This week I dove into my first situated context: precision agriculture in California. Through this process I created an Actor-Network map:
This really helped to organize my thoughts around California agriculture and got me to think about several actors and relationships that I need to research further. A big actor that has currently been mostly absent from my research is the USDA I have also considered policymakers as part of my capstone, but I didn’t really know what that looked like until looking at USDA’s Environmental Quality Incentive Programs (EQUIPs) which provide incentives for precision ag technologies on the basis that they decrease pollution/runoff in the surrounding environment. I plan to look further in this incentive program and look for other applicable regulations or incentives that might encourage or discourage technology adoption.
This concept map also helped to start thinking about the key differences between California and India. One key difference that was highlighted was the relationship between farm owners and laborers. Namely, India has many, many more people involved and willing to be involved in agriculture. This is a huge barrier to precision agriculture adoption, as the technology can replace low-level jobs. In California, this is a plus as there are less migrant laborers than ever, but in India, this may be a big disincentive. Another huge difference to account for is the sustainable development problem of food security, which is much bigger in India. I’m not sure yet what role precision technologies can play in establishing food security, but it will be an important dimension going forward.
Overall, I feel a lot more secure in my situated context after this activity, and it highlighted a number of areas for which I will need to focus my attention. In the near future, I will need to make an actor-network map for India and will continue to update this actor-network map as I learn more through my research.