Drowning in a Sea of Information - Essay Example

Drowning in a Sea of Information Introduction Information overload is a simple concept but dealing with the problems created by an excess of information is anything but simple. Like the quote given by Herbert Simon, there are many other instances where our modern life is said to be filled with useless data and messages which have no relevance to us. However, there are cases, businesses as well as theorists who show that information overload is actually a good thing since this wealth of information can be sifted, mined and utilized to gain positive benefits. Theoretically and practically, the method of handling information comes from the same tools which are used to create vast amounts of information i.e. computers. While information overload is certainly a reality, artificial intelligence and other mechanisms which allow the sorting and prioritization of information can help in reducing this burden. In essence, the problem is to develop such systems which are as intelligent or perhaps more intelligent than human beings. The business side of the problem of information overload can be handled through data mining and the application of relevance which allow companies and business professional to decide which information is important and which is not. Artificial Intelligence At the present time in the field of artificial intelligence, it is reasonable to say that while some AI systems mimic human intelligence, there is no system in the world which surpasses a human in all aspects of thought, intelligence or even social interaction. However, it is also plausible to say that the rate of development of current machines means that at some point the future, there will certainly be a time when AI based systems become more intelligent than the humans who created them in the first place. Kurzweil’s The Age of Spiritual Machines (1999) presents a very detailed look at the future of artificial intelligence in terms of where they are going and what can be expected of them in coming decades. He focuses on machine intelligence and shows that the evolution of machines has taken a similar path to the evolution of biological creatures but at a much more accelerated pace. Kurzweil describes how computational and processing power has grown exponentially in the past and records were broken as expectations were shattered. For instance, it was once thought that no computer would ever be able to beat a grand master champion at chess but the best human player in the world has been defeated by a computer specifically created for that purpose. For machines which are specifically created to handle tremendous amounts of data and glean relevant information from the data, even volumes of information should not be problem if there is enough processing power within them (Kurzweil, 1999). While Kurzweil (1999) discusses the rise of computers as tools for handling information, he also discusses their limitations when it comes to physical limitations in terms of processor size and computational power. He suggests that the computers of the future may take a different direction altogether by using biological elements or even quantum mechanics but no definite viewpoint can be given on that since such products are still in early development. The direction that computer scientists as well as the technology market take with the next generation of computers will be the only sure explanation. However, we can be very certain that future computers will only become more powerful and more able to handle vast amounts of information. The ability to handle information would also be helped by the fact that the future of computers connects strongly with artificial intelligence which goes beyond the thrashing problem. The thrashing problem will certainly come up as systems become more intelligent but at present it seems that brute force is the only way to enhance the capabilities of computers when all other means have been completely exhausted. While AI may be seen as one way to deal with information overload, there are variations on what can be defined as an intelligent computer and what can be taken as a good measure to evaluate an AI construct. Kurzweil (1999) holds the opinion that the future of the information age will establish a convergence of man and machine where machines will be embedded within human beings to help them process information at a much faster rate with greater efficiency. These would not be wearable computers but embedded computers which help humans deal with all sorts of information regardless of the source of the data. It must be noted that while such as future may be far off, it is certainly not inconceivable. On the other hand, there are others who believe that machines will never be able to understand the essence of humanity or behave in the ways human beings do with regard to sorting and handling information as well as understanding its relevance. Ackely (2001) believes that the expectations we have had of AI have been over inflated by the ideas projected in the media and the Star Trek like vision of the future where computers evolve to a point to replace doctors. The interpretation of the future of AI as suggested by Ackley seems to be closer to HAL in 2001: A Space Odyssey rather than the informative as well as intelligent friend envisioned by Kurzweil (1999). Further, there are those who think that there would be no need for human beings in the future since the amount of information and the methods to handle such information would be completely beyond the capacity of a human being. The future will become governed by machines and technology to the extent that human participation or governance will only lead to inefficiencies in the decision making process. Joy (2000) describes his interactions with other computer scientists and information age professionals to come to the conclusion that the role of the human being with regard to the future may be subservient to machines. While this idea may be quite scary, the method by which Joy arrives at the conclusion is quite logical. He begins his argument by presenting the machines of the future which are far more ‘intelligent’ and thus better at every logical interpretation and information processing than human beings. With such machines, all management related decisions would be better handled by large, interconnected thinking machines which need no human input. The machines would also be powerful enough to make their own decisions and thus would be able to choose their own destinies making humans unnecessary. His scenario comes to a point where the future of all the people on the planet remains at the whim and fancies of the machines that control them. Joy (2000) does not take his argument to the point that a war could take place between machine and man for the control of the world; nor does he suggest that we be aware of a coup led by machines against human control but he does say that humans may willingly give up control since the machines would be so much more efficient at handling information than humans. While this may be a dark picture of the future, it is not very different from the ideas given by Kurzweil where man and machine live as symbiotic