Computers: Science and Society Research Paper

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For decades, pundits with scholarly credentials have been predicting that computer and information technology would radically transform both science and society. Ultimately, they may be right, but the apparent changes to date have been limited and often contradictory.

Societal Impact of Computing

It is often said that rationalization, mechanization, and computerization of work contribute to the degradation of skills and thus the demotion of the workforce. Yet the research has shown varying effects: In 1987 William Form reported that technology sometimes led to the loss of skills but at other times required increased skills. Surveying a different large body of research, Jeffrey Liker, Carol Haddad, and Jennifer Karlin reported in 1999 that the consequences for work organization of new technologies are highly variable and contingent on a number of factors, including labor-management relations and the specific social process through which the technology was developed and introduced. Information technology has long been considered a tool that large corporations use to control their workers and governments use to monitor their citizens. This is true both in the United States, where much of the information technology has been developed, and in countries into which such technologies have been introduced, despite their very different social conditions. In 1977 Philip Kraft argued that corporate desires for control over employees led to routinization and fragmentation even of the profession of computer programming itself, with a consequent loss of innovativeness.

Perhaps ironically, 1977 was also the year in which the first really successful personal computer, the Apple II, was introduced, created by a tiny company started by two friends in a garage. Since that time computer innovation has resulted in a remarkable scenario: Visionary individuals develop a prototype of an innovation and found a start-up company, which either becomes a major corporation overnight or is purchased for millions of dollars by an existing major corporation. In many cases, such as Google and the first Web browsers, the innovators were graduate students who received government support from grants to their professors who were working on something only indirectly related.

In 1973 the sociologist Daniel Bell proclaimed “the coming of post-industrial society,” a new form of information-intensive society that would be marked by five primary features:

  1. Economic sector: the change from a goodsproducing to a service economy.
  2. Occupational distribution: the preeminence of theprofessional and technical class.
  3. Axial principle: the centrality of theoreticalknowledge as the source of innovation and of policy formulation for the society.
  4. Future orientation: the control of technology andtechnological assessment.
  5. Decision making: the creation of a new “intellectualtechnology.”

In such a postindustrial society, social scientists and information scientists might have been expected to enjoy great prestige and their profession to have achieved a position of dominance. Yet in the United States, where modern information technology largely arose, almost the opposite has occurred. Since 1982, when the Reagan administration sought to eradicate social science from the National Science Foundation and did succeed in cutting budgets to 40 percent of their prior levels (and cutting all budgets for social scientists; Larsen 1992), the influence of social scientists (other than economists and, rarely, demographers) on American policies has been insignificant. During the Clinton administration of the 1990s, there was a brief government flirtation with social science as applied to the Internet, before the second Bush administration ended it.

The so-called digital divide was the subject of much discussion in the mid- to late 1990s. The term refers to the tendency of disadvantaged groups to have less access to the Internet, and thus to information in general, than other more privileged groups. When numerous studies found this digital divide in schools as well as in the adult world, some voiced concerns that computers, though they might have the potential to reduce socioeconomic inequality, were actually increasing it. By this logic, government should invest in Internet-related technologies as a fundamental solution for social problems stemming from poverty and lack of opportunities for education. Once most middle-class households hooked up to the Internet on home computers, the novelty of the issue faded, and unequal access to information came to be taken for granted.

Internet and other modern computer technologies raised ethical issues that were mostly updated versions of old ones—for example, product liability, with software manufacturers forcing customers to agree to licenses in which the producers promised nothing. Some of these ethical issues may be more acute in the information context, notably those concerning privacy and intellectual property rights, but they are not unprecedented. An extended debate has raged over whether computers degrade social relationships in society, enhance them, or merely provide a new environment in which they may take place. As Leah Lievrouw (2003) has observed, the Internet has become contested territory on which individuals and small groups assert their autonomy, major corporations monopolize attention and attempt to criminalize activities that threaten profits, and activists launch counterattacks against corporate tyranny. This is seen not only with respect to file sharing of music, but also blogs revealing government or corporate secrets, posting of programs called “mods” (modifications) that alter commercial software, and coopting commercial chatrooms to organize radical cultural, political, sexual, and economic networks. Ray Kurzweil, among the most influential computer entrepreneurs and visionaries, argues in his 2005 book that technology is driving humanity toward a singularity, utterly transforming human life during the present century. He raises the possibility that humans may no longer be limited to biological bodies but dwell within robots or computers, and that artificial intelligences will surpass human intelligence. Whatever one thinks of this extreme possibility, Kurzweil suggests an interesting principle that puts all such prognostications in context: People tend to overestimate the near-term impact of a technological revolution and to underestimate the long-term impact. Social scientists have tended to stumble along these lines, asserting that the computer revolution has arrived but not contemplating where and when its greatest impacts will be felt.

Implications for Social Science

Arguably, the computer revolution began for social science at the beginning of the twentieth century, when Hermann Hollerith developed programmable, punchcard counting machines to analyze data from the 1900 U.S. census and founded what later became the IBM corporation. Thus social-science computing is a mature field, yet many promising computer methods are underused in the social sciences.

