some sort of Artificial Intelligence such as phones, all smart phones have some form of artificial intelligence. Many of them have fingerprint locking systems and voice recognition searches.

The Goals of AI The goals of artificial intelligence are mainly to provide intelligence to machines, with it advancing all the time, AI has achieved a good portion of these already, but it still continues to advance.

Goals AI has already achieved Artificial Intelligence has already accomplished lots of different goals in different areas. Below is a list of some of the different things it has accomplished over the years: 1. It has been able to achieve speech from within computers which is extremely beneficial today. It can be used as a form of speech therapy for patients who suffer from some sort of speech impediments. It can also be used much more simply in phones to call someone by speaking to the phone rather than typing in the buttons that navigate to the phone book.

2. Used by the police for fingerprint scanners which are a necessity to identify a suspect for them.

3. It can be used to diagnose patients in a hospital and give a course of action back.

4. It can do machine translation where a computer will attempt to translate a language from one to another without any input.

These goals are some of the biggest in the AI field, but it also has many other goals that it has accomplished that may seem smaller, but are significant in the development in the future: 1. IBM’s Supercomputer “Watson” beats humans in a game show known as Jeopardy (Ibm.com, 2015).

(Ibm.com, 2015) This was the final result for the Jeopardy game.

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20067817 2. Another one of IBM’s Supercomputers known as “Deep Blue” was successfully able to defeat chess champion Gary Kasparov in a game of chess. Since then there’s been many other types of machines set out to play chess one being Kasparov vs X3D Frintz which ended in a draw, with another game also ending in a draw Kramnik vs Fritz (Wired UK, 2015).

(Wired UK, 2015) 3. The website Wolfram is another example of this. It is a website that is able to perform mathematical calculations and take a user through them step by step.

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(Wolframalpha.com, 2015)

Expert Systems An expert system in Artificial Intelligence is one that is capable of making decisions just like a human.

An example of these types of systems would be the auto pilot of an aircraft or a machine that diagnoses patients in a hospital. One thing to note about a system like that is that it cannot be depended on fully and still requires some human knowledge to go along with it (Bbc.co.uk, 2015).

The Three Core Branches of AI Symbolic AI Symbolic AI is a section of Artificial Intelligence that is not used commonly anymore. It is the field that focused on human behaviour and it didn’t really work because they were never able to truly achieve this. One of the main problems that they had was that they weren’t able to work out how human behaviour like common sense would ever work.

Statistical AI This is the field of Artificial Intelligence that deals with the mathematical aspects of Artificial Intelligence. It is used for what is known as a Bayesian Network which is used to show how two or more things are related using probability. It is also used to show the state of a current object for example if a tire if flat or not. An example of this: Danny O’Leary

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This is a simple version of a Bayesian Network used to diagnose patients. It shows the probability that visiting Asia might lead to Tuberculosis or how smoking is related to the probability to lung cancer or bronchitis (Norsys.com, 2015).

Computational Intelligence This is the field of Artificial Intelligence that deals with problems that are not humanly possible to solve. An example of this kind of Artificial Intelligence is Artificial Neutral Networks which is used to help solve problems using algorithms with things like facial recognition, they achieve this by using algorithms (Theprojectspot, 2015). Another example of Computational Intelligence is what is called fuzzy logic. Fuzzy logic is used in many day to day appliances for example it makes a toaster pop at the perfect time for toast or it could be used to get the perfect golf clubs for a person by using their height and swing (Mark.stosberg.com, 2015).

Machine Learning Machine learning is when a machine is learning from examples and the collection of data over time.

It works mostly with complex algorithms that are developed usually by Mathematicians and Scientists. The aim of these complex algorithms is to be able to take data and better themselves as a machine and better interact with the data in algorithms.

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This is a picture of what is known as “Spam” which is a filter that the majority of E-Mail sites use to block unwanted mail from entering a user’s main inbox. To do this, they use Machine Learning and use many different algorithms to achieve this. One of the ways they do this is by matching words with common spam related words and then giving the message a “Spam Rating” and if it reaches a certain rating it gets marked as spam. Another thing that these Email providers do to mark spam is get users to report it and when a certain number of people that report it, they then mark it as spam and add the words to the database to use with the first method.

Another example of Machine Learning was when IBM produced a documentary called “The Smartest Machine On Earth”. In this documentary IBM, asked viewers to try come up with a way that computers could tell different variations of the letter “a” apart, which included different fonts, uppercase and lowercase. It turned out that there was no way to actually for the computer to figure it out by using regular forms of programming. Then they used Machine Learning from it where it learned from thousands of different examples and built up a database of different variations and then was able to tell apart the different variations of the letter “a”.

There are many examples of how Machine Learning is used today and how beneficial it is to the advancement of computers. Some more of these include: 1. Amazon recommends related products on every page using Machine Learning 2. Pandora makes playlists by predicting artists that are alike in the music industry using Machine Learning.