beings. The theoretical visions of the future with regard to information processing can be said to be no different than the visions of the present presented by some of the greatest thinkers of the past. Fiction writers from hundreds of years ago talked about a world where the moon would be an inhabited region and permanent settlements would be made by humans in space as well as on other planets. They also predicted that carts would go without horses and towers would be built to rival the heights of mountains. Many of these predictions have certainly come true, we may not have colonized the moon yet but we have certainly established a permanently manned station outside the earth i.e. the international space station. Cars and airplanes now transport millions of people and the title of the tallest tower in the world seems to change on a yearly basis. Therefore, it is not unreasonable to think that future AI machines will have the same level or surpass the intelligence of a human being in terms of handling information which will give us the means of handling the tremendous amounts of information we have or will have then. The Current Business Situation In the real world however, businesses appear to already be doing the same as they are handling vast amounts of data to glean relevant information through the use of computers. Levy and Powell (1998) suggest that a large part of the flexibility and adaptability shown by many enterprises is due to their information systems and various technology based tools that help them compete with other companies. Information systems can be used in the real world to gain business advantages and understanding the types of information systems becomes essential when it comes to knowing how they can help a company (Boxall and Purcell, 2003). While there can be several types of information systems, the most important ones remain Transaction Processing Systems, Decision Support Systems and Expert Systems. A transaction processing system collects and processes information about various transactions that take place between two or more parties. It also administers certain characteristics of a transaction depending on the requirements of the users or the given flexibility of the system. For instance, a checkout counter at a store is a part of a transaction processing system which may be connected to various other information processing systems that handle reordering of stocks or allow for the approval of purchases which used credit cards or debit cards (Kelly, 2006). Such systems generate tremendous amounts of information but for the most part the results can be condensed and summaries except for various issues which come up during transactions that may require human corrections or approvals. Without these systems, a company may find it impossible to manually handle a large number of transactions on a daily basis (Kelly, 2006). For large enterprises, the volumes of data handled by these systems and the number of records created, edited or processed on a daily basis can run into millions such as the number of transactions handled per day by Amazon.com. Companies such as Wal-Mart and other retailers depend on the efficient running of these systems since the information gathered from them can help in making real-time strategic choices. The stakeholders in this system are all parties that are involved in the transaction process as well as those who are going to make decisions based on the results of the transactions that take place. These decisions are also helped by the decision support system which is a type of information system that helps managers make strategic decisions. These information systems work with the input given to them from other information systems such as transaction support systems, human resource management systems etc. They are particularly useful when a company or a manager wishes to create ‘what if’ scenarios to see what impact certain decisions can have on the company (Kelly, 2006). For example, if a company wishes to attain a certain target with regard to sales, one possible method of getting that target would be to reduce prices. However, the reduction in prices can also impact other aspects of the business therefore a company has to go use a DSS which can let a financial expert see the impact of a reduction in prices on other sectors of the company. In essence, any party which has something to gain or lose from the decisions created with the help of the DSS is a stakeholder to some level in a Decision Support System. A combination of these systems results in a more complex system of handling information which can be considered an expert system. Theoretically, it is a system which can replicate the expertise of a human being in a given field. The concepts of Artificial intelligence figure largely in this type of system since an expert system seeks to capture the knowledge and the reasoning ability of a human. This requires a vast knowledge base as well as a database for rules that let the expert system make sense of the information and the given data to give guidance and suggestions (Kelly, 2006). Of course such expert systems can be used by anyone involved in decision making or evaluating any course of action when a large amount of data needs to be processed and evaluated. For instance, in a theatre of war, aerial photographs of a given region could be processed into an expert system whereby the system can mark those photographs that seem to contain points of military interest or those which appear to be strategically important. While a human being might be able to analyze hundreds of such pictures in a day, an expert system would be able to process millions of such images in the same time which certainly puts the computer at an advantage. Information Systems to Handle Information Coming back from defense applications to the real world of business, we see companies use information systems to their benefit in many different ways. One example comes from Equation Research which is a small company that does not even have a physical office but manages its entire seventeen person staff from the internet using the information systems they have created for themselves. They specialize in getting research done for other companies and conducting product and service related surveys (Rupley, 2005). In fact, information and the idea of generating vast amounts of useful information is the basic premise of their business. Levy and Powell (1998) suggest that the information systems and the organizational purposes for which the technology is used affect the usability and usefulness of the information which is created. Simply stated, if the information systems used by the company are adaptable and flexible, the company will become adaptable and flexible as well since it will be more able to handle the information it creates (Young & Francis, 1993). This is the case for Equation Research since according to Rupley (2005): “The employees — most from project management backgrounds, some with statistical training — are scattered about eight states. A dozen servers (mostly Dell machines), Linux operating systems, SQL databases, firewalls, and password-protected security implementations keep Equations