Will Artificial Intelligence Ever Replace Human Intelligence - Term Paper Example

Will Artificial Intelligence ever replace Human Intelligence? Section Number of Will Artificial Intelligence ever replace Human Intelligence? The relationship between man and machine has been the subject of many discussions and debates both scientific and otherwise. Over the years, this relationship has grown and developed into a strong and enduring bond as man and machine have worked together, played together and fought together. Rapid development in the field of Information and Communication Technology (ICT) has made man and machine mutually indispensable. Human beings now depend on the ubiquitous computer, the most common manifestation of the machine to accomplish an ever increasing range of task from the most ordinary to the very complicated, while the machine depends on human beings to achieve increasing levels of sophistication in make and operation. It has now come to a stage when the machine can not only outperform human beings in physical performance as it has been designed to so, but is also increasingly able to outperform man in many mental capabilities. It is when grandmasters of chess are beaten by Deep Blue (Reddy, 1996, pp. 88), it is when the machine starts participating in human conversations that human beings start to cast sidelong glances at it and begin to wonder whether artificial intelligence will ever replace human intelligence. Will machines ever be able to think? Or have machines, in whatever form, already achieved the faculty that human beings have long held to be their own exclusive preserve in this world? Divided Opinions The question under consideration has however been floating around in one form or the other. It is as old, if not older, than the computer. The popular press has had a record of being rather lenient in equating human intelligence with artificial intelligence. As early as on January 15, 1941, the Des Moines Tribune carried an article on the development of the first prototype of the ABC computer at the Iowa State University by Professor John V Atanasoff and his graduate student Clifford Berry with the headline ‘Machine Remembers’. "The giant computing machine under construction at Iowa State College has a memory consisting of 45 vacuum tubes…", the article reported, and went on to define it as: "An electrical computing machine said here to operate more like the human brain than any other such machine known to exist is being built." (Martin, 1991, pp. 124). The early computers were more of calculating devices when compared to modern technology. Yet, machines that could solve mathematical problems, including algebraic problems involving many variables, and that too at speeds unthinkable by human beings, were bound to impress. Since these machines surpass human beings in some activity, they had to be capable of thinking. The logic was simple: "A machine can handle information; it can calculate, conclude, and choose; it can perform reasonable operations with information. A machine, therefore, can think." (Berkeley, 1949) The idea of building a machine could possess human intelligence has exerted a powerful attraction on people throughout the ages. Even in the days before the advent of the computer, there were inventors who dreamt of building a steam-driven warrior or an automatic scribe driven by a clockwork. Human beings have been so charmed by the subject of thinking machines that it can be discussed, “on various levels, ranging from that of a sensational Sunday newspaper to that of a sober philosophical periodical. It arouses deep-seated emotions, and views are apt to be expressed with vigour.” (Wilkes, 1953, pp. 1230). The scientific community has however been more reserved in its approach. British Mathematician Alan M Turing was the one who first figured out how to build a programmable computing device – the universal Turing Device. All programmable computers today in essence use the Turin principle. It was also Turing who first raised the question, ‘Can machines think?’ in 1950 (Turing, 1950). However, in the same paper, Turing went on to opine that the question he had raised was a bad one – a question that could lead only to meaningless debates and controversy over definitions. He termed it, “too meaningless to deserve discussion” (Turing, 1950). In its place, Turin proposed the Imitation Game or the Turin Test (TT) to find out whether a machine or a computer is actually capable of thinking. Other scholars have tended to be even more conservative. There is no doubt however that the world at large has been divided into two distinct camps with radically opposing views since the very early days of the computer. Just a couple of years after Turing had raised the question on the capability of machines to think, Wilkes (1953, pp. 1230) had written about the two common but contrary attitudes towards machines. “Two contrary attitudes,” he stated, “are common. In the first place there is a widespread, although mostly unconscious, desire to believe that a machine can be something more than a machine, and it is to this unconscious urge that the newspaper articles and headlines about mechanical brains appeal.” “On the other hand, many