Information overload is a term first used in the early 1960s to indicate limits to human information handling capacity (Meier 1962) and later by Toffler (1970) as one dimension of “future shock,” by which he broadly meant too much change in too short a time. Computer communications and the Internet have contributed to the realization of this “shock,” sometimes also referred to as “techno-stress” (Weil & Rosen 1997). The term “information overload” has its roots in the context of computer-mediated communications, where it might typically be applied to an individual who receives a large number of emails per day and who experiences some difficulty in processing the volume of information. Lest one is tempted to think of information overload as a new problem, let us recall the words of T. S. Eliot (1934), “where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?”
Dimensions In Information And Information Overload
Eliot reminds us that turning information into knowledge is not easy and is far from automatic. It is important to understand the process by which data is or can be transformed into knowledge. Since the advent of computer-based data processing there has been a vast increase in the capacity and capability for storing data and transforming it into information that can be used in decision-making. The definition suggested by Ackoff (1989, 4) that “information is data that has been given meaning by way of relational connection” is confirmation that information contains meaning. A further way of looking at this is to suggest that the processing of data into information helps to answer questions of “who,” “what,” “where,” and “when.” Knowledge is used to answer “how” questions. Wisdom is, according to the Oxford English Dictionary, “experience and knowledge together with power of applying them.”
The very possibility of information overload appears paradoxical in the sense that conventional wisdom has it that more information leads to improved decision-making. So just what are the dimensions of the problem of information overload? One perspective is to examine the growth of information. A study by Lyman and Varian (2003, 1) at the University of California at Berkeley found that “print, film, magnetic, and optical storage media produced about 5 exabytes of new information in 2002. Ninety-two percent of the new information was stored on magnetic media, mostly in hard disks. . . . If digitized with full formatting, the seventeen million books in the Library of Congress contain about 136 terabytes of information; five exabytes of information is equivalent in size to the information contained in 37,000 new libraries the size of the Library of Congress book collections.”
This quantitative perspective on information overload needs to be complemented with a qualitative viewpoint. Is there some confusion about data and information? What is the quality of the information received? Was the information relevant, timely, accurate, and complete? Some manifestations of information overload could be due to irrelevant, incomplete, or inaccurate information. In other words, some information overload could more properly be classified as information pollution (Nielsen 2003).
A further perspective is to consider the reach of information overload, in other words, as between people who have access to digital technologies and those who do not. This can be considered from either a national or an international perspective. The former tends to be based on socio-economic issues and the latter on geographical boundaries, with a very low proportion of the population of developing countries having access to information and communication technologies. Information overload tends to be a problem for those living in relatively prosperous countries who work in knowledge-based sectors of the economy.
Finally, there is a sense in which overload can be a symptom of too many information channels open at any one time. For example, in an office environment email, telephone, mobile phone, instant messaging, VoIP, and SMS all compete for our attention. Recent research suggests that it takes several minutes to recover from an interruption. This phenomenon has been called interruption overload (Rigby 2006). Potentially there is a sense in which the presenting problem of information overload could be a symptom of either information pollution or interruption overload.
Consequences Of Information Overload
Saying less often communicates more. There is a tendency with electronic communications for there to be more detail, from which users have to extract useful information. The danger is that some users may “tune out” and thereby miss important information contained in the mess (Nielsen 2003).
For human-to-human communication to be successful there is a need to supply a context to transform the data into information (Kimble et al. 1998). In face-to-face communication, this happens quite naturally. However, in electronic communication many contextual clues are missing. Grimshaw et al. (1997) focus on the concept of context as a key to transforming machine data into human information. Taking Wilson’s (1984) definition of information as data plus context, we can conclude that meaning is conferred in a particular context. Here, context is discussed in relation to meaning, highlighting problems where failures in communication or “breakdowns” occur.
Another way of dealing with information overload may involve, in the future, notions of pervasive computing (Kenny 2006). A possible scenario for the future is one where computer technology becomes so pervasive that it is embedded in everyday objects such as clothing, traffic signals, passports, etc. There would then be socalled “traces” left by people who move around undertaking transactions. Profiles of activities and individuals could thereby be drawn up much more easily. The notion is that greater contextual knowledge of activities would lead to information that could be assimilated and used more effectively. In this way information overload would be reduced. Or, in other words, an increase in information would not lead to indigestion; rather it would lead to enlightenment.
