This is the second in a list of issues which I believe will need much discussion and the posterior development of feasible decision making processes to ensure a functional biosafety regulatory system, if the decision has been to include socioeconomic considerations.

The socioeconomic impact literature available for India shows a very real problem that regulatory systems will likely face when dealing with regulatory decisions involving socioeconomics. That is, the fact that there will likely be a host of competing socioeconomic impact claims with regard to a specific technology.

In my experience, it can be even get to the point of difficulty, whereas the decision maker face a set of assessments based on the same or similar set of farmers -even the same source database- and then have the assessments reach contrastingly different results as a consequence of the method used and the implementing teams that will conduct the assessment.

After all, when doing an assessment, be it a an economic or a socio-cultural-anthropological assessment especially in an ex ante (before adoption) assessment where there will be a multitude of assumptions used to forecast or provide estimations (be it Social Impact Assessments, Sustainable Livelihoods or Economic Impact Assessments) there is quite a bit of subjectivity involved in the assumptions and scientific tools used to forecast or estimate potential impacts.

The regulatory/decision making process will require having clearly defined rules and decision making standards to ensure that competing claims are properly evaluated and decided upon. Here it is important to note that it is important to have as much detail as needed in implementing regulations, but we have to be cognizant that too much detail can increase the likelihood of regulations becoming inflexible and thus prescriptive. This reduces the opportunities to include innovative assessment alternatives which may make the process more efficient.

I honestly do not want to consider unscrupulous individuals who may manipulate data to reach a predetermined conclusion. This un-ethical and should not be tolerated.