After decades of development, computer simulation still has only a marginal position in most of the social sciences. In 1974 Donella Meadows and colleagues published a dire and influential warning about the human future, called The Limits to Human Growth, based on computer simulations of the global socioeconomic system; but three decades later social scientists were still debating whether the approach has merit. A number of social scientists with classical training have taken up computer simulation as a methodology for developing theory and testing its logical consistency. For example, William Bainbridge (2006) used a system of 44,100 artificial intelligent agents to model the way that religious cognitions and social influences interact in a community the size of a small city. But much of the simulation work on human societies ignores traditional work on the same topics, thereby failing to integrate the simulation community with the rest of social science. A striking but not unusual example is the otherwise excellent textbook, Simulation for the Social Scientist (2005), by Nigel Gilbert and Klaus Troitzsch, which cites in its extensive Bibliography : almost none of the simulation studies published in mainstream social science journals.

The general field of human-centered computing (HCC), including the subfields called human-computer interaction (HCI) and computer-supported cooperative work (CSCW), has become major research territory, although a large fraction of the scientists come from outside the classical social sciences, and very little of this work is published in mainstream social science journals. The goal of these HCC researchers is generally to develop or evaluate hardware or software systems, rather than test general theories, and their methodologies rarely meet social science standards of rigor. This “wild west phase” in the history of HCI and CSCW may be coming to an end, as evidenced by the papers presented at the international Communities and Technologies conferences that tend to cite a good mixture of traditional social science along with computer science work on Internet-based communication networks.

Although every social scientist today uses Internet search engines, few seem to realize that they are versatile tools for social analysis, and that other potentially useful tools can be found on commercial Web sites. A Web search engine needs not only to find Web sites that contain a particular word, but also to arrange the Web sites in descending order of probable value to the user, on the basis of natural language processing (NLP) and analysis of the network of links connecting Web sites. These methods could be used by social scientists to map the culture and society that produced all the Web sites. Business sites, such as Amazon and Netflix, include recommender systems (or collaborative filtering systems) that create advertisements personally tailored for the individual user, based on the buying patterns and expressed preferences of previous customers. Applied, for example, to books about politics, these methods could tell political scientists much about how citizens view leaders and issues. Even as social scientists study the impact of information technology on the rest of society, they should contemplate how it might transform their own disciplines, for good or ill.


  1. Attewell, Paul. 2001. The First and Second Digital Divides. Sociology of Education 74 (3): 252–259.
  2. Bainbridge, William Sims, ed. 2004. Berkshire Encyclopedia of Human-Computer Interaction. Great Barrington, MA: Berkshire.
  3. Bainbridge, William Sims. 2006. God from the Machine: Artificial Intelligence Models of Religious Cognition. Lanham, MD: AltaMira.
  4. Bell, Daniel. 1973. The Coming of Post-Industrial Society: A Venture in Social Forecasting. New York: Basic Books.
  5. DiMaggio, Paul, Eszter Hargittai, W. Russell Neuman, and John P. Robinson. 2001. Social Implications of the Internet. Annual Review of Sociology 27: 307–336.
  6. Form, William. 1987. On the Degradation of Skills. Annual Review of Sociology 13: 29–47.
  7. Freiberger, Paul, and Michael Swaine. 1999. Fire in the Valley: The Inside Story of Silicon Valley’s Computer Pioneers. Foster City, CA: IDG Books.
  8. Gilbert, Nigel, and Klaus G. Troitzsch. 2005. Simulation for the Social Scientist. Buckingham, U.K.: Open University Press.
  9. Kizza, Joseph Migga, ed. 1996. Social and Ethical Effects of the Computer Revolution. Jefferson, NC: McFarland.
  10. Kurzweil, Ray. 2005. The Singularity Is Near: When Humans Transcend Biology. New York: Viking.
  11. Larsen, Otto N. 1992. Milestones and Millstones: Social Science at the National Science Foundation, 1945-1991. New Brunswick, NJ: Transaction.
  12. Lievrouw, Leah A. 2003. When Users Push Back: Oppositional New Media and Community. In Communities and Technologies, eds. Marleen Huysman, Etienne Wenger, and Volker Wulf, 391–406. Dordrecht, Netherlands: Kluwer.
  13. Liker, Jeffrey K., Carol J. Haddad, and Jennifer Karlin. 1999. Perspectives on Technology and Work Organization. Annual Review of Sociology 25: 575–596.
  14. Meadows, Donella H., et al. 1974. The Limits to Growth. 2nd ed. New York: Universe Books.
  15. Van Den Besselaar, Peter, et al., eds. 2005. Communities and Technologies 2005. Dordrecht, Netherlands: Springer.
  16. Wellman, Barry, et al. 1996. Computer Networks as Social Networks: Collaborative Work, Telework, and Virtual Annual Review of Sociology 22: 213–238.

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