Norwood Russell Hanson authored one of the most significant attacks on traditional empiricism with ther argument that all data is 'theory-laden', that is, that what counts as data depends on how we interpret what we perceive. The figures in the image above, for example, may resemble antelopes, but in a different context, the same figures may be interpreted as pelicans. Why is this important? As we enter the era of 'big data' we are forgetting that what we find in data analysis depends very much on what we are looking for. This is Kate Crawford's message in The Hidden Biases in Big Data. "As we move into an era in which personal devices are seen as proxies for public needs, we run the risk that already existing inequities will be further entrenched. Thus, with every big data set, we need to ask which people are excluded. Which places are less visible? What happens if you live in the shadow of big data sets?" Good questions. For more scepticism on big data, this list of articles from Metafilter is also recommended.
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