In this overview article, I have provided examples that illustrate the growing importance of exposure as a scientific discipline that supports the process of risk assessment and risk management. One issue that recurs throughout this review is the need to address many types of 'multiples' in the quantification of human exposure. We see the need to address multiple environmental media (air, water, soil); multiple exposure pathways (or scenarios); multiple exposure routes (inhalation, ingestion, dermal); multiple chemicals; multiple population subgroups; and multiple health endpoints. Practitioners of the exposure assessment are now developing measurement and modeling strategies for interpreting from environmental and biomarker measurements the relative contribution of indoor, local, regional, and global sources. In the exposure field, we see a need for exposure models and databases that can address multiple space and time scales. For human populations, total exposure assessments that include time and activity patterns and microenvironmental data reveal that an exposure assessment is most valuable when it provides a comprehensive view of exposure pathways and identifies major sources of uncertainty. In any issue involving uncertainty, it is important to consider a variety of plausible hypotheses about the world; consider a variety of possible strategies for meeting our goals; favor actions that are robust to uncertainties; favor actions that are informative; probe and experiment; monitor results; update assessments and modify policy accordingly; and favor actions that are reversible (Ludwig et al., 1993). In order to make an exposure assessment consistent with such an approach, it should have both sensitivity and uncertainty analyses incorporated directly into an iterative process by which premises lead to measurements, measurements lead to models, models lead to better premises, and better premises lead to additional but better informed measurements, and so on. In 1996, the U.S. EPA Risk Assessment Forum held a workshop on Monte Carlo Analysis. Among the many useful discussions at this meeting was a call for a 'tiered' approach for probabilistic analysis, which is iterative and progressively more complex. The need for formal uncertainty analysis and a tiered approach will require the development by the exposure assessment community of new methods and will put greater demands on the number and types of exposure measurements that must be made.