Knowledge

Laboratory Life (Latour & Woolgar) is an ethnography of a neuro-biology laboratory in the 1970’s. The authors perform a phenomenological observation of the activities that occur in a neuro-biology lab, detailing the activities of raising mice, experimenting with them, analyzing their brains and cerebral fluids, and publishing the findings of their lab work in journals. Latour and Woolgar assume no previous knowledge of the neuro-biologists’ behaviors, so their writing about the lab’s activities appears simplistic, much like a National Geographic episode’s description of a tribal shaman’s work. This treatment of a contemporary scientific practice is fascinating and entertaining to read — assuming that you find philosophy of science fascinating and entertaining!


 

The book that raises several questions about humans and how we gather, or create, knowledge.

1. Are one of these categories of knowledge primary? And are one of the binaries within a category primary? Why?

  • apriori / aposterori
  • deductive / inductive
  • phenomenological / analytical
  • experimental / theoretical
  • other dichotomies or models for human knowledge?

2. Is knowledge discovered or created? In other words, is knowledge something that exists independent of the person who knows it, like a rock? Or, is knowledge something that exists as part of the person who knows it, like your experience of the world?

3. Is knowledge contingent on the being, or type of being, that discovered or created it? In other words, if another creature discovered calculus, physics, or biology, would it appear the same way as humans have codified these particular fields? Or, is what we know dependent on how we know it? This question has been asked different ways by philosophers since Plato, but even after millenia, it’s remains an unsettled question.


This book shows one type of human knowledge gathering applied to another type of human knowledge gathering, and that’s something I find fascinating. This is why all of these philosophical questions “fall out” after reading the book.

I’m not sure there is a correct analysis of Laboratory Life, at least not one that I can give. But I think the questions are important in shaping how humans understand our relationship with what we know. Moreover, this relationship doesn’t just apply to academic topics, like trigonometry or sociology. The same analysis can be applied to dogmatic rituals or prophetic experience too.

Scientific and religious knowledge are affected by the way we understand our relationships to these experiences. If we understand a spiritual vision to be something created by a fevered brain, we arrive at different conclusions than if we understand that vision to be a prophetic revelation sent by a deity. Similarly, the validity of a scientific discovery, like that of Benzene, could be questioned: did Kekule see the structure of Benzene as a divine revelation deductive, an intuitive insight, or a fevered dream?

I’m not writing this to attack science or religion. Rather, I think that the foundations of human knowledge are less subject-specific than is popularly believed. Religious and scientific insight appear surprisingly similar, for example, the cases of Kekule’s vision of Benzene’s molecular structure and Mose’s burning bush. Moreover, there are interesting overlaps in human knowledge, where monastic traditions generate and maintain some of the best experimental or analytical research — the case of Gregor Mendel’s genetics research, or the Buddhist Abhidharma “psychological” system, come to mind.

I wonder what useful syntheses of human knowledge might arise if folks allowed themselves to view different categories of knowledge as overlapping fields of experience, rather than distinct “silos” containing knowledge of one type? It seems that some of the most recent advances in human knowledge have arisen because of this type of thinking: computer science as an extension of engineering and formal logic; programming languages as an extension of linguistics and computer science; informatics or business analytics as an extension of biological taxonomy and computer science (perhaps I’m reaching on that?).

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