[
]1Interesting new paper
Johnson, J. A. (2014). [The Ethics of Big Data in Higher
Education.]2 International Review of Information Ethics, 7.
although I think unfair to at least some (but certainly not all)
data-mining research efforts so far. Argues that, insofar as they limit
autonomy, course recommender systems and similar data-mining ‘products’
are problematic, and should explicitly (and on a case-by-case basis)
justify their ethical position with regard to such limiting (e.g. saving
tax payers money, helping students with their original aims – to gain
education, etc.). Also argues empirical and normative assumptions built
into data mining process, which can be obscured (by data-scientists
tending towards scientism) and lead to a ‘fetishization of the
scientific method’ (p.5) e.g. through policies such as PISA. Suggests
that an alternative model would critically evaluate methods and evidence
before assuming causal relations. Overall suggests considering
data-mining as part of ‘technosocial system’, particularly focussing on
policies in which data-mining will play a role. “The ethical questions
presented in data mining will be clearer when building a data mining
model is situated in relation to the perceived need for the policy, the
interventions that are proposed, the expected outcomes of the policy,
and the ways in which the policy will be evaluated; problems such as
incompatibilities between the assumptions of the data model and those of
the intervention will only be apparent from this perspective.” (p.6).
Through such analysis, data mining can deliver on its potential,
ethically and effectively. If you like this area, you might also like
my paper: Knight, S., Buckingham Shum, S., & Littleton, K. (2014).
[Epistemology, assessment, pedagogy: where learning meets analytics in
the middle space]3. Journal of Learning Analytics, In-press.
Footnotes
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