An Annotated Bibliography on Artificial Intelligence

Artificial Intelligence (AI) has been in development since the early 1950s and continues to be an area of great discussion, interest, and conflict among scientists. AI broadly indicates that an object having the ability to perform and function in ways characterized by human thought (Encarta, 2005). This topic has been fictionalized through film with the development of HAL the ill-tempered computer, and in the movie AI where the boy begins to develop feelings. These are only a couple of examples that lead to fevered discussions and even arguments, among scientists and futurists in regard to the abilities of AI. Many people are not convinced that true AI will ever be developed, but some continue to strive for this creation.

AI usage has become more prevalent in computing, business, military, and even medicine. The AI systems discussed in this annotated bibliography are used to create "thinking and learning" machines. These systems take computers beyond basic programming, but despite sophistication, these systems still do not approach the complexity of true intelligent thought.

This annotated bibliography is a tool to be used by people exploring the topic of AI. Most of the works reviewed are written for the general public; however, reports that are more technical are also included. AI is an interesting topic on its own, but more remarkable is its uses in business, cyberspace, robotics, and the military.

Booth, C. & Buluswar, S. (2002). The return of artificial intelligence [Electronic version]. McKinsey Quarterly 4. Retrieved April 5, 2005 from http://search.epnet.com/login.aspx?direct=truee&db=buh&an=7576567.

Booth and Buluswar present an excellent overview of numerical analytics systems, rule-based decision systems, and autonomous execution systems. In addition, the authors offer examples of real businesses using each of these systems. Each business has gained some kind of cost or time savings with the use of AI systems in day-to-day operations. The authors discuss a three step process in deciding whether a business should employ an AI system. The implication that AI systems may not be beneficial for every business is an underlying factor, however most of the information provided in the article suggests that these systems are more beneficial than not.

Fried, C. (2004). Can technology build a better buffet? [Electronic version]. Business 2.0 5(1). Retrieved April 5, 2005 from http://search.epnet.com/login.aspx?direct=truee&db=buh&an=12164964.

Fried presents the idea of AI replacing humans in the financial investments arena as complete science fiction. Fried provides insight on the use of this technology in the field replacing financial managers and investment agents,. The author suggests that the use of mathematically-driven calculations would be best used in this field; however, the results from two companies that used artificial investor technology were less than stellar. This article touches on the hype surrounding AI and its uses within the business world. Fried explains that the jobs and the minds of Warren Buffet and Peter Lynch will continue to be safe even though AI systems will continue to develop.

Gibson, K. (2003). Arguing artificially: A rhetorical analysis of the debates that have shaped cognitive science [Electronic version]. Business Communication Quarterly 60(2). Retrieved April 5, 2005 from http://web5.epnet.com/citation.asp?

Gibson presents an extensive discussion as part of his dissertation and bases his rhetorical examination of AI in three topics; "the debate regarding the rhetorical nature of science, the unresolved issue of the social construction of scientific facts, and the relative scarcity of rhetoric-focused scholarship investigating the relationship between AI and rhetoric" (p. 86, para.2). Gibson refers further to what he calls "three key moments of debate" in AI research based upon works by Allen Newell and Herbert Simmons, Rodney Brooks, and Roger Penrose. These works represent findings first beginning in the early 1950s as Gibson examines the history of AI. Gibson summarizes that his work contributes to improving a layperson's understanding of AI, a researcher's ability to develop more persuasive arguments of AI, and assist rhetoricians "describe the construction of scientific knowledge" to groom their students in that understanding.

Greis, N. P., Olin, J. G., & Kasarda, J. D. (2003). The intelligent future [Electronic version]. Supply Chain Management Review 7(3). Retrieved April 5, 2005 from http://web5.epnet.com/citation.asp?

Gries, Olin, and Kasarda discuss the use of intelligent agents, a form of AI, to assist in overcoming the demands of logistics and supply chain management in today's internet age. The authors consider those companies employing AI as one's that will gain a competitive advantage by effectively directing business operations and decision-making in real-time. In addition, Greis et. al. provides an exciting overview of what intelligent agents are and their uses, abilities, attributes, and limitations. The term intelligent agent refers to software that learns from the surrounding environment, run in the background, and wait to act until it is necessary. These agents are more than user initiated programs because they respond automatically to environmental changes, recover from disturbances, and can anticipate and prepare for change. This article further defines AI and intelligent agents, its uses, and how these agents are currently employed in the supply chain and logistics management.