(Love, 2014)

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How AI could change our World Many people have different thoughts about how Artificial Intelligence could change our world for the better or even for the worst. With Artificial Intelligence rapidly growing and advancing in sophistication it’s becoming more like simulating a human brain all the time, which is the goal for a lot of people who work in the Artificial Intelligence field. Artificial Intelligence has improved a lot of the machines we have today and not many would dispute that fact, but it is also scary at the potential it has. To simulate a human level intelligence, it is suggested that computers would need to: 1. Speed: Computer speeds are already faster than we think in regards to mathematical problems, etc. It has already been achieved.

2. Storage: Our brains can store an extreme amount of data, but so can computers currently and are always improving. They can also always be expanded.

So what makes people scared of Artificial Intelligence?

When you think about how we have been able to make so much progress with Artificial Intelligence in such a short period of time, it makes thinking about what would happen when Computers reach our level of thinking interesting. For example: 

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When a program reaches our level of thinking they would be able to think just like us, with the use of machine learning they would be able to increase their capabilities even further and it would only continue to increase over time and start to grow at an exponential rate.

Then one of the things that scares peoples could very well happen, since humans effectively dominate earth just due to sheer intelligence would now give computers all the power to do with what they please.

This also means that these machines could be 1 billion times smarter than us in no time which could make it so that many things that are currently not possible, possible such as reverse human aging, curing diseases, changing the weather to protect the earth as a whole and even the potential to destroy the earth whenever they want. Computers could become literally what some people consider a god.

The other end of this is that people also believe that this could be used to save us with immortality which may never be possible without smarter beings’ which will mean eventually humans will go extinct.

There’s many more different theories and other beliefs people have also, but I won’t get into them here. (Waitbutwhy.com, 2015)

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Conclusion From doing this essay I have learned a lot about the field of Artificial Intelligence and how broad it is, how we all use it in our daily lives, how it is advancing rapidly and how people see it going in the future. I think Artificial Intelligence is a fascinating field that could be talked about in great detail in regards to some of the potential it has. From doing this essay I learned how a lot of big companies are using machine learning to do work for them so they can focus on either areas. I learned about the future of AI and what could possibly happen when Artificial Intelligence reaches human intelligence and some of the dangers it may have or may not have which depends on how the person wants to view it. I also learned about how Artificial Intelligence is done using algorithms which could be beneficial to know at some point. I think this shows why Artificial Intelligence is such a rapidly growing field because of how interesting it can be.

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Bibliography 

http://courses.cs.washington.edu/courses/csep590/06au/projects/history-ai.pdf [Accessed 7 Apr. 2015].

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Computerhistory.org, (2015). Computer History Museum | Timeline of Computer History : Robots & Artificial Intelligence Entries. [online] Available at: http://www.computerhistory.org/timeline/?category=rai [Accessed 7 Apr. 2015].

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Timetoast, (1917). The History of Artificial Intelligence. [online] Available at: http://www.timetoast.com/timelines/70617 [Accessed 7 Apr. 2015].

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Ibm.com, (2015). Say Hello to IBM Watson. [online] Available at: http://www.ibm.com/smarterplanet/us/en/ibmwatson/ [Accessed 9 Apr. 2015].

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Wired UK, (2015). Did Deep Blue beat Kasparov because of a computer bug? (Wired UK). [online] Available at: http://www.wired.co.uk/news/archive/2012-10/01/deep-blue-bug [Accessed 9 Apr. 2015].

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Bbc.co.uk, (2015). BBC - GCSE Bitesize: Expert systems. [online] Available at: http://www.bbc.co.uk/schools/gcsebitesize/ict/databases/0datainforev5.shtml [Accessed 9 Apr. 2015].

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Norsys.com, (2015). Tutorial on Bayesian Networks with Netica. [online] Available at: http://www.norsys.com/tutorials/netica/secA/tut_A1.htm [Accessed 11 Apr. 2015].

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Google+, f. (2015). Introduction to Artificial Neural Networks - Part 1. [online] Theprojectspot.com. Available at: http://www.theprojectspot.com/tutorialpost/introduction-to-artificial-neural-networks-part-1/7 [Accessed 12 Apr. 2015].

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Mark.stosberg.com, (2015). The Role of Fuzzy Logic in Artificial Intelligence. [online] Available at: http://mark.stosberg.com/Tech/fuzzy/role_in_ai.html [Accessed 12 Apr. 2015].

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Love, D. (2014). What The Heck Is Machine Learning?. [online] Business Insider. Available at: http://www.businessinsider.com/machine-learning-2014-5?IR=T [Accessed 22 Apr. 2015].

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Waitbutwhy.com, (2015). The AI Revolution: Our Immortality or Extinction | Wait But Why. [online] Available at: http://waitbutwhy.com/2015/01/artificial-intelligence-revolution2.html [Accessed 22 Apr. 2015].

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