How can we mitigate ethical and privacy issues in data science? Prof Alan Smeaton talks to Silicon Republic
Insight cites ethical research and data ethics as a central concern. Its new website www.magnacartafordata.org explores this area in detail. Now these issues are squarely in mainstream consciousness and Professor Alan Smeaton recently spoke to Silicon Republic about it.
For example, he explained how “bias creep” can occur relatively easily in datasets, “unless we are aware of it, take appropriate action and be cognisant of it when we look at our outcomes from using those data sources”.
Sampling bias is one of the biggest obstacles data scientists face, according to Ross. He posed the question: “Can we be sure that the data we collect to train our model on is an accurate reflection of the full population that our model will later be applied to?” If the answer is no, gender bias, racial bias and even financial bias could all occur as a result of the initial skewed dataset.
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