Returning human factors to an engineering discipline: expanding the science base through a new generation of quantitative methods--preface to the special section.

ENGINEERING IN HUMAN FACTORS Human factors is a disparate discipline. Academic programs in human factors are found in departments of industrial engineering, psychology, mechanical engineering, architecture, optometry, and elsewhere. Human factors professionals are employed in a variety of industries, at many levels in the organization chart, and hold an equally disparate array of job titles. However, many hold job titles along the lines of "human factors engineer," and many academic programs housed outside engineering departments still refer to an engineering component in their program -- for instance, many human factors programs in psychology departments are termed engineering psychology. Thus, despite the fact that the field is far from uniform or unitary, there is clearly a strong engineering presence. Is this merely a label or is this how human factors is actually practiced? The Accreditation Board for Engineering and Technology (ABET, which accredits for engineering higher education in the United States) defines engineering as "the profession in which a knowledge of the mathematical and natural sciences gained by study, experience, and practice is applied with judgment to develop ways to utilize economically the materials and forces of nature for the benefit of mankind" (ABET, 2003, back cover). For the purposes of this discussion, we will focus on the "mathematical and natural sciences" aspect of this definition. To what extent do mathematical and natural sciences guide work in human factors? It is our contention that the answer to this question has changed over time and, indeed, has been somewhat cyclical. Consider two relatively influential publications from two different points in time: 1984's Advances in Man-Machine Systems Research (volume 1), edited by Rouse, who was originally trained as an engineer, and 2001's Advances in Human Performance and Cognitive Engineering Research (volume 1), edited by Salas, who was originally trained as an industrial/organizational psychologist. The Rouse volume is replete with equations and formalisms, whereas in the more recent Salas volume such presentations are largely (though not entirely) absent. This is in no way a criticism of the work that appears in the Salas volume, but we believe this reflects the realities of the problems approached by human factors researchers over that span of 17 years. In particular, many of the equations and formalisms presented in the Rouse volume deal with control theoretic models of manual control, whereas the Salas volume tackles a much more cognitively oriented set of issues. In those intervening 17 years, obviously psychological constru cts such as "situation awareness" have risen to the forefront in the field of human factors. This orientation has allowed human factors practitioners to address complex problems in domains with much broader scope than manual control. We see this shift as being driven, at least in part, by a raft of new technologies. These technologies have tended to shift the responsibilities of human operators from manual control to monitoring and directing complex, automation-driven systems. The cockpit of a commercial 777 jetliner produced in 2001 has as much onboard computer processing power as many universities and medium-sized corporations had, organization-wide, just 20 or 30 years ago. Pilots of such modern aircraft may deal with manual control problems if they choose not to use the automation available to them, but now they have a host of other systems to monitor and manage. As the differences between the Rouse (1984) and Sales (2001) volumes reflect, this change in the character of many essential human factors problems has naturally given rise to a change in methodology and terminology. Even the best, most quantitatively accurate manual control model does not scale up to issues of crew coordination and training. However, this change has de-emphasized, at least to some extent, the use of methods and practices found in mathematics and natural sciences, a "de-engineering" of the field. …