surveys running smoothly (Rupley, 2005, Pg. 84)”. Given the information system technology Equation Research has at their disposal and with the secure information framework that they have, it comes as no surprise that they manage to deliver information without overloading their clients with irrelevant data. Rupley (2005) praises the company for having a high level of flexibility as well as providing means for generating and handling information which prevents uncertainty and risk that are two major problems which can be created with information overload. Links between Information Systems Information overload also creates uncertainty which can certainly come into play when dealing with tremendous amounts of data such as the data generated by weather prediction systems. Wheeler et. al. (2005) use the example of small farmers and the agriculture industry which is constantly dealing with the uncertainties of local weather. Their suggestion, as well as the given solution to the problem of uncertainty is a close coordination of various information systems including weather predictions, genetic engineering for crop seeds and farm management systems which are all connected through technology. Their aim is to reduce uncertainty generated by information overload through the creation of mathematical equations and predicting patterns for climate that are based in physics, chemistry and biology. It is certainly an innovative solution for overcoming information overload but it connects deeply with allowing machines to make decisions where humans simply cannot process such volumes of data. Dester and Blockley (2003) also make extensive use of information management tools and decisions support systems to help small companies overcome any information overload problems especially when it comes to dealing with assets such as the usefulness of machinery. They made an extensive study of the construction industry and suggested that companies can better manage risks if they integrate various risk management procedures into a larger checklist rather than be bogged down by information about each incidence of use. More importantly, they use construction accident and evaluation reports as evidence to prove that few failures happen completely out of the blue. By effectively using present information a perceptive manager or even a computer system can spot uncertainties before they become obvious to everyone else and can suggest actions to prevent losses. Clearly the importance of observation and established systems of handling information cannot be stressed enough since Hall et. al. (2004) report on a software based tool to assess the performance of assets which can let a person make decisions on further investing time and money in particular investments. This software tool attempts to quantify nearly all of the variables associated with a given asset so that the business decisions can be made without emotional leanings. In fact, this supports the ideas given by the Economist (2004) which say that we should think like machines when it comes to evaluating investment decisions in the face of uncertainty or when information is not as much as we would like it to be. On the other hand, when the relevant information is present, information systems can become a symphony which leads to more profits and more business for a company. For example, a very small company such as Oriel wines was the subject of the cast study by Chozich (2005) shows how a lot of information can be translated into a lot of profit. The company is a producer and supplier of wine which uses the internet to give their clients an image of a company which seems to be much larger than it actually is with a supply chain which runs from California to Germany and as far as Japan. The company is quite simple in structure, but the organisation of such an effort depends on several very complicated information systems which work together to make the company appear to be much larger (Johnson et. al., 2005). Using Information Positively Chozich (2005) tells us that Oriel Wines sells more than twenty varieties of wines from around the world and it appears to have offices in Europe as well as in America. In reality however, they employ only a staff of six persons. What they use to get the advantage of size is the creative use of information systems that give them better overall footing (Segal-Horn & Faulkner, 1999). They can do this because even a team comprising of one person can use online tools like PayPal, yahoo merchant stores and eBay which handle a lot of information on the backend to ensure that they become a part of the business world and can have their share of the global business pie if they are dedicated professionals. Companies such as Oriel Wines can handle information generated by them automatically through email services that create Amazon like recommendation pages for their clients, in effect this makes them appear to be more on top of things and thus seem larger in size. Deliveries, supply levels, shipping procedures and various other information generating operations which require control over the supply chain are automated with technology based service providers (Chozich, 2005). Instead of being overloaded with information, the company outsources information handling procedures to other organisations which specialise in such activities. These information related activities include the handling of distribution lists, client contact information storage and related information that are handled by outsourcing service providers such as Constant Contact who maintain mailing lists and provide email services for monthly fees allowing the company to focus on its core competencies (Chozich, 2005). Conclusions As far as information overload is concerned, the best method for handling information overload today appears to allow other systems or other companies to handle the vast amounts of information generated by businesses activities. For the future, it seems that information handling abilities of the computers of tomorrow will develop to an extent which will make the idea of information overload an archaic concept. Until that future is here, individuals and businesses who can create innovative methods of handling information overload will continue to be more successful than those who do not. Works Cited Ackley, D. 2001, Artificial intelligence 2001: a disappointment? [Online] Available at: http://www.economist.com/science/displayStory.cfm?Story_ID=883645 Boxall P. and Purcell J. 2003, Strategy and Human Resources, Palgrave & Macmillan. Chozich, A. 2005, ‘Managing Technology; Appearances Are Deceiving’, Wall Street Journal. 19 Sep, p. R7. Dester, W. and Blockley, D. 2003, ‘Managing the uncertainty of unknown risks’, Civil Engineering & Environmental Systems, vol. 20, no. 2. pp. 83-104. Economist. 2004, ‘Freud, finance and folly’, Economist, vol. 370, no. 8359, pp. 5-6. Hall, J. et. al. 2004, ‘A decision-support methodology for performance-based asset management’, Civil Engineering & Environmental Systems, vol. 21, no. 1, pp. 51-75. Johnson, G. et. al. 2005, Exploring Corporate Strategy, Prentice Hall. Joy, B. 2000, Why the future doesnt need us. 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