Cover Image

PAPERBACK
$44.00



View/Hide Left Panel

10
Information Technology and Data in the Context of Developing Countries

Chrisanthi Avgerou

London School of Economics, United Kingdom

Although my affiliation is the London School of Economics, I am not an economist. People assume that the London School of Economics is populated by economists, but that is not the case. I am in information systems, where we study the efforts required to make use of new information. That makes me appreciate the significance of information and communication technologies, as well as the significance of information and data.

It is not enough for organizations to have access to technology or to be able to acquire technology. It is not enough for organizations to have information and data assets, whether internally or externally generated. They also should have the capacity to use all of the technology and information resources to their own advantage. Nevertheless, in our efforts to emphasize the significance of access to data and information in the current discourse of the global information economy and the digital divide, we run some risks. We may neglect some important issues that do not appear significant at the beginning.

I will briefly discuss the risk of reifying data, information, and knowledge. Despite the definitional differences of these three concepts, it is problematic to consider data, information, and knowledge as objects possessing some value that is independent of context and of other aspects within which they are embedded. I will build on that concept and argue for the need for analytical capabilities over and above the need to have access to data and information. In relation to that I will argue for the significance of social sciences, which in my opinion, are weak in many parts of the world.

THE RISK OF REIFYING DATA

The risk of reifying data is the problem of assigning value, assuming that there is value in data and information, without consideration of institutionalized practices, both in terms of where the data come from and also where these data or information are going to be put to use. There is now a whole field, the sociology of science and technology, that has created awareness about the process of scientific and technological development. This process by no means discovers the truth, but rather ends up with packages of knowledge, which tend to be black boxed, and with alternative contested knowledge, which tends to be forgotten with time.

When we talk about public access to scientific data and information, we tend to forget that these resources contain codified information that has acquired legitimacy in specific historical and socioeconomic contexts; at the time of their production there were different research projects or alternative areas of science that for whatever



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 41
Open Access and the Public Domain in Digital Data and Information for Science: Proceedings of an International Symposium 10 Information Technology and Data in the Context of Developing Countries Chrisanthi Avgerou London School of Economics, United Kingdom Although my affiliation is the London School of Economics, I am not an economist. People assume that the London School of Economics is populated by economists, but that is not the case. I am in information systems, where we study the efforts required to make use of new information. That makes me appreciate the significance of information and communication technologies, as well as the significance of information and data. It is not enough for organizations to have access to technology or to be able to acquire technology. It is not enough for organizations to have information and data assets, whether internally or externally generated. They also should have the capacity to use all of the technology and information resources to their own advantage. Nevertheless, in our efforts to emphasize the significance of access to data and information in the current discourse of the global information economy and the digital divide, we run some risks. We may neglect some important issues that do not appear significant at the beginning. I will briefly discuss the risk of reifying data, information, and knowledge. Despite the definitional differences of these three concepts, it is problematic to consider data, information, and knowledge as objects possessing some value that is independent of context and of other aspects within which they are embedded. I will build on that concept and argue for the need for analytical capabilities over and above the need to have access to data and information. In relation to that I will argue for the significance of social sciences, which in my opinion, are weak in many parts of the world. THE RISK OF REIFYING DATA The risk of reifying data is the problem of assigning value, assuming that there is value in data and information, without consideration of institutionalized practices, both in terms of where the data come from and also where these data or information are going to be put to use. There is now a whole field, the sociology of science and technology, that has created awareness about the process of scientific and technological development. This process by no means discovers the truth, but rather ends up with packages of knowledge, which tend to be black boxed, and with alternative contested knowledge, which tends to be forgotten with time. When we talk about public access to scientific data and information, we tend to forget that these resources contain codified information that has acquired legitimacy in specific historical and socioeconomic contexts; at the time of their production there were different research projects or alternative areas of science that for whatever