Grupe, F. H. & von Sadovsky, T. (1995). An executive's guide to artificial intelligence [Electronic version]. Information Strategy: The Executive's Journal 12(1). Retrieved April 5, 2005 from http://search.epnet.com/login.aspx?direct=truee&db=buh&an=9508211090.

Grupe and von Sadovsky describe five increasingly popular types of AI systems used in business enterprises today. An entertaining article, first discussing the 2001 film computer HAL, explains expert systems, case-based reasoning, neural networks, genetic algorithms, and fuzzy logic systems. Informative and well written, the authors provide a comparative analysis that is easily understood by even the most newly aware readers. The use of business world examples helps the reader to understand more concretely how these systems work, how they are applied, and for which situations each system is appropriate. Finally, these authors projected a positive view of the use of AI in business and contend that businesses employing AI systems develop a remarkable advantage over those who do not.

Jackson, P. (2005). Artificial intelligence and information retrieval [Electronic version]. Searcher 13(1). Retrieved April 5, 2005 from http://search.epnet.com/login.aspx?direct=truee&db=buh&an=15750111.

Jackson emphasizes how AI systems are used in business as a means to inform a firm's employees for better decision making. Explaining the difference between tools and appliances, the author discusses Don Norman's (USCD) distinction between the two. Tools are objects that enhance a person's skill, but it requires skill to use. Appliances are objects that perform functions without much user input. Applying these two terms to information retrieval would equate a traditional search engine, using Boolean and proximity searches, to a tool; where as an appliance would look more like Google searches. Users of Google still will get some meaningful results even if the search wasn't well crafted. Finally, Jackson promotes AI as a part of design systems, themselves. He suggests that AI information retrieval should act as an accessory to human intelligence. Everyone seems to want access to information at the touch of a button, but no one seems to want to talk with a computer to handle situations.

Lima, P. U., & Custodio, L. M. M. (2004). Artificial intelligence and systems theory: Applied to cooperative robots. International Journal of Advanced Robotic Systems 1(3), pages 141-148.

Lima and Custodio supply a provocative approach to AI and its use with cooperative robots. These robots are used for many areas including surveillance, search and rescue, transportation, and fire detection. In addition, the authors explain that the research and use of cooperative robots in the SocRob program is developing awareness and the ability to use robots to work together and perform separate functions simultaneously. SocRob stand for both the Society of Robots and Soccer Robots. Soccer was used as the vehicle to develop the coordination of robots while performing separate functions of each player on the field. Though the article focused soley on the SocRob research and the methods, applications, and development therein, this article provoked an exciting thought of how these robots could be used in place of humans in very dangerous situations, or even in battle. The potential to limit the destruction of human lives by use of cooperative robots is worth examination.

McManus, J. W., & Goodrich, K. H. (1989). Application of artificial intelligence (AI) programming techniques to tactical guidance for fighter aircraft. Presented at 1989 AIAA Guidance, Navigation, and Control Conference, Boston, Massachusetts, AIAA 89-3525, August 14-16, 1989, pp. 17, (543KB).

McManus and Goodrich's technical report presented at the AIAA conference in 1989 expounded upon my comments of using AI to preserve human life in the preceding article. The report discusses the research program investigating the use of AI to assist in developing a system they call a "Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat" engagements. An overview of the research, application of AI, development, and implementation of TDG provides an in-depth view of the remarkable uses of AI. The authors discuss the history of other AI programs and uses and compare and contrast these systems with TDG. The report presents the test results and findings evaluating the performance of the TDG system versus the earlier AI system and human pilots from Langley Air Force Base in the Differential Maneuvering Simulator. The results of the TDG program shows "significant performance gains" in one-on-one air combat and easier to modify than older AI systems. Though very technical in nature, this report creates awareness with readers to the extensive nature which AI systems can be used.

Moy, C. H. (n.d.). Artificial intelligence, today and tomorrow [Electronic version]. Retrieved April 5, 2005 from http://www.insiderreports.com/storypage.asp?

