Introduction

 

 

 

            Cognitive Science is a very specific and precise study of the mind and brain.  It is also a study that has been around for millennia.  A basic question such as “how do we think?” can be answered in great detail through the massive study of Cognitive Science.

            This study started with great philosophers such as Confucius and Aristotle.  In attempt to answer demanding inquiries of the mind, these two pressed on to discover the nature of thought, how we reason, how we learn and use language, the meaning of consciousness, how we recognize shapes and faces, how we understand each other, etc.

            While philosophy remained important in providing a base for the study of Cognitive Science, it’s physiology that has separated this science from psychology or any other related science.  Currently, most cognitive scientists are more interested in the physiological reasoning for the accomplishments of the mind--discovering exactly how complex the human mind is, and if and when functions of the mind can be linked with specific parts of the brain.

            There are billions of highly interconnected neurons that form our brains.  Cognitive Science--the study of thinking--brings us closer to finding out exactly how these neurons affect our every thought, memory, emotion, or anything else in our mind, conscious or otherwise.  After a while, computers began to make solving this puzzle somewhat easier, but also offer a lot more to study.  As the computer age arrived, scientist began to wonder whether computers could help humans understand thinking better and improve our knowledge of thinking processes.

 

            Artificial Intelligence is a broad topic.  Its fields span from diverse areas such voice recognition to expert systems, and cover a wide area in between.  In solving problems in the mentioned fields, Artificial Intelligence is makes use of the idea that we can create software or machinery with the ability to “think.”  In order to simulate thinking, however, we need to define intelligence.  With technology, we cannot create actual intelligence, thus Artificial Intelligence, or AI, comes into play.

            So by what makes our AI technology “intelligent,” artificial or otherwise?  Does it need to solve complex problems, make generalizations and relationships?  Does it need to perceive and comprehend exactly as human do?  To an extent, yes.  AI is a mixture of all of these different things.

            The main purpose of AI is to build an intelligent machine.  At its simplest, a machine capable of taking in a problem and thinking of a solution on its own. Researchers have used their studies of learning, language, sensory perception, and comprehension to aid them in building intelligent machines.  Possibly, the most challenging approach that experts face is building a system that mimics the behavior of the human brain, which is made up a billions of neurons.  This has been called the most complex matter in the universe.

 

            So how exactly are Cognitive Science and Artificial Intelligence related?  Well, most would consider Cognitive Science and AI separate fields, and with good reason.  Cognitive Science is the study of the human mind and its many quirks.  AI, on the other hand, is the attempted recreation of the human mind and its many quirks, in technology.  Is it my theory that it is possible to connect Cognitive Science and Artificial Intelligence in a way that could greatly improve the knowledge and successes of both fields.

            In this paper,  I will demonstrate the importance of both Cognitive Science and Artificial Intelligence in past, present, and what I perceive as the future.  And from that research, I will give my theory on how the two different studies can be combined to improve upon both, as well as offer opinions on existing theories similar to this.

 

The History and Importance of Cognitive Science

 

 

 

            You could call the study of Cognitive Science an amalgam if you wished, as it is a mixture of different sciences.  Cognitive Science made it’s first step towards becoming an individual field when researchers in anthropology, computer science, neurobiology, philosophy, psychology and sociology realized that a lot of the problems they all were working on were similar, if not related.  Researchers in each field were trying in their own way to answer the same questions.  Once information technology became mainstream, increased methods of communication made it possible for these researchers to communicate with each other and use different tools developed within each field to understand the mind.  Together they would work by combining all of their knowledge and resources to find out as much about the brain and its though processes as possible.

            Not only did this newfound science of the mind provide its aspiring experts with many things to study, but it also created applications for other fields as well.  Information technologies such computers, the internet and virtual reality have succeeded because studies in Cognitive Science has allowed programmers to understand the abilities and limitations of computer users--thus, making their systems more user-friendly.  Another application is voice recognition.  Cognitive Science was one of the fields that broke ground in forging technology that actually allows computers to process and understand spoken language.  Were it not for the understanding of how humans perform the complex task of speaking, no piece of technology would be able to recognize our voice patterns.