people passionately deny that machines can ever think. They often hold this view so strongly that they are led to attack designers of high-speed automatic computing machines, quite unjustly, for making claims, which they do not in fact make, that their machines have human attributes. Such people are often misled by the use of technical terms based on physiological analogies; a good example is the use of the word memory,’ for the part of the machine in which numbers are stored.” The intensity of conviction in both the camps and the basic reasons behind such beliefs hold good even today. Role of the Popular Media The popular media has played and continues to play a crucial, but often misleading, role in the formation of opinions such as the possibility of Artificial Intelligence to replace human intelligence. The relation between the media and the public has always been bi-directional. The media has as often reflected the views of the public as it has played a role in shaping others: “Sometimes the media reflect a cultural anxiety or perspective, as much as they create it. Detailed research into how media influence operates rarely identifies a simple, one-way, causal route. Early notions that the media act as a ‘hypodermic’ directly injecting ideas into people’s minds have now largely been discredited.” Kitzinger(2003, pp. 45) In the case of views on science and technology specifically, the media has played a crucial role in reflecting public views as well as shaping them. When it comes to technology issues that is beyond the grasp of the lay person, the role of the media in shaping the public views become more prominent as made clear by Nelkin (1987, pp. 123): most adults in fact become informed about science and technology through the media . . . public understanding of science and technology is critical in a society increasingly affected by their impacts and by policy decisions determined by technical expertise . . . . for most people the reality of science is what they read in the press. They understand science less through direct experience or past education than through the filter of journalistic language and imagery. With the exception of an occasional television program or radio notice, newspapers and popular magazines are their only contact with what is going on in rapidly changing scientific and technical fields, and their major source of information about the implications of such developments. Either way, the role that the media has played in portraying the developments in the field of computer science has served to promote the images of machines in general and computers specifically as capable of thinking. It has been so because as with other science and technology issues, the development of the computer has also been reported in the media with other interests in mind. One such common tendency has to sensationalize news to attract readers or viewers to the extent that the news itself gets distorted. In the case of science and technology another trend was to avoid description of complex issues due to pre-defined assumptions the interest or understanding level of the audience. The media has always been prone to attribute almost every new development in the field of computer science with human faculties. This has been very evident in the case of the development of computers as pointed out by Martin (1993, pp. 120): “Much of what the public believes about computers is rooted in the way journalists have described a ‘computer revolution’ in the same utopian terms that the technological revolution of the 1880 – 1930 time period had been previously described. During the early years of the computer revolution between 1940 – 1960, a large segment of the public came to believe the myth that the computer was an awesome thinking machine … this mythical perception of computers could be traced to the science representation of computers as robots, monsters or huge brains such as in the 1927 Fritz Lang film Metropolis.” The use of metaphors relating to human thinking and intelligence is also evident in media reports in the early days of the computer. The unveiling of the ENIAC computer in 1946 generated a lot of public interest throughout the US and Europe. It was the public’s first view of large-scale, high-speed computers. ENIAC was called a brain and was pictured in the June 1946 issue of the ‘Mechanix Illustrated’, superimposed over a brain. The ‘Philadelphia Inquirer’ carried the headline, ‘Army’s New Wonder Brain and it Inventors’; the ‘New York Herald Tribune’ chose ‘Electronic Brain computes 100-year Problem in 2 hours’; and the ‘Newark Star Ledger’ carried the headline, ‘Computing Super-Brain Aids Army’. The British Broadcasting Company, in an article on Artificial Intelligence states that examples of working AI is all around us in computer games, cruise control of cars and in mail servers. The article goes on to assert that “the worlds most powerful supercomputer can carry out 100 trillion operations per second, which some scientists believe could be approaching the processing power of the human brain” (BBC, 2004). Those from the scientific community who were associated with the development of computers had tried to put matters in their