this trend, for example, the annual Computer Applications and Quantitative Methods in Archaeology Conference, which, after more than twenty-five years, attracts a growing number of archaeologists from around the world.

This trend has been characterized as a step forward to the ultimate full-fledged embracing of IT by archaeologists. In an evolutionary scheme akin to the Danish archaeologist c. j. thomsen’s three-age system, the evolution of computer applications in archaeology can be considered as follows: the 1960s were the age of exploration; the 1970s, the age of implementation; the 1980s, the age of exploitation; and the 1990s, the age of information.

Quantitative Applications

In the 1960s, the age of exploration, statistics represented the main practical application of computers to archaeology. The facts that the statistical packages used were developed for mainframe computers and that archaeologists interested in this type of analysis had to have certain knowledge of the programming languages limited the generalized adoption of computers to a certain extent. Nevertheless, toward the second half of the 1970s, there was a noticeable shift in how archaeologists approached their data.

Archaeologists became aware of the need to present and analyze their data in a numerical form, and this shift was fostered by the development of radiocarbon dating, on the one hand, and the development of easier programming languages—e.g., Fortran—on the other. Although statistical applications experienced a decline in the mid-1980s, perhaps as a reaction against the alleged scientism of processual archaeology on the part of postprocessual archaeologists, the development of commercial statistical packages for the personal computer (PC), along with the impact of multivariate statistics, provoked a resurgence of this approach in the 1990s. Overall, it can be said that statistics has remained a favored computer-based application in archaeology throughout time.

Equally favored since the 1970s has been the use of computers in database management. Originally designed to keep museum and site inventories on mainframe computers, the development of PC-based programs (e.g., Dbase, Access) has sparked interest in this application. Currently, the development of metadata (i.e., data that documents information about datasets while allowing the expedient transfer and sharing of data between users) has opened the possibility of having access to the enormous resources contained in museum collections and site reports from other research institutions.

Artificial Intelligence and Expert Systems

The 1980s witnessed the emergence of what was presaged as being a revolutionary approach to archaeological problem solving: artificial intelligence (AI) and expert systems. Simply described, AI is a system by which computers are programmed to process data following a rationale similar to that of the human brain. In other words, the goal was to teach computers how to “think” like people. An outcome of AI was the development of expert systems, or programs that can replicate the combined knowledge of human experts addressing a specific problem in order to solve it. By mimicking the advice-giving capabilities of human experts, expert systems can offer intelligent advice or make an intelligent decision about how to solve a problem.

The proponents of this new methodology believed the multidisciplinary nature of the archaeological issues provided the ideal environment in which expert systems could thrive. However, despite the initial clamor and success stories in other disciplines, expert systems have not been fully embraced by archaeologists. Its critics argued that despite the expedient access to expert knowledge that expert systems offered, their main drawback lay in their limited or nonexistent ability to reproduce the uniquely human capabilities of common sense, creativity, and learning. Furthermore, some archaeologists expressed concern that an overreliance on expert systems could be detrimental to the development of archaeological theory.

Attempts to overcome some of the limitations were undertaken, but apparently the momentum was lost. Expert systems gained a moderate level of popularity in archaeology toward the latter part of the 1980s but eventually lost favor and have been practically abandoned,