The gworls that get it: value-laden; the gworls that don't: value-free by Prof. Johnson

 I won't lie, I've been reluctant ti take a class with Professor Johnson because my brain literally cannot do science but that fact that ethics and epistemology underly a lot of the science talk in this paper, makes me very optimistic about taking a class later on. 

With that being said, here are some connections that I drew between the two and some insights that I gained. What Prof. Jonson describes as canons of inductive inferences, seem to me like scientific schema (schema being mental roadmaps that we rely on to navigate our day to day world.) In the same way that schema helps us make sense of our world by using our prior knowledge to interpret our surroundings, Prof. Johnson's canons help scientists to limit the amount of acceptable answers they will apply to a set of data. 

This reminds me of an example we spoke about in tutorial with Prof. Hurley in which a scientist was looking for funding to prove that bacteria was the cause of some stomach sickness (sorry I forgot the name.) This scientist was refused funding from numerous places because there was an already established assumption (canon/schema) that stomach acids kill bacteria and so there is no way the sickness could be bacterial. This claim was made withstanding evidence of bacteria on test plates because those scientist assumed that the bacteria got there not from the stomach but sometime after and so it was factored out. Semi-happy ending, the scientist eventually got the funding he needed after he induced himself with the sickness to prove that it was bacterial. This connects to the problem of programming in Prof. Johnson's paper where "If there's a problematic outcome of the operations of some program, and the programmers have done their due diligence, then the problem must exist in the collection of the data..." (pg. 1) 

What's also interesting about this idea of canon/schema is how it returns to Kuhn's idea about the development of new theories. "The third type of phenomena, the recognized anomalies whose characteristic feature is their stubborn refusal to be assimilated to existing paradigms" (pg. 97.) This reminds me of the idea of schema clash where one's existing schema isn't consistent with an experience or experiences that one has, causing a disruption of their cognitive roadmap and a need to build a new one. 

This relates to Prof. Johnson's paper in that the current schema that is propelling scientist innovation especially in the field of A.I, machine learning, and technology is one obsessed with a value-free or "objective" algorithm. This drive has instead revealed the load of biases built into what is supposed to be unbiased machinery pricing that machine learning is value-laden anyway (except with bad values.) Prof. Johnson provides the example of the COMPAS algorithm. You would think that this experience would cause the schema clash necessary to abandon this value-free pursuit but it doesn't seem to have generally. What accounts for this? It seems that humans know they are naturally flawed especially in decision making, why then do we think we can make a perfect and unflawed decision maker?  We seem to be wanting a false utopia under a false sense of objectivity. Like we discussed with Dr. B, I think it's time that we update our idea of objectivity to one more value-laden. Weirdly,  I think the more biases we are able to include in our programming, the better it would be. By biases I mean identities that hold different epistemic positions (further pushing the idea of standpoint epistemology.) 

One of the importances of this conglomeration of epistemic bodies that we previously discussed was because no single person is able to be objective. Further that not everyone has the capacity to occupy every single epistemic position or that there are obvious hardships for some to occupy certain position. If we group all of our biases into a machine, not only do we eliminate oppressive biases in the process (at least for the meantime,) we create a "being" capable of better occupying multiple positions that we can't as embodied beings. This seems easier said in epistemology than it does in science though. Despite that, there is an ethical obligation that scientist have to achieve this because of consideration for topics discussed in the argument from inductive risk section. 

 

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