ABSTRACT
The Italian philosopher Giambattista Vico is best known for comparing methods on truth finding in philosophy and science. In an earlier work referenced here, he discussed briefly “socialis commodis” as the social life we live full of advantages we enjoy [1]. He argues humanity may simply have no relationship to the truth as it is transcendent. Nonetheless, even the selfish human establishes an intelligent order of sorts. Striving for intelligent order we devise methods like life cycle analysis but plagued by things like uncertainty as imperfect beings we sometimes fail miserably. Life cycle analysis (LCA) claims to be a holistic and comprehensive way of examining and evaluating whether phenomena possess a problematic environmental health and safety footprint. Conceptually, it is hardly refutable on its face. However, proponents of LCA have
done a less than admirable job finding ways to incorporate the common interests of society into their algorithms. This chapter will examine three classes of challenges focusing on nanotechnology and emerging technologies. First, how is it possible to develop a diagnostic like LCA when the levels of uncertainty associated with emerging technologies, in this instance nanotechnology, remain so high? Populating an LCA with meaningful data is challenged by what remains unknown about nanotechnology. This problem is not limited to what we know and do not know about the toxicology of nanoparticles, although this receives a lot of attention. The intrinsic interdisciplinary nature of the fields composing nanoscience and nanotechnology may perpetuate this problem as well. Uncertainty is especially problematic when we attempt to include data about societal interests some of which is qualitative and some quantitative. Second, deciding where to include data about societal interests in an LCA has not been established in the prevailing LCA models. While societal concerns can be justified at different points in LCA, we must decide whether societal interests belong at every major decision node in an LCA or at some particular points and not others. While it is politically correct to argue societal interests are important at every point, locating debates over social dimensions at every node might be self-defeating. Saying social dimensions data belong everywhere in an LCA model may result in it included nowhere. And, if experience serves as a guide, as LCA is designed it is imperative we determine how and when societal interests function in the analysis, else societal interests become an afterthought. Similar to the relegation of social scientists to the concluding session in conferences on nanotechnology, failing to plan for the inclusion of societal interests data into LCA may relegate it to window-dressing, which might complicate the relationship between nanotechnology scientists and the public. We know public reluctance about engagement activities, like consensus conferences, has been dominated by relevance issues. If the public perceives its participation is predominantly symbolic, the gap between science and engineering and public understanding will widen further. Third, LCA like most other forms of risk assessment is not optimal when data is incomplete. However, risk managers have been reluctant to consider new ways of assessing risk that is not dominated by explicit and finite projections of exposure and dosage.
