Scale: The Law of Large Numbers

A. It is an interesting conundrum that is brought as we transition from traditional humanities to digital humanities; as the author suggests, there is abundantly more humanitarian works to sift through and analyze. The law of large numbers usually yields a better, unbiased understanding of the hypothesis as the data goes towards the true mean, or rather in the case of humanitarian research the “objective” truth. B. With the advent of more and more texts/articles, digital humanities research becomes similar to scientific research, as the analysis of the data is impossible to do by human minds; In this case, leaning towards machine learning algorithms for further analysis is crucial to understand the testimonies on a macro scale. But the question then becomes, how are these machine learning algorithms trained to avoid making biased conclusions when given a large sample of objective data? I personally believe that even with the more traditional analysis with printed media, there was still bias hidden within the researchers; but the scale at which machines can lead to biased conclusions is nothing short of alarming.

Distributed Knowledge Production and Performative Access

A. The way the author describes the knowledge production being a collaborative process among many generations is extremely similar to how the author of Short Guide to Digital Humanities refers to what Big Humanities research; The ability to develop a collective consciousness that not only analyzes the humanitarian work in question, but also does various different jobs to illustrate that analysis in everyday technological tools for the broader audience to view and contribute to. The quote “Distributed knowledge production means that a single person cannot possibly conceive of and carry out all facets of a project” perfectly summarizes this point. But is this an inherent truth concerning digital humanities, that was not characteristic of traditional humanities, in which researchers of the printed world worked in solitude to analyze bodies of text? I wouldn’t go so far as to call this characteristic dishonest but it might be the case that this way of collaborative engagement evolved as a result of digital media. B. Similarly, the author illustrates that performative access illustrates the ability for the audience to engage with the knowledge/content curated through multiple digital platforms. Through the digital age, the author asserts that the information overload will have a way of uniting multiple audiences together, forming an almost collective, intelligent reader capable of making analyses over the revised work. The author suggests that the act of viewing the living body of work is itself a performance, which I don’t know how much I agree with the notion that reading and writing a body of work are in the same category; if, however, the knowledge is somehow proven to be interpreted and absorbed by the reader, one can then have the conversation that the acts are somewhat identical.

Written by Omozusi Guobadia