However, the above approach might be perceived to involve threats to the privacy of individuals. As more information about individuals, especially related to their transactions and movements, is captured there is a danger that such information could be abused.
Key Research Questions
One of the key research issues in this area is the development of search engines that can be sensitive to context, meaning, and validity. As we produce more information there is a corresponding need to search, find, and evaluate the results of searches. Arthur (2006) points out that the Google search facility will often lead to a Wikipedia page. Since the top of the results list gets 42 percent of the click-throughs, this raises important questions for the validity of the results. Academic research, for example Montebello (1998), argues that information overload is essentially an information retrieval problem. However, there are two parts to this issue: first, an effective search strategy, and, second, a means of discriminating between the results on the basis of relevance, timeliness, and accuracy.
Some authors, including Maes (1994), have suggested that using intelligent agents will be the solution to information overload. This is essentially the application of artificial intelligence to help the user search through information. The key issues here revolve around the need to be able to know when to trust the agent and the agent itself being able to acquire the knowledge needed to interpret the information.
A further question to ask is: do some media lead to more information overload than others? For example, it might be that the use of email, compared to an intranet, leads to higher levels of overload. This might be because, in general, most people prefer to “pull” information rather than have it “pushed” to them.
Information overload has been a recognized feature of computer-mediated communications for the past 30 years. With clear evidence that more information is being held on computers each year, will information overload continue to be a problem or will the increasing power of computing bring with it techniques and methods that begin to reduce overload? Whatever the answer to that question might be, we can begin to manage our own individual information overload by ensuring that we filter for quality, relevance, timeliness, and accuracy. The ultimate goal of reaching wisdom depends on how each of us manages information in relation to our experiences in life.
References:
- Ackoff, R. L. (1989). From data to wisdom. Journal of Applied Systems Analysis, 16, 3–9.
- Arthur, C. (2006). Top of the heap. Guardian, August 31. At http://technology.guardian.co.uk/weekly/story/0,,1861112,00.html, accessed March 3, 2007.
- Eliot, T. S. (1934). The Rock. London: Faber and Faber.
- Grimshaw, D. J., Mott, P. L., & Roberts, S. A. (1997). The role of context in decision making: Some implications for database design. European Journal of Information Systems, 5(4), 113 –122.
- Kenny, L. (2006). Exploring the business and social impacts of pervasive computing. Zurich: Swiss Re Centre for Global Dialogue.
- Kimble, C., Grimshaw, D. J., & Hildreth, P. (1998). The role of contextual clues in the creation of information overload. In D. Avison & D. Edgar-Nevill (eds.), Matching technology with organisational needs: Proceedings of 3rd UKAIS conference. Reading: McGraw-Hill, pp. 405– 412.
- Lyman, P., & Varian, H. R. (2003). How much information? At www2.sims.berkeley.edu/research/projects/how-much-info-2003, accessed March 3, 2007.
- Maes, P. (1994). Agents that reduce work and information overload. Communications of the ACM, 37(7), 31–40.
- Meier, R. L. (1962). A communications theory of urban growth. Cambridge, MA: MIT Press.
- Montebello, M. (1998). Information overload: An IR problem? In String processing and information retrieval (SPIRE): A South American symposium. Washington, DC: IEEE Computer Society, p. 0065. Abstract at http://doi.ieeecomputersociety.org/10.1109/SPIRE.1998.712984, accessed March 3, 2007.
- Nielsen, J. (2003). Information pollution. At http://useit.com/alertbox/20030811.html, accessed March 3, 2007.
- Rigby, R. (2006). Warning: interruption overload. Financial Times, 26 August. At www.ft.com/cms/ s/d0f71fb6-3243-11db-ab06-0000779e2340,dwp_uuid=4e612cca-6707-11da-a650-0000779e2340,print= yes.html, accessed March 3, 2007.
- Toffler, A. (1970). Future shock. New York: Bantam Books.
- Weil, M. M., & Rosen, L. D. (1997). TechnoStress: Coping with technology @home, @work, @play. New York: John Wiley.
- Wilson, B. (1984). Systems: Concepts, methodologies and applications, 2nd edn. Chichester: John Wiley.