ABSTRACT
Expert system technologies are varieties of artificial intelligence (AI) approaches in which decision-making knowledge is codified and modeled. This design case has the challenging task of characterizing this set of technologies during a particularly important period in its development (1984–1991), with an emphasis on particular systems used in food production by Campbell Soup. It analyzes the social and research impacts of early, pioneering information elicitation and processing strategies that focused on the distillation of the know-how of individuals construed as experts in particular arenas, approaches broadly labeled as “knowledge-based engineering” (KBE). Widely-publicized notions of “thinking machines” and “canned experts” provided motivation for a good deal of early expert systems development, with accusations of “hype” often levied. This article historically situates these technological strategies in 1984–1991 period, then links them with current instructional systems approaches that more fully involve collaborative elements as well as contextual perspectives. The article also explores the circumstances and consequences of “failures” of system development, with expert systems providing widely-discussed exemplars. This article is rooted in the assumption that historically-informed perspectives can provide useful underpinnings to the building of humane and sustainable research projects, particularly in areas that have human subjects and volatile contexts as essential elements.