OCR for page 41
Open Access and the Public Domain in Digital Data and Information for Science: Proceedings of an International Symposium reason were marginalized. The data from these alternatives may still be relevant and in some cases more relevant in the particular context where the scientific knowledge will be used. The institutionalized context within which scientific knowledge is produced can be very important. It is also very important to be able to relate whatever data, science, or knowledge you have with the prospective problem area where the knowledge will be used. There is a considerable effort to emphasize the significance of science in developing countries. It is important to be able to unpack the black boxes of scientific data and be able to interpret them, understand their contextual nature, and make choices that are contextually appropriate. There is, however, something else that we tend to forget, which is the significance of scientists from developing countries being able to participate in the scientific debate worldwide. I would like to share with you a very unpleasant experience I had as the editor of a special issue of a prestigious scientific journal. The special issue was supposed to cover the area of information systems in developing countries. I was an organizer of a conference in 2000 that was convened under the umbrella of the International Federation for Information Processing in the Developing Countries Group. For a number of years the federation had established a tradition of being quite open and inclusive in its participants. The conference organizing group considered it very important to have participants from all over the world to be able to exchange information. The conference was successful and it was decided that a special issue with the best papers presented would be produced. The papers chosen were from authors from both industrialized and developing countries and went through peer-review processes. Unfortunately, two colleagues from developing countries were not able to include their papers in the special issue. Why? Scientific processes are very much institutionalized; there are rituals of writing, referencing, and arguing that are very much a part of our academia. Developing countries very often do not have the capacity to take part and prove their point as competently in these rituals as peer reviewers would like to see. In the end the special issue had only authors from industrialized countries. One lesson to be learned from this is that we should develop the institutions of science in a broad-minded way and perhaps be prepared to change our rituals in order to accommodate more voices. THE NEED FOR ANALYTICAL CAPABILITIES There is also the problem of data acquiring objectivity and universal truth status. There are philosophers and sociologists of science who have argued about the quality of scientific knowledge—that it might be reassessed, that alternative knowledge within science might prevail. Yet, the current perception of scientific knowledge is that it tends to take for granted such knowledge as universal truth. Not only is scientific knowledge not universal truth, but it hides power. By that I do not mean the rather clichéd view that knowledge is power; I mean the opposite. What we take as scientific knowledge, as prevailing truth, is very much an output of the dynamics of power, as I think my example illustrated. My colleagues from developing countries, not having mastered the conventions of writing their ideas in a way that is acceptable within the current norms of the scientific community, lost their voice. Their points simply were not included in a special issue on the very topic of information technology and development. I would like to argue for the need to develop analytical capacities to be able to interpret data and make critical judgments about the validity of data in specific contexts. This is not a trivial issue. You should be able to unpack what is already black-boxed and have the ability to argue for your choices, often against the prevailing legitimate practice. There is also the need to juxtapose alternative context-specific knowledge. For some time there has been a debate within development studies about the relative status of scientific knowledge and indigenous knowledge, an unfortunate dichotomy. It is very important to accommodate alternative knowledge within one’s own epistemology and underlying values. Again, this requires an ability to examine the reified notion of data and information and develop critical judgment about what is relevant, beneficial, and feasible. The development of policies that give a voice to the public and consider their own judgments of issues of relevance to their lives is weak in developing countries.

OCR for page 41
Open Access and the Public Domain in Digital Data and Information for Science: Proceedings of an International Symposium Another weakness of developing countries is social science. Some areas of social science are very much the Cinderella in academia because they are not tangible and do not require labs or technological infrastructure. It is even slightly dangerous to the local elites because it raises some difficult questions. It encourages inquiries into values, thus quickly entering politics. However, the division between science and value judgments or political choices is blurred more and more, making it important to develop scientific abilities in social issues. Social sciences in many respects are different from the natural sciences. They are much more discursive. They require a totally different way of thinking and analyzing that complements that of the natural sciences. I would now like to give an example that illustrates the blurring between data and value judgment, or perhaps judgments and assumptions that have been codified into data (see Table 10.1). Such data and assumptions need examination. These data make associations between the availability of technology or the capacity to use technology and the economic development index. The data were produced by a group of scientists, economists, and information technology experts at Harvard University’s Center of International Development. This illustration shows what we assume and accept as obvious—that industrialized countries, those countries that have more technology and more capabilities to use technology, are the more economically advanced countries. There is also the national readiness index rank. The countries at the top of this index are the richest countries while the poorest have very little capability with technologies. While we are all familiar with that correlation, the difficulty is interpreting what this means. The dominant interpretation at the moment is that information technology and the capabilities for using it, in other words, the readiness for information society in terms of technology, are tools for development. It could be the opposite as well. It could be that those countries that are already advanced economically and technologically are in a better position to use their technology to further their economic growth. The interesting tricky question here is, if we take the view that technology and information are related to the capacity to analyze information, in what way is information technology a tool for development? For example, it is acknowledged that for the top tier of rich countries, information technology in terms of innovation becomes a competitive weapon and a factor for further economic growth. Of course we know that information technology can be significant for development in many other ways. Nevertheless, a lot of examination, analysis, and critical judgment are required to decipher these data and make sensible use of them. TABLE 10.1 Network Readiness Index Country NRI NRI rank Country NRI NRI rank United States 6.05 1 China 3.10 64 Iceland 6.03 2 Romania 3.10 65 Finland 5.91 3 Ukraine 3.05 66 Sweden 5.76 4 Bolivia 3.04 67 Norway 5.68 5 Guatemala 3.00 68 Netherlands 5.68 6 Nicaragua 2.83 69 Denmark 5.56 7 Zimbabwe 2.78 70 Singapore 5.47 8 Ecuador 2.65 71 Austria 5.32 9 Honduras 2.64 72 United Kingdom 5.31 10 Bangladesh 2.53 73 New Zealand 5.23 11 Vietnam 2.42 74 Canada 5.23 12 Nigeria 2.10 75   SOURCE: Adapted from G. S. Kirkman et al., 2002, The Global Information Technology Report 2001-2002: Readiness for the Networked World, Oxford University Press, New York.

OCR for page 41
Open Access and the Public Domain in Digital Data and Information for Science: Proceedings of an International Symposium This page intentionally left blank.