proper perspectives. In a November 1946 article on the British ACE computer, Alan Turing had deprecated any notion that a machine could be a complete substitute for a human and had opined that “the fashion which has sprung up on the last 20 years to decry human reason is a path which leads straight to Nazism. (Martin, 1993, pp. 129) However, as people come into closer contact with machines like the computer and start using them as tools to execute different works in their day-to-life, and especially with the new computer-spawned generation taking stock of things, the myth of the thinking machine amongst the public is fast losing ground. In her study about the psychological effects of computers on people, Turkel (1997) has commented that computers have changed the way people think about themselves, about thinking, and about intelligence. In the Driver’s Seat: Technology or the User? The rapid development of Information and Communication Technology (ICT) has brought in unprecedented changes in the way of living of people. Computer systems, the Internet and the Web have become a way of life itself. Computer technology has developed by leaps and bounds. Systems are growing more and more intelligent in the sense that they can perform more and more complicated and complex tasks. Not only so, computing technology has also entered realms which were up till now thought to be the exclusive domain of the human mind. On the other hand, the Digital Divide is also being bridged at a very rapid rate. ICT is permeating into almost every nook and corner of the world. In such a scenario it is very essential that people understand, comprehend and appreciate the exact character, potentials and limitations of the very technology that is affecting their lives. Having the right perspective on the technology could enable the users to shape the technology rather than allowing the technology to determine the course of social and organizational change. A wrong perception of the intelligence of machines could lead to awe and a certain element of hesitancy on the part of the individual to embrace or utilize the new technology – an attitude that could adversely affect the popularity of any machine or technology. There could be other consequences. Hendler (2006) cites in his editorial an example of how, on the eve of the Wright Brother’s precedent-setting flight at Kitty Hawk, the US army had been in fact been cutting funds to flight research because of the compelling arguments that human flight was an impossibility. When Simon Newcomb, one of the most famous scientists of his day remarked, “Flight by machines heavier than air is unpractical and insignificant, if not utterly impossible,” people were more willing to believe him than the two bicycle repairmen from Dayton, Ohio. False beliefs and conceptions therefore put a restraining bridle on scientific and technological development. It works in the other way too. The Case of Artificial Intelligence The case of Artificial Intelligence (AI), on the other hand, has been a prime example of even the scientific community stumbling in their over zealousness. John McCarthy introduced the concept of Artificial Intelligence in 1956. But AI was soon over hyped and it resulted in disappointment and a downslide in AI research funding. Moravec (1998) wrote: “In the 1950s, the pioneers of AI viewed computers as locomotives of thought, which might outperform humans in higher mental work as prodigiously as they outperformed them in arithmetic, if they were harnessed to the right programs... By 1960 the unspectacular performance of the first reasoning and translation programs had taken the bloom off the rose.” There was however a resurgence in the interest in AI in 1981. Though terms like ‘intelligent knowledge-based systems’, ‘expert systems’, ‘knowledge engineering’, and ‘multi-agent systems’, were used more in place of AI, it was nevertheless what was termed as the ‘fifth generation’ AI in the context of the Japanese endeavour. But yet again, the potential of AI was overestimated. AI promises on speech recognition and natural language understanding, machines rivalling human intelligence and educating themselves, all went undelivered. By 1990, AI itself was again relegated to the back burner. It was at this stage that there was a paradigm shift in Artificial Intelligence. Many researchers felt that trying to emulate human thinking in its entirety, or even trying to mimic the human ability to solve problems and achieve goals in the real world, as was envisaged in what was termed ‘strong AI, was indeed very farfetched. A series of conceptual breakthroughs would be required for such achievements. Instead, the focus was shifted on to what came to be known as ‘weak AI’ – “applications that model some, but not all, aspects of human behavior.” (Arnal, 2003, pp. 10) However, with the advent of the Internet, interest in AI has been revived again although in combination with the Human-Computer Interaction (HCI) approach. The developments in ICT have breathed new life into the effort to build a machine capable of human intelligence. Researchers, especially in the field of Artificial Intelligence are optimistic that the ‘AI Winter’ has ended. A paper by Kurzwel (2006) on the advances in AI is titled ‘Why we can be confident of Turing Test Capability within a Quarter Century.’ ‘Strong AI’ is now not defined in terms of equalling human intelligence but in terms of exceeding it in the new AI concept of ‘Singularity’. A set of new and powerful tools is behind this new-found AI enthusiasm. . The claim that a ‘thinking-feeling’ machine had been designed was made by none other than the US Army Armament Research, Development and Engineering Department (Scanlon & Johnson, 403). The study was based on the approach of using the mammalian brain as a model, and investigating the possibility of duplicating its functions in electronic circuitry. This extension of neural design was termed Non-Living Intelligence (NLI). In an article on Ray Kurzweil the AI expert, New York Times even as recently as in June 2008, has reported that Kurzweil is confident that “by the 2020s we’ll be adding computers to our brains and building machines as smart as ourselves” (Tierney, 2008). For the pioneers of Artificial Intelligence, intelligence was the accurate application of well-defined rules to a set of symbolic objects (Grudin, 2006). If intelligence is strait-jacketed so, then computer systems that perform complicated calculations, or the Deep Blue machine that outplays grandmasters in chess can very well be termed intelligent machines – machines that can think. Few would however agree to such a definition of intelligence. It does not take into account the uncertainties of life. The basic question in this roller coaster history of Artificial Intelligence has always been whether Artificial Intelligence would ever be able to measure up to or even replace human intelligence. Conclusion It is therefore evident that all development in technology is proceeding towards the ultimate goal of replicating human intelligence in machines. The scientific community and the popular press basically hold very similar views on the possibility of Artificial Intelligence replacing or equalling human intelligence. The scientific community want to or rather have to believe in the possibility as they actively work towards making it a reality. Scholarly papers written by the scientific community are however guarded in their presentation. First, they equivocally accepted that machines have not achieved the level or quality of information processing that can be equated to human-level intelligence. Second, there is confidence in the scientific world of today that machines will possess human-level intelligence some time in the future even if not within another quarter of a century as claimed by Kurzwel (2006). The popular press on the other hand is given to going overboard at the slightest of excuse and at every technological breakthrough to claim time and again that Artificial Intelligence has equalled or even surpassed human intelligence. This tendency of the popular press or media can be attributed to a bid to attract the readers’ or viewers’ attention in order to secure commercial advantage at the cost of a more reasoned and practical presentation of facts. References Popular Press Arnal, A., H., 2003, Future Technologies, Today’s Choices, Nanotechnology, Artificial Intelligence and Robotics; A technical, political and institutional map of emerging technologies. A report for the Greenpeace Environmental Trust. BBC, 2004, Artificial Intelligence (AI), Science & Nature, Hot Topics [Online] Available. http://www.bbc.co.uk/science/hottopics/ai/ [July 23, 2008] Kitzinger, J., 2003, The role of Media in Public Engagement, Engaging Science: Thoughts, deeds, analysis and action. [Online] Available. http://www.wellcome.ac.uk/assets/wtx032695.pdf [July 23, 2008] Martin, C.D., 1993, The Myth of the Awesome Thinking Machine, Communications of the ACM, April 1993/Vol. 36, No. 4 Tierney, J., 2008, The future is now? Pretty soon, at Least, New York Times, [Online] Available. http://www.nytimes.com/2008/06/03/science/03tier.html?_r=1&oref=slogin [July 23, 2008] Scholarly Journals Berkeley, E., C., 1949, Giant Brains, John Wiley & Sons, New York. Grudin, J., 2006, Turing Maturing: The Separation of Artificial Intelligence and Human-Computer Interaction, Interactions, pp. 54 – 57. Hendler, J., 2006, Fly, but not like an Eagle, IEEE Intelligent Systems, IEEE Computer Systems, 1541-1672/06/$20.00 © 2006 IEEE Kurzweil, R., 2006, Why we can be confident of Turing Test Capability within a Quarter Century. Will Machines Become Conscious? [Online] Available. http://www.kurzweilai.net/meme/frame.html?main=/articles/art0683.html? [October 20, 2007] Moravec, H., 1998, When will computer hardware match the human brain? Journal of evolution and technology, 1, 1. Nelkin, D., 1987, Selling Science. W.H. Freeman, New York. Reddy, R., 1996, The Challenge of Artificial Intelligence, Computer, October 1996, 0018-9162196185 00 @ 1996 IEEE Scanlon, R., Johnson, M., 1998, Machine Emotion, US Army Research, Development and Engineering Centre, Benet Laboratories. Turing, A. (1950), Computing Machinery and Intelligence, Mind 59(236), pp. 433–460. Turkel, S.,1997, Life on the screen: Identity in the Age of the Internet Simon & Schuster, USA: NY paperback reprint, ISBN: 0684833484 Read More