Moy's light-hearted article prepares the reader with basic knowledge by defining AI, discussing new technology, and providing examples of neural networks, mobile agent systems, fuzzy logic, and genetic algorithms. The non-technical discussion of the aforementioned tools provide relevant information for a person to understand how these tools are used. Though not as powerful as some of the other articles reviewed in this annotated bibliography, Moy implies ethical and moral dilemmas faced with the further development of AI. In addition, the author lists possible AI applications used in business and our everyday lives such as the automatic stock modification agent, the automatic bill paying schedules, and others more farfetched.

Ruggiero Jr., M.A. (2001). Artificial intelligence: The newest answer in market analysis [Electronic version]. Futures: News, Analysis & Strategies for Futures, Options & Derivatives Traders 30(13). Retrieved April 5, 2005 from http://search.epnet.com/login.aspx?direct=truee&db=buh&an=5335686.

Ruggerio focuses on the use of AI in market analysis and building better systems. Like others in this annotated bibliography, the focus is on traders and the systems used to operate in the trading industry. Though current trading systems are mostly statistical by approach, some new theories and systems are being developed by applying the Game Theory to trading systems. The Game Theory is studying the interaction between groups trying to produce the best results. The author explains the cooperative and non-cooperative game theories and applications of each with regard to trading. In addition, examples of business and economic applications of the Game Theory are provided and linked to real-world situations to solidify the readers understanding. This article supplies readers an overall understanding of the Game Theory and how this theory can be applied across many industries and uses of AI.

Scruggs, J. (2005). A.I. researchers struggle with human toll of automation [Electronic version]. Memphis Business Journal. Retrieved April 5, 2005 from http://memphis.bizjournals.com/memphis/stories/2005/01/31/focus4.html.

Scruggs highlights the newest AI technology being considered by FedEx Institute of Technology. AI technologies are being adapted and applied to no-pilot flights and intelligent runways. The use of AI in these capacities brings to light another down side to smart machines, thinking planes, and the computer age - the impact of human labor reduction. The human workforce has decreased with the increase of automation and increased usage of AI will further exacerbate the situation. FedEx IT suggests that AI is simply used as a performance enhancing technology, not one meant to replace humans. Moreover, FedEX IT contends it uses AI for tutoring systems that assist in career and professional development more than a replacement. This article illustrates the struggle businesses face with the human labor issue versus the use of AI in gaining competitive advantages.

Strickler, D. (2003). Artificial intelligence scopes out spam [Electronic version]. Retrieved April 5, 2005 from http://www.nwfusion.com/news/tech/2003/0414techupdate.html.

Strickler's article discusses one of the most annoying attributes to cyberspace and electronic mail systems - spam. AI spam filtering systems that learn and evolve based upon incoming mail and user customization may be the key to getting ahead of spammers. Examples of interpreted emails are provided to show the reader how this system works. A contrasting example of a legitimate email is also provided to show how programs may eliminate wanted emails. Strickler explains that challenges in programs choosing legitimate emails may be difficult in ridding electronic mailboxes from spam altogether, but AI applications and techniques are edging anti-spam closer to the goal. Strickler is able to balance the discussion of technical attributes of programs with everyday language allowing the general reader to gain greater insight to the possibilities and difficulties of spam filtering systems using AI.

Yick, L. T. (2003). The crucial roles of the artificial information systems web in intelligent human organizations [Electronic version]. Human Systems Management 22(3). Retrieved April 5, 2005 from http://search.epnet.com/login.aspx?direct=truee&db=buh&an=11189809.

Yick's complex and technical review of AI and its application in business organizations provides a wealth of knowledge in several areas and systems associated with AI. Yick expanded upon intelligent organizational structures and internal intelligent information systems. Like others in this annotated bibliography, Yick explained artificial neural networks, fuzzy logic, expert systems, intelligent hybrid and other systems and provided examples of business applications for each. The in-depth and technical nature of this report is written more for those in the computer or AI fields. An illustration mapped the classification of intelligent information systems dividing them first into internal and external systems and then further disaggregated the systems into the smaller subgroups (i.e., fuzzy logic). The message delivered by Yick is that AI systems assist with the effective flow of information in business and that a competitive advantage is gained by businesses that use AI in daily operations and knowledge management.

References

"Artificial Intelligence," Microsoft® Encarta® Online Encyclopedia 2005
http://encarta.msn.com © 1997-2005 Microsoft Corporation. All Rights Reserved. Retrieved May 2, 2005, from http://encarta.msn.com/encyclopedia_761567118/Artificial_Intelligence.html).