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journals.sagepub.com journals.sagepub.com
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For example, Librett and Perrone (2010) claim that ethnography operates at ethical and epistemic odds with human-subjects protections, and that university IRBs undermine ethnographic knowledge and discipline-specific ethical practices by risking confidentiality.
I, argue, it is the exact opposite. Ethnographic is defined as: "relating to the scientific description of peoples and cultures with their customs, habits, and mutual differences." The very DEFINITION displays the large importance of people in ethnographic knowledge, and to do this, we have to risk confidentiality with consent, of course. I feel like there is not a big issue as long as there is consent, by I understand the view that keeping things hush hush IS necessary for data collection. To me, you can't really ever have a stalemate or in-between with this type of collection and time period, there will only ever be two polarizing extremes.
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Further, data science methods create an abstract relationship between researchers and subjects, where work is being done at a distant remove from the communities most concerned, and where consent often amounts to an unread terms of service or a vague privacy policy.
This reminds me of the "Atlas of AI" reading, as well as answering my question of when is too much. The inhumane nature of this collection and it being on a mass scale is very reminiscent of "Atlas of AI".
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Publicly available data can be put to a wide range of secondary uses, including being combined with other data sets, that can pose serious risks to individuals and communities.
The question of ethics also comes into play when, again, asking how this data is collected. I refuse to believe this data is always voluntary.
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Critical data studies is in its infancy
I feel like this also provides to how early one can do a critical data study, with infants, although the availability for any type of data will be limited.
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We examine several contentious cases of research harms in data science, including the 2014 Facebook emotional contagion study and the 2016 use of geographical data techniques to identify the pseudonymous artist Banksy.
Before even starting, as I read the abstract, I'm curious how this data was collected, willingly or otherwise. On top of this, it is a very odd question for companies, that are in no way scientific, to ask such personal questions. I feel like this, in a way, set the expectation for what I should expect from this article.
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