            Cognitive Science “officially” got its start 40 years ago.  A journal of important papers, theories, and ideas on topics such as categorization, linguistics, and memory had brought a hidden new study to the forefront.  It was just then that computers had first became major research recourses.  By the 1990s, the study became so great that cognitive scientists could be found in various university departments, industrial and professional settings, and many other places.  The 1990s has even been labeled “The Decade Of The Brain,” by many, as developments have been made in brain-imaging techniques, computer-modeling and neurophysiology--expanding upon our knowledge of how the brain functions.
            Because the brain is arguably the most complex thing in the world, with billions of nerve cells that have interconnections in the trillions, many philosophical questions have arrived.  Cognitive Science helps us understand more about these things, such us how we form categories out of things, how they relate to our languages, etc.  It has also helped us develop visualization techniques in the form of virtual worlds that has led to the exploration of environments that couldn‘t previously be explored.  These environments include the inside of a human heart, the hallway of an building not yet built, etc.  These findings have benefited architecture, engineering, medical research and many other fields.

            Currently, there are applications of Cognitive Science arriving in our lives at a still-accelerating pace.  Helping to forge the interface and layouts on our computers, the video games we play, Cognitive Science has definitely impacted society to the point where we regularly use its applications without noticing.

The History and Importance of Artificial Intelligence

 

 

           

            While evidence of Artificial Intelligence can be traced way back to ancient Egypt, the ability to create Artificial Intelligence in machinery did not become available to us until the development of the computer in 1941.  Although the resources for AI were available throughout the 1940s, the possibility for human intelligence in computers was not really observed until the 1950s, most notable with Norbert Weiner.  Weiner made important observations on the principle of the feedback theory.  Weiner theorized that all intelligent behavior was the result of feedback from a given stimulus.  For example, a thermostat, which automatically lowers or raises heat, when the temperature is above or below a desired amount.  At this point, feedback mechanisms were very  important in paving the way for AI.

            Newell and Simon were the next major players in  developing AI.  They developed The Logic Theorist, which is considered to be the very first AI program by many.  The program took problems and represented them as trees, then would select the branch with the most plausible solution.  This was an amazing breakthrough for AI.

            It wasn’t too long after that when John McCarthy organized a conference for experts interested in machine intelligence to study and brainstorm.  The term “Artificial Intelligence,” was coined in 1956 at that conference and since its birth that night, the name would go on to be associated with many advancements over the coming decades.

            The first of these major programs would be a new protocol called The General Problem Solver or GPS, which arrived in 1957.  Developed by AI veterans Newell and Simon, it took off right where Weiner left off with his feedback principle.  The GPS was able to solve a vast degree of common sense problems.  Years later, IBM finally sought a team to research Artificial Intelligence.

 

            Many more inventions in Artificial Intelligence have popped up over the decades.  These include programs like:  STUDENT, which could solve algebra problems; SIR, which could understand simple English sentences; Expert systems, which predict the probability of a solution under given conditions.  Expert systems, one of the most groundbreaking technologies, were created to read statistics and recognize patterns, and has actually helped diagnose diseases, predict the stock market, instruct miners to mineral locations, and much more.  By the 1980s, companies such as DuPont, General Motors, Boeing, Digital Electronics and VAX all  relied heavily on expert systems to complete their day-to-day business.

            Artificial Intelligence has always been at the most innovative and breakthrough branch of the computer science industry.  Were it not for AI, advanced-level language, computer interfaces and word-processors would not exist.  AI research offers new innovations and theories that will assuredly set the standards for computing in the future.  If the amazing findings out today are a small example of what’s to come, it’s clear that Artificial Intelligence will continue to affect the way we learn, work, and live.

Can Cognitive Science and Artificial Intelligence be Intermingled?

 

 

 

            We know that Cognitive Science is the study of the human mind and all of its functions.  We know that Artificial Intelligence is the formation of intelligence in software and machinery.  And while one has lead to the other, few scientists in either field would consider combining the use of one with another.  So if this is the case, can it be done?  Can Cognitive Science and Artificial Intelligence be joined together in a way that serves and improves both sciences?

            One of the most known theories in the field of Artificial Intelligence is that of Alan Turing, often referred to as the Turing Test.  Turing theorized that in order to insure that a machine really possessed “intelligence” (even if artificial), was to see if that machine could fool a human into thinking it was human.  Is there a machine known to mankind that can do such things?  No, not yet.  However, if Cognitive Science can tell us exactly how many neurons make up the human brain and how they are connected, is there any reason not to believe that eventually, these neurons will be able to be simulated within a machine?  No, there is not.

            The first idea that I have that can be used to merge Artificial Intelligence with Cognitive Science is the age-old problem of creating an Artificial Human with all the basic human functions of a human being.  In this day and age, we have virtual pets that learn their own names, have motion censors, can feel touches, and react to stimulus as a pet would.  With the necessary technology, we can do the same for human beings.

            So what exactly will the Artificial Human need to function?  Well, it’s given that this would take more resources than any other project in AI       or possibly the any field, in history.  But concerns like have arrived during every breakthrough piece of technology.  Possibly, the only thing as difficult as gaining the recourses for such an amazing machine would be properly programming it.  The perfect Artificial Human should have the following qualities:

 

Ÿ         Basic human emotions such as: happiness, sadness, anger, loneliness, desperation, etc.

Ÿ         Sensors that deal with touch, sight, smell, taste, and sound.

Ÿ         Temporary and long-term memory, and the ability to associate experiences to future experiences, as a human would.

Ÿ         The ability to learn, as a human would.

Ÿ         Billions of artificial neurons with billions of interconnections, in order to process the above, as a human would.

 

 

            Those are just a few basic things the Artificial Human would need.

 

            What are experts’ takes on ideas such as the Turing Test?  Well, this goes back to the origin of Artificial Intelligence and the associated ethical issues.  Basically, it’s been feared that when you program a machine with the ability to think, you’re endangering yourself and your world with the risk that machine may rise to become too powerful.  Many of those few scientists that think that this “passing” the Turing Test will one day be accomplished are generally fearful of the chance that these machines may rise to a level where they pose a threat to authentic human intelligence.

            I, personally, do not think that this is as important of an issue as some would make it seem.  Even if the Artificial Human got off the ground, it would take an extraordinarily amount of programming to get it to the point where it would be a danger to mankind.  I definitely think that there is nothing to be worried about, as long as the proper security precautions are being taken.

            Another argument against studies like this is the common from experts who think that AI should be rejected instantly, wherever Cognitive Science is concerned.  Some think that it simply has not place in physiology, as it has little or nothing to do with the subject.  I disagree with this thinking, very much.  Cognitive Science and Artificial Intelligence are both related in a sense that they both deal with the mind and intelligence.  It just so happens that with Cognitive Science, the mind is human and real; with Artificial Intelligence, the mind is programmed and artificial.


Conclusion

 

            Over the past millennia, Cognitive Science has arrived and changed the way experts look at the human mind.  What was once a total mystery, is now something comprehendible and explainable.  While many mysteries still exist in exactly how the mind works, there have been breakthroughs that have allowed us to discover many things about the mind that we never thought we would know, just some decades earlier.

 

            Artificial Intelligence, since its arrival, has also changed a lot of how we spend our lives. Computers are now powerful enough to make logical problem solving a lot easier not only for entertainment purposes, but also in business and health.  It has affected the way we learn, work, and live our lives, and it will continue to do so.

 

            Combining Cognitive Science and Artificial Intelligence may not be seen as “possible” or “safe” by many experts.  However, it’s clear that the ultimate accomplishment would be the result if it were attempted successfully.  Together, both fields could generate the solution to what is possibly the most complex “problem” in history.

 

 

References

 

 

 

http://www.cogsci.soton.ac.uk/psyc-bin/ptopic?topic=Ai-cognitive-science&submit=View+Topic

 

http://www.psych.indiana.edu/general/general.html

 

http://cognet.mit.edu/MITECS/Entry/mataric.html

 

http://cognet.mit.edu/MITECS/Entry/lewis.html

 

http://plato.stanford.edu/entries/cognitive-science/

 

http://www.lucs.lu.se/Abstracts/LUCS_Studies/index.html

 

http://www.lucs.lu.se/Projects/index.html

 

http://www.ai.mit.edu/research/projects/projects.shtml

 

http://www.cs.washington.edu/research/